I lead the Ecosystem Dynamics Health and Resilience research program within the School of Life Sciences, a key UTS research strength.
My ecological impacts of climate change research involve the use of ground, tower and satellite measures to analyse ecosystem responses and resilience to climate forcings and extreme events. This research extends to landscape ecology, phenology, ecohydrology, and monitoring extreme drought/ wet/ heat events.
I look at vegetation dynamics, landscape phenology processes, and their shifting seasonalities with climate variability. Recently, I used remote sensing and field measurements to understand the phenology patterns of tropical rainforests and savannas in the Amazon and Southeast Asia and my Amazon work was featured in a National Geographic television special entitled "The Big Picture".
Currently my research involves coupling eddy covariance tower flux measurements with ground spectral sensors and satellite observations to study carbon and water cycling across Australian landscapes.
I am actively involved with several international space programs, including the NASA-EOS MODIS Science Team, the Japanese JAXA GCOM-SGLI Science Team, the European PROBA-V User Expert Group, and NPOESS-VIIRS advisory group.
Member, International Society for Photogrammetry and Remote Sensing
Member, American Geophysical Union
Member, Surveying & Spatial Sciences Institute
Member, The Institution of Electrical and Electronic Engineers
Member, Association for Tropical Biology and Conservation
Can supervise: YES
- Ecosystem responses to climate forcings and drought
- Functional phenology measures and climate-induced biome shifts in seasonality
- Satellite - flux tower integrations for carbon and water models
- Tropical savanna and rainforest dynamics
- Land-ocean interactions and feedback
- Phenology (pollen) - public health studies
- Development of an AusCover- Sydney Node, TERN Education Investment Fund (EIF),
- Spectral Sampling Tools for Vegetation Biophysical Parameters and Flux Measurements in Europe, COST Action program, ES0903.
- Scaling photosynthesis in tropical systems: from forest to savanna, from seasons to extreme events, NASA, co-CI,
- Development of SGLI Time Series Vegetation Indices for Long Term Climate Studies, Collaborative research agreement for the Global Change Observation Mission, Japan Aerospace Exploration Agency (JAXA),
- Evaluation and Validation of NPP VIIRS Vegetation Index EDR for Earth System and Climate Sciences, NASA, co-I.
- Integration of Airborne Dust Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health Decision Support Systems, NASA Applied Sciences- Public Health, co-I.
- New Approaches for Vegetation Index Time Series Evaluation, NOAA-Univ of Maryland.
Chuvieco, E & Huete, A 2009, Fundamentals of Satellite Remote Sensing, 1st, CRC/Dekker, Taylor & Francis Informa Group, Boca Raton, Florida USA.
ESCADAFAL, R & HUETE, AR 1991, INFLUENCE OF THE VIEWING GEOMETRY ON THE SPECTRAL PROPERTIES (HIGH-RESOLUTION VISIBLE AND NIR) OF SELECTED SOILS FROM ARIZONA, EUROPEAN SPACE AGENCY.
HUETE, AR, QI, J, CHEHBOUNI, A, LEEUWEN, W & HUA, G 1991, NORMALIZATION OF MULTIDIRECTIONAL RED AND NIR REFLECTANCES WITH THE SAVI, EUROPEAN SPACE AGENCY.
QI, J, MORAN, MS, HUETE, AR, JACKSON, RD & CHEHBOUNI, A 1991, VIEW-ATMOSPHERE-SOIL EFFECTS ON VEGETATION INDEXES DERIVED FROM SPOT IMAGES, EUROPEAN SPACE AGENCY.
Huete, AR 1988, Soil spectral filtering for improved biomass assessment in arid ecosystems.
Remote sensing of agriculture, forest and rangeland frequently involves the measurement of two or more components (plants, soil, atmosphere, etc) in the presence of each other. In this study, factor analysis is used to filter the soil background response and extract the spectra of the vegetation from measurements made over a desert grassland. The extracted vegetation spectra are compared to the original spectra as to their ability to assess green biomass. Green biomass sensitivity is found to be significantly improved with the use of factor analytic separation techniques. -from Author
Peng, D, Wang, Y, Xian, G, Huete, AR, Huang, W, Shen, M, Wang, F, Yu, L, Liu, L, Xie, Q, Liu, L & Zhang, X 2021, 'Investigation of land surface phenology detections in shrublands using multiple scale satellite data', Remote Sensing of Environment, vol. 252.View/Download from: Publisher's site
© 2020 Elsevier Inc. Shrublands occupy about 13% of the global land surface, contain about one-third of the biodiversity, store about half of the global terrestrial carbon, and provide many ecosystem services to a large amount of world's human population and livestock. Because phenology is a sensitive indicator of the response of shrubland ecosystems to climate change, the alteration of ecosystems following species invasions, and the dynamics of shrubland ecosystem function, biodiversity, and carbon budgets, it is critical to monitor and assess phenological dynamics in shrubland ecosystems. However, most current land surface phenology (LSP) products derived from satellite data do not provide phenology detections in some semiarid shrublands where the amplitude of seasonal vegetation greenness is small. Therefore, we investigated the LSP detection using multiple spatial resolution satellite data and examined the impacts of spatial scales and shrubland ecosystem components (shrub and herb cover) on LSP detections over the western United States. Specifically, greenup onset date (GUD) in shrublands was detected from 30 m Harmonized Landsat and Sentinel-2 (HLS) data and 500 m Visible Infrared Imaging Radiometer Suite (VIIRS) data to quantify scale effects. The GUD spatial patterns were explored with 30 m pixel variations in shrubland ecosystem components. The results show that GUD values varied with percent vegetation cover and shifted to earlier dates with increasing vegetation cover, demonstrating that satellite observations were not able to capture greenup onset until a threshold of green vegetation cover is reached. GUD was mostly undetectable from both HLS and VIIRS pixels with vegetation cover less than 10% and became fully detectable with vegetation covers larger than 50%. Similarly, the differences of GUD between HLS and VIIRS detections also decreased with increased vegetation cover. As a result of high shrubland heterogeneity, GUD from 30 m HLS pixels could b...
Ma, X, Huete, A, Tran, NN, Bi, J, Gao, S & Zeng, Y 2020, 'Sun-angle effects on remote-sensing phenology observed and modelled using himawari-8', Remote Sensing, vol. 12, no. 8.View/Download from: Publisher's site
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Satellite remote sensing of vegetation at regional to global scales is undertaken at considerable variations in solar zenith angle (SZA) across space and time, yet the extent to which these SZA variations matter for the retrieval of phenology remains largely unknown. Here we examined the effect of seasonal and spatial variations in SZA on retrieving vegetation phenology from time series of the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) across a study area in southeastern Australia encompassing forest, woodland, and grassland sites. The vegetation indices (VI) data span two years and are from the Advanced Himawari Imager (AHI), which is onboard the Japanese Himawari-8 geostationary satellite. The semi-empirical RossThick-LiSparse-Reciprocal (RTLSR) bidirectional reflectance distribution function (BRDF) model was inverted for each spectral band on a daily basis using 10-minute reflectances acquired by H-8 AHI at different sun-view geometries for each site. The inverted RTLSR model was then used to forward calculate surface reflectance at three constant SZAs (20°, 40°, 60°) and one seasonally varying SZA (local solar noon), all normalised to nadir view. Time series of NDVI and EVI adjusted to different SZAs at nadir view were then computed, from which phenological metrics such as start and end of growing season were retrieved. Results showed that NDVI sensitivity to SZA was on average nearly five times greater than EVI sensitivity. VI sensitivity to SZA also varied among sites (biome types) and phenological stages, with NDVI sensitivity being higher during the minimum greenness period than during the peak greenness period. Seasonal SZA variations altered the temporal profiles of both NDVI and EVI, with more pronounced differences in magnitude among NDVI time series normalised to different SZAs. When using VI time series that allowed SZA to vary at local solar noon, the u...
Senanayake, S, Pradhan, B, Huete, A & Brennan, J 2020, 'Assessing Soil Erosion Hazards Using Land-Use Change and Landslide Frequency Ratio Method: A Case Study of Sabaragamuwa Province, Sri Lanka', REMOTE SENSING, vol. 12, no. 9.View/Download from: Publisher's site
Shen, J, Huete, A, Ma, X, Ngoc, NT, Joiner, J, Beringer, J, Eamus, D & Yu, Q 2020, 'Spatial pattern and seasonal dynamics of the photosynthesis activity across Australian rainfed croplands', ECOLOGICAL INDICATORS, vol. 108.View/Download from: Publisher's site
Wongsai, N, Wongsai, S, Lim, A, McNeil, D & Huete, AR 2020, 'Impacts of spatial heterogeneity patterns on long-term trends of Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature time series', Journal of Applied Remote Sensing, vol. 14, no. 1.View/Download from: Publisher's site
© 2020 Society of Photo-Optical Instrumentation Engineers (SPIE). Land surface temperature (LST) is a crucial parameter for global climate change studies. LST changes are also directly associated with the large-scale changes in land cover. Previous studies carried out a comparative analysis of satellite-derived LST response between periods before and after homogenous land cover changes. We present an alternative approach that quantifies long-term LST variability in response to various land use/land cover change (LULCC) patterns over Phuket Island, Thailand, from 2003 to 2017. First, four Moderate Resolution Imaging Spectroradiometer (MODIS) overpass times of LST time series were adjusted for seasonal effects using a cubic spline function to preserve the number of original data and enable estimates of LST dynamics and trends using the generalized least squared models. Second, LULCC patterns were classified according to land cover type conversion and spatial pattern transformations between the years 2000 and 2016. Spatial homogeneity and heterogeneity were quantified by the coverage percentage for each land use and land cover (LULC) type within a given location. Finally, the influence of LULCC patterns on the long-term spatiotemporal behavior of LST was assessed using the generalized estimating equation model. Results showed that different land cover transitions influence the dynamics of daytime LST but not the nighttime LST. The proportion of different land cover types within an LST pixel and transition amounts contributed to the quantity of increasing surface temperature, especially over impervious surface types. Diverse LULCC patterns with considerations of spatial heterogeneity improved our insight about a relatively strong effect of combined LULC types on LST responses. The climatic effect through the gradual conversion of heterogeneous land cover is necessary to be considered in climate research studies.
Wongsai, N, Wongsai, S, Lim, A, McNeil, D & Huete, AR 2020, 'Statistical model for land surface temperature change over mainland southeast Asia', International Journal of Geoinformatics, vol. 16, no. 2, pp. 33-39.
© Geoinformatics International. This study presents an alternative statistical methodology for estimating changes in land surface temperatures over mainland Southeast Asia (SEA). The method comprises of seasonal adjusting and autocorrelation filtering of MODIS LST time series obtained from 2000 to 2019 at systematic 45 sample locations. Furthermore, the filtered seasonal-adjusted LST time series were estimated to quantify the decadal change of LST using linear regression model. The long-term dynamic of temperature change was revealed by curve fitting using a spline model with different knots. The overall LST changes in sub-regional and regional scale were estimated using multivariate regression model which adjusted for spatial correlation and aggregated information of LST change from all individual sample locations irrespective of their strength of statistical evidence (p-value). The final result showed that the surface temperature change in the SEA region increases by 0.126 °C/decade. 95% confident interval for increasing ranges between 0.04 to 0.21 °C/decade, which shows evidence of substantial warming surface in this region.
Zeng, Y, Li, J, Liu, Q, Huete, AR, Xu, B, Yin, G, Fan, W, Ouyang, Y, Yan, K, Hao, D & Chen, M 2020, 'A Radiative Transfer Model for Patchy Landscapes Based on Stochastic Radiative Transfer Theory', IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, vol. 58, no. 4, pp. 2571-2589.View/Download from: Publisher's site
Ma, X, Huete, A, Moore, CE, Cleverly, J, Hutley, LB, Beringer, J, Leng, S, Xie, Z, Yu, Q & Eamus, D 2020, 'Spatiotemporal partitioning of savanna plant functional type productivity along NATT', REMOTE SENSING OF ENVIRONMENT, vol. 246.View/Download from: Publisher's site
Zhang, M, Wang, B, Cleverly, J, Liu, DL, Feng, P, Zhang, H, Huete, A, Yang, X & Yu, Q 2020, 'Creating New Near-Surface Air Temperature Datasets to Understand Elevation-Dependent Warming in the Tibetan Plateau', REMOTE SENSING, vol. 12, no. 11.View/Download from: Publisher's site
Barraza, V, Alfredo Huete, Dara Entekhabi, Esteban Roitberg, Francisco Grings, María Gassmann, Mariano Franco, Natalia Restrepo-Coupe & Vanesa Douna 2019, 'Estimation of latent heat flux using satellite land surface temperature and a variational data assimilation scheme over a eucalypt forest savanna in Northern Australia', Agricultural and forest meteorology., vol. 268, pp. 341-353.View/Download from: Publisher's site
In this study, the performance of the combined-source variational data assimilation scheme (CS-VDA) is assessed in detail using in situ heat fluxes (i.e. sensible heat (H) and latent heat (LE)) collected at a Eucalypt forest savanna of Northern Australia (Howard Springs). The CS VDA scheme estimates surface turbulent heat fluxes via assimilation of sequences of land surface temperature (LST) and meteorological data into a surface energy balance model and a dynamic model. The main objectives of this paper were to extend previous studies to a semi-arid ecosystem and to evaluate the potential of using global meteorological forcing data (GMD) to drive the CS VDA model (rather than in-situ meteorological observations). In order to study the new errors associated with the use of GMD, the effects on LE of the uncertainty in air temperature and wind speed (the two key meteorological factors that controls the total estimation error) was quantitatively characterized. Using hourly in-situ measurements as inputs, the daily-averaged LE RMSEdaily was 54 W/m2, which agrees with the errors previously reported in the literature. As expected, replacing local meteorological data with GMD reduces the performance of the LE estimation (GMA: RMSEdaily = 82 W/m2, GLDAS: RMSEdaily = 151 W/m2). However, LE RMSE values at 8-day temporal scale for GMA are RMSE8-days = 32 W/m2, similar to those reported in this area for other models (MODIS (MOD16A2) and Breathing Earth System Simulator (BESS)). The error propagation analysis indicate that the CS VDA model is very sensitive to uncertainties in wind speed measurements. Moreover, there are large discrepancies between in situ and GMD wind speed. These two factors combined can explain the degradation in LE estimations. In this context, our study is a first step towards the characterization of an operational daily LE estimation scheme using hourly LST observations.
© 2019 by the authors. Remote sensing of phenology usually works at the regional and global scales, which imposes considerable variations in the solar zenith angle (SZA) across space and time. Variations in SZA alters the shape and profile of the surface reflectance and vegetation index (VI) time series, but this effect on remote-sensing-derived vegetation phenology has not been adequately evaluated. The objective of this study is to understand the behaviour of VIs response to SZA, and to further improve the interpretation of satellite observed vegetation dynamics, across space and time. In this study, the sensitivity of two widely used VIs-the normalised difference vegetation index (NDVI) and the enhanced vegetation index (EVI)-to SZA was investigated at four northern Australian savanna sites, over a latitudinal distance of 9.8° (~1100 km). Complete time series of surface reflectances, as acquired with different SZA configurations, were simulated using Bidirectional Reflectance Distribution Function (BRDF) parameters provided by MODerate Resolution Imaging Spectroradiometer (MODIS). The sun-angle dependency of the four phenological transition dates were assessed. Results showed that while NDVI was very sensitive to SZA, such sensitivity was nearly absent for EVI. A negative correlation was also observed between NDVI sensitivity to SZA and vegetation cover, with sensitivity declining to the same level as EVI when vegetation cover was high. Different sun-angle configurations resulted in considerable variations in the shape and magnitude of the phenological profiles. The sensitivity of VIs to SZA was generally greater during the dry season (with only active trees present) than in the wet season (with both active trees and grasses), thus, the sun-angle effect on VIs was phenophase-dependent. The sun-angle effect on NDVI time series resulted in considerable differences in the phenological metrics across different sun-angle configurations. Across four sites, the sun-a...
Medek, DE, Simunovic, M, Erbas, B, Katelaris, CH, Lampugnani, ER, Huete, A, Beggs, PJ & Davies, JM 2019, 'Enabling self-management of pollen allergies: a pre-season questionnaire evaluating the perceived benefit of providing local pollen information', Aerobiologia, vol. 35, no. 4, pp. 777-782.View/Download from: Publisher's site
© 2019, Springer Nature B.V. The Australian AusPollen Partnership provides respiratory allergy patients with accurate, relevant and localised pollen information via smartphone Apps. This study aims to evaluate public perceptions of need and benefit of providing local pollen information. Individuals aged 18 years and older were contacted through AusPollen Smartphone Apps (Brisbane, Sydney, Canberra and Melbourne), Australian Society for Clinical Immunology and Allergy, Asthma Australia and social media. A pilot questionnaire was developed in consultation with partner organisations, including select questions drawn from the National Young People and Asthma Survey. The questionnaire consisted of four sections: participant demographics, allergic rhinitis and asthma symptoms, symptom management and App utility. One hundred and twenty-seven people completed the survey, of whom 53% had access to local pollen information. Most (97%) participants without access to local pollen information indicated that they wanted such a service. Pollen information was most commonly perceived by participants to be useful for prevention and avoidance as well as preparation and planning. This preliminary study identified a public demand for local pollen information. Users identified practical ways in which pollen information assisted them. Publicised pollen concentrations and forecasts have the potential to improve awareness of allergy triggers and empower patient self-management, reducing symptoms and burden of disease.
Newlands, NK, Porcelli, TA, Potgieter, AB, Kouadio, L, Huete, A & Guo, W 2019, 'Editorial: Building and delivering real-world, integrated sustainability solutions: Insights, methods and case-study applications', Frontiers in Environmental Science, vol. 7, no. May.View/Download from: Publisher's site
Songsom, V, Koedsin, W, Ritchie, RJ & Huete, A 2019, 'Mangrove phenology and environmental drivers derived from remote sensing in Southern Thailand', Remote Sensing, vol. 11, no. 8.View/Download from: Publisher's site
© 2019 by the authors. Vegetation phenology is the annual cycle timing of vegetation growth. Mangrove phenology is a vital component to assess mangrove viability and includes start of season (SOS), end of season (EOS), peak of season (POS), and length of season (LOS). Potential environmental drivers include air temperature (Ta), surface temperature (Ts), sea surface temperature (SST), rainfall, sea surface salinity (SSS), and radiation flux (Ra). The Enhanced vegetation index (EVI) was calculated from Moderate Resolution Imaging Spectroradiometer (MODIS, MOD13Q1) data over five study sites between 2003 and 2012. Four of the mangrove study sites were located on the Malay Peninsula on the Andaman Sea and one site located on the Gulf of Thailand. The goals of this study were to characterize phenology patterns across equatorial Thailand Indo-Malay mangrove forests, identify climatic and aquatic drivers of mangrove seasonality, and compare mangrove phenologies with surrounding upland tropical forests. Our results show the seasonality of mangrove growth was distinctly different from the surrounding land-based tropical forests. The mangrove growth season was approximately 8-9 months duration, starting in April to June, peaking in August to October and ending in January to February of the following year. The 10-year trend analysis revealed significant delaying trends in SOS, POS, and EOS for the Andaman Sea sites but only for EOS at the Gulf of Thailand site. The cumulative rainfall is likely to be the main factor driving later mangrove phenologies.
Wang, S, Ju, W, Peñuelas, J, Cescatti, A, Zhou, Y, Fu, Y, Huete, A, Liu, M & Zhang, Y 2019, 'Urban-rural gradients reveal joint control of elevated CO2 and temperature on extended photosynthetic seasons.', Nature Ecology and Evolution, vol. 3, no. 7, pp. 1076-1085.View/Download from: Publisher's site
Photosynthetic phenology has large effects on the land-atmosphere carbon exchange. Due to limited experimental assessments, a comprehensive understanding of the variations of photosynthetic phenology under future climate and its associated controlling factors is still missing, despite its high sensitivities to climate. Here, we develop an approach that uses cities as natural laboratories, since plants in urban areas are often exposed to higher temperatures and carbon dioxide (CO2) concentrations, which reflect expected future environmental conditions. Using more than 880 urban-rural gradients across the Northern Hemisphere (≥30° N), combined with concurrent satellite retrievals of Sun-induced chlorophyll fluorescence (SIF) and atmospheric CO2, we investigated the combined impacts of elevated CO2 and temperature on photosynthetic phenology at the large scale. The results showed that, under urban conditions of elevated CO2 and temperature, vegetation photosynthetic activity began earlier (-5.6 ± 0.7 d), peaked earlier (-4.9 ± 0.9 d) and ended later (4.6 ± 0.8 d) than in neighbouring rural areas, with a striking two- to fourfold higher climate sensitivity than greenness phenology. The earlier start and peak of season were sensitive to both the enhancements of CO2 and temperature, whereas the delayed end of season was mainly attributed to CO2 enrichments. We used these sensitivities to project phenology shifts under four Representative Concentration Pathway climate scenarios, predicting that vegetation will have prolonged photosynthetic seasons in the coming two decades. This observation-driven study indicates that realistic urban environments, together with SIF observations, provide a promising method for studying vegetation physiology under future climate change.
Watson, CJ, Restrepo-Coupe, N & Huete, AR 2019, 'Multi-scale phenology of temperate grasslands: Improving monitoring and management with near-surface phenocams', Frontiers in Environmental Science, vol. 7, no. FEB.View/Download from: Publisher's site
© 2019 Watson, Restrepo-Coupe and Huete. Grasslands of the Australian Southern Tablelands represent a patchwork of native and exotic systems, occupying a continuum of C 3 -dominated to C 4 -dominated grasslands where composition depends on disturbance factors (e.g., grazing) and climate. Managing these complex landscapes is both challenging and critical for maintaining the security of Australia's pasture industries, and for protecting the biodiversity of native remnants. Differentiating C 3 from C 4 vegetation has been a prominent theme in remote sensing research due to distinct C 3 /C 4 seasonal productivity patterns (phenology) and high uncertainty about how C 3 /C 4 vegetation will respond to a changing climate. Phenology is used in northern hemisphere ecosystems for a range of purposes but has not been widely adopted in Australia, where dynamic climate often results in non-repetitive seasonal vegetation patterns. We employed time-lapse cameras (phenocams) to study the phenology of twelve grassland areas dominated by cool season (C 3 ) and warm season (C 4 ), native or exotic grasses near Canberra, Australia. Our aims were to assess phenological characteristics of the functional types and to determine the drivers of phenological variability. We compared the fine-scale phenocam seasonal profiles with field sampling and MODIS/Landsat satellite products to assess paddock-to-landscape functioning. We found C 3 /C 4 species dominance to be the primary driver of phenological differences among grassland types, with C 3 grasslands demonstrating peak greenness in spring, and senescing rapidly in response to high summer temperatures. In contrast, C 4 grasslands showed peak activity in Austral summer and autumn (January-March). Some sites displayed primary and secondary peaks dependent on rainfall and species composition. We found that the proportion of dead vegetation is an important biophysical driver of grassland phenology, as were grazing pressures and species-depen...
Xiao, J, Chevallier, F, Gomez, C, Guanter, L, Hicke, JA, Huete, AR, Ichii, K, Ni, W, Pang, Y, Rahman, AF, Sun, G, Yuan, W, Zhang, L & Zhang, X 2019, 'Remote sensing of the terrestrial carbon cycle: A review of advances over 50 years', Remote Sensing of Environment, vol. 233.View/Download from: Publisher's site
© 2019 Elsevier Inc. Quantifying ecosystem carbon fluxes and stocks is essential for better understanding the global carbon cycle and improving projections of the carbon-climate feedbacks. Remote sensing has played a vital role in this endeavor during the last five decades by quantifying carbon fluxes and stocks. The availability of satellite observations of the land surface since the 1970s, particularly the early 1980s, has made it feasible to quantify ecosystem carbon fluxes and stocks at regional to global scales. Here we provide a review of the advances in remote sensing of the terrestrial carbon cycle from the early 1970s to present. First, we present an overview of the terrestrial carbon cycle and remote sensing of carbon fluxes and stocks. Remote sensing data acquired in a broad wavelength range (visible, infrared, and microwave) of the electromagnetic spectrum have been used to estimate carbon fluxes and/or stocks. Second, we provide a historical overview of the key milestones in remote sensing of the terrestrial carbon cycle. Third, we review the platforms/sensors, methods, findings, and challenges in remote sensing of carbon fluxes. The remote sensing data and techniques used to quantify carbon fluxes include vegetation indices, light use efficiency models, terrestrial biosphere models, data-driven (or machine learning) approaches, solar-induced chlorophyll fluorescence (SIF), land surface temperature, and atmospheric inversions. Fourth, we review the platforms/sensors, methods, findings, and challenges in passive optical, microwave, and lidar remote sensing of biomass carbon stocks as well as remote sensing of soil organic carbon. Fifth, we review the progresses in remote sensing of disturbance impacts on the carbon cycle. Sixth, we also discuss the uncertainty and validation of the resulting carbon flux and stock estimates. Finally, we offer a forward-looking perspective and insights for future research and directions in remote sensing of the terrestr...
Yan, H, Wang, SQ, Huete, A & Shugart, HH 2019, 'Effects of Light Component and Water Stress on Photosynthesis of Amazon Rainforests During the 2015/2016 El Niño Drought', Journal of Geophysical Research: Biogeosciences, vol. 124, no. 6, pp. 1574-1590.View/Download from: Publisher's site
©2019. American Geophysical Union. All Rights Reserved. Whether enhanced sunshine increases photosynthesis in Amazon rainforests during drought is unclear. Here we used a light component-based two-leaf-photosynthesis model, driven with climate data and satellite vegetation data, to inspect the controlling mechanisms among climate factors on gross primary production (GPP) during the 2015/2016 El Niño drought event. We found that simulated GPP and Moderate Resolution Imaging Spectroradiometer enhanced vegetation index indicated an Amazonian "browning" and not a "green up" during the 2015/2016 El Niño year relative to the 2011–2014 interval. The result shows that, along with intensified sunlight, diffuse sunlight and diffuse fraction as well as canopy light use efficiency decreased, which further produced a decreased potential GPP* (determined by light components and leaf area index of shaded and sunlit leaves). The decreased GPP* and drought-induced water stress jointly reduced canopy photosynthesis of Amazon rainforests during the 2015/2016 drought. The light component variations caused a reduction in GPP but with a magnitude inferior to the GPP reduction from water stress. These findings suggest that intensified sunlight did not enhance photosynthesis of Amazon rainforests and highlight the important role of light components in interannual and seasonal variations of photosynthesis in Amazon rainforests.
Xie, Z, Huete, A, Cleverly, J, Phinn, S, McDonald-Madden, E, Cao, Y & Qin, F 2019, 'Multi-climate mode interactions drive hydrological and vegetation responses to hydroclimatic extremes in Australia', Remote Sensing of Environment, vol. 231.View/Download from: Publisher's site
© 2019 Australia has experienced a large frequency of hydroclimatic events since the early 21st century, with multiple large-scale droughts and flooding rains exerting dramatic impacts on water resources and ecosystems. Despite these pronounced consequences, the coupling of ecosystem functioning to extreme climate variability remains elusive due to the lack of complete understanding of hydrological connections. In this study, we investigated the spatiotemporal trends of Australia's hydrological and vegetation responses to three climate modes: El Niño-Southern Oscillation, the Indian Ocean dipole and the Southern Annular Mode, utilizing climate indices, satellite-derived total water storage anomaly (TWSA) from GRACE, precipitation from TRMM and vegetation greenness from MODIS. Using partial cross-correlation and vegetation sensitivity analyses to interpret the interactions among climate modes, water resources and vegetation across Australia, three hydroclimatic extreme events from 2002 to 2017 were analyzed: (i) a prolonged drought (2002–09, colloquially known as the 'big dry'); (ii) a dramatic wet pulse (2010–11, the 'big wet'); and (iii) another anomalous El Niño event (2015). Our results showed the entire continent partitioned into three geographic zones with diverse drying and wetting trends in total water storage, precipitation and vegetation greenness, reflecting varying and fundamental influences from the individual climate modes. Ecosystem productivity was found to be better related and more sensitive to TWSA than precipitation across different hydroclimate zones and during both extreme dry and wet conditions. We also observed TWSA increased rapidly during wet extremes, and these gains in water resources persisted for an additional four years (i.e., TWSA remained positive until 2015 following the 2011 'big wet'). Lastly, findings from another hydroclimatic event (the 2015 El Niño drought) further confirmed the relationships among climate, water and ecosyst...
Camp, EF, Edmondson, J, Doheny, A, Rumney, J, Grima, AJ, Huete, A & Suggett, DJ 2019, 'Mangrove lagoons of the Great Barrier Reef support coral populations persisting under extreme environmental conditions', Marine Ecology Progress Series, vol. 625, pp. 1-14.View/Download from: Publisher's site
© The authors 2019. Global degradation of coral reefs has increased the urgency of identifying stress-tolerant coral populations, to enhance understanding of the biology driving stress tolerance, as well as identifying stocks of stress-hardened populations to aid reef rehabilitation. Surprisingly, scientists are continually discovering that naturally extreme environments house established coral populations adapted to grow within extreme abiotic conditions comparable to seawater conditions predicted over the coming century. Such environments include inshore mangrove lagoons that carry previously unrecognised ecosystem service value for corals, spanning from refuge to stress preconditioning. However, the existence of such hot-spots of resilience on the Great Barrier Reef (GBR) remains entirely unknown. Here we describe, for the first time, 2 extreme GBR mangrove lagoons (Woody Isles and Howick Island), exposing taxonomically diverse coral communities (34 species, 7 growth morphologies) to regular extreme low pH (<7.6), low oxygen (<1 mg l−1) and highly variable temperature range (>7°C) conditions. Coral cover was typically low (<5%), but highly patchy and included established colonies (>0.5 m diameter), with net photosynthesis and calcification rates of 2 dominant coral species (Acropora millepora, Porites lutea) reduced (20−30%), and respiration enhanced (11−35%), in the mangrove lagoon relative to adjacent reefs. Further analysis revealed that physiological plasticity (photosynthetic 'strategy') and flexibility of Symbiodiniaceae taxa associations appear crucial in supporting coral capacity to thrive from reef to lagoon. Prevalence of corals within these extreme conditions on the GBR (and elsewhere) increasingly challenge our understanding of coral resilience to stressors, and highlight the need to study unfavourable coral environments to better resolve mechanisms of stress tolerance.
Peng, D, Zhang, H, Liu, L, Huang, W, Huete, AR, Zhang, X, Wang, F, Yu, L, Xie, Q, Wang, C, Luo, S, Li, C & Zhang, B 2019, 'Estimating the aboveground biomass for planted forests based on stand age and environmental variables', Remote Sensing, vol. 11, no. 19.View/Download from: Publisher's site
© 2019 by the authors. Measuring forest aboveground biomass (AGB) at local to regional scales is critical to understanding their role in regional and global carbon cycles. The Three-North Shelterbelt Forest Program (TNSFP) is the largest ecological restoration project in the world, and has been ongoing for over 40 years. In this study, we developed models to estimate the planted forest aboveground biomass (PF_AGB) for Yulin, a typical area in the project. Surface reflectances in the study area from 1978 to 2013 were obtained from Landsat series images, and integrated forest z-scores were constructed to measure afforestation and the stand age of planted forest. Normalized difference vegetation index (NDVI) was combined with stand age to develop an initial model to estimate PF_AGB. We then developed additional models that added environment variables to our initial model, including climatic factors (average temperature, total precipitation, and total sunshine duration) and a topography factor (slope). The model which combined the total precipitation and slope greatly improved the accuracy of PF_AGB estimation compared to the initial model, indicating that the environmental variables related to water distribution indirectly affected the growth of the planted forest and the resulting AGB. Afforestation in the study area occurred mainly in the early 1980s and early 21st century, and the PF_AGB in 2003 was 2.3 times than that of 1998, since the fourth term TNSFP started in 2000. The PF_AGB in 2013 was about 3.33 times of that in 2003 because many young trees matured. The leave-one-out cross-validation (LOOCV) approach showed that our estimated PF_AGB had a significant correlation with field-measured data (correlation coefficient (r) = 0.89, p < 0.001, root mean square error (RMSE) = 6.79 t/ha). Our studies provided a method to estimate long time series PF_AGB using satellite repetitive measures, particularly for arid or semi-arid areas.
Xie, M, Wang, Z, Huete, A, Brown, LA, Wang, H, Xie, Q, Xu, X & Ding, Y 2019, 'Estimating peanut leaf chlorophyll content with dorsiventral leaf adjusted indices: Minimizing the impact of spectral differences between adaxial and abaxial leaf surfaces', Remote Sensing, vol. 11, no. 18.View/Download from: Publisher's site
© 2019 by the authors. Relatively little research has assessed the impact of spectral differences among dorsiventral leaves caused by leaf structure on leaf chlorophyll content (LCC) retrieval. Based on reflectance measured from peanut adaxial and abaxial leaves and LCC measurements, this study proposed a dorsiventral leaf adjusted ratio index (DLARI) to adjust dorsiventral leaf structure and improve LCC retrieval accuracy. Moreover, the modified Datt (MDATT) index, which was insensitive to leaves structure, was optimized for peanut plants. All possible wavelength combinations for the DLARI and MDATT formulae were evaluated. When reflectance from both sides were considered, the optimal combination for the MDATT formula was (R723 - R738)/(R723 - R722) with a cross-validation Rcv2 of 0.91 and RMSEcv of 3.53 μg/cm2. The DLARI formula provided the best performing indices, which were (R735 - R753)/(R715 - R819) for estimating LCC from the adaxial surface (Rcv2 = 0.96, RMSEcv = 2.37 μg/cm2) and (R732 - R754)/(R724 - R773) for estimating LCC from reflectance of both sides (Rcv2 = 0.94, RMSEcv = 2.81 μg/cm2). A comparison with published vegetation indices demonstrated that the published indices yielded reliable estimates of LCC from the adaxial surface but performed worse than DLARIs when both leaf sides were considered. This paper concludes that the DLARI is the most promising approach to estimate peanut LCC.
Xie, Q, Dash, J, Huete, A, Jiang, A, Yin, G, Ding, Y, Peng, D, Hall, CC, Brown, L, Shi, Y, Ye, H, Dong, Y & Huang, W 2019, 'Retrieval of crop biophysical parameters from Sentinel-2 remote sensing imagery', International Journal of Applied Earth Observation and Geoinformation, vol. 80, pp. 187-195.View/Download from: Publisher's site
Barraza Bernadas, V, Grings, F, Restrepo-Coupe, N & Huete, A 2018, 'Comparison of the performance of latent heat flux products over southern hemisphere forest ecosystems: estimating latent heat flux error structure using in situ measurements and the triple collocation method', International Journal of Remote Sensing, vol. 39, no. 19, pp. 6300-6315.View/Download from: Publisher's site
© 2018 Informa UK Limited, trading as Taylor & Francis Group In this study, we compared different remote-sensing (RS)-based land surface models (LSM) and reanalysis latent heat flux (LE) products over different forest ecosystems. We analysed the performance of three RS products, the MOD16A2, the Breathing Earth System Simulator (BESS) model, and a combined optical-microwave model (COM) in their ability to replicate eddy covariance (EC) flux observations of LE at eight southern hemisphere forest ecosystems and compared their results to simulated LE from the offline LSM (GLDAS/NOAH) and a reanalysis LE dataset (MERRA). To determine spatial uncertainties, we used the triple collocation (TC) method, which does not require a priori knowledge of the true LE value, at selected Australian EC locations and over an area without in situ measurement (the Dry Chaco Forest (DCF), Argentina). The spatial pattern of the TC results was commensurable with uncertainties calculated using EC observations, indicating that the TC method is a robust technique to estimate spatial uncertainties. As global products have been validated with EC measurement from Ozflux stations, we hypothesized and found, using the TC model, that LE products achieve a better performance over areas with EC from networks than over sites without ground-based measurements and may reflect over-calibration of models or a need for a more diverse representation of ecosystems at flux tower networks.
Devadas, R, Huete, AR, Vicendese, D, Erbas, B, Beggs, PJ, Medek, D, Haberle, SG, Newnham, RM, Johnston, FH, Jaggard, AK, Campbell, B, Burton, PK, Katelaris, CH, Newbigin, E, Thibaudon, M & Davies, JM 2018, 'Dynamic ecological observations from satellites inform aerobiology of allergenic grass pollen.', The Science of the total environment, vol. 633, pp. 441-451.View/Download from: Publisher's site
Allergic diseases, including respiratory conditions of allergic rhinitis (hay fever) and asthma, affect up to 500 million people worldwide. Grass pollen are one major source of aeroallergens globally. Pollen forecast methods are generally site-based and rely on empirical meteorological relationships and/or the use of labour-intensive pollen collection traps that are restricted to sparse sampling locations. The spatial and temporal dynamics of the grass pollen sources themselves, however, have received less attention. Here we utilised a consistent set of MODIS satellite measures of grass cover and seasonal greenness (EVI) over five contrasting urban environments, located in Northern (France) and Southern Hemispheres (Australia), to evaluate their utility for predicting airborne grass pollen concentrations. Strongly seasonal and pronounced pollinating periods, synchronous with satellite measures of grass cover greenness, were found at the higher latitude temperate sites in France (46-50° N. Lat.), with peak pollen activity lagging peak greenness, on average by 2-3weeks. In contrast, the Australian sites (34-38° S. Lat.) displayed pollinating periods that were less synchronous with satellite greenness measures as peak pollen concentrations lagged peak greenness by as much as 4 to 7weeks. The Australian sites exhibited much higher spatial and inter-annual variations compared to the French sites and at the Sydney site, broader and multiple peaks in both pollen concentrations and greenness data coincided with flowering of more diverse grasses including subtropical species. Utilising generalised additive models (GAMs) we found the satellite greenness data of grass cover areas explained 80-90% of airborne grass pollen concentrations across the three French sites (p<0.001) and accounted for 34 to 76% of grass pollen variations over the two sites in Australia (p<0.05). Our results demonstrate the potential of satellite sensing to augment forecast models of grass pollen aer...
Kanniah, KD, Tan, KP, Cracknell, AP, Huete, AR, Idris, NH, Lau, AMS, Abd Rahman, MZ, Rasib, AW & Ahmad, A 2018, 'Assessment of biophysical properties of Royal Belum tropical forest, Malaysia', Singapore Journal of Tropical Geography, vol. 39, no. 1, pp. 90-106.View/Download from: Publisher's site
© 2017 Department of Geography, National University of Singapore and John Wiley & Sons Australia, Ltd The Royal Belum forest reserve is one of the oldest tropical rainforests in the world and it is one of the largest vir gin forest reserves in Malaysia. However, not many studies have been conducted to understand the ecology of this forest. In this study we estimated the aboveground biomass (AGB) of the forest using diameter at breast height (DBH) and height of trees (h), tree species and hemispherical photographs of tree canopy. We estimated AGB using five allometric equations. Our results demonstrated that the AGB given by the one tree species specific allometric equation does not show any significant differences from the values given by the non-tree species specific allometric equations at tree and plot levels. The AGB of Intsia bijuga species, Koompassia malaccensis species and Shorea genera were comparatively higher, owing to their greater wood density, DBH and h. This has added importance because some of these species are categorized as threatened species. Our results demonstrated that mean AGB values in this forest (293.16 t ha -1 ) are the highest compared to some studies of other areas in Malaysia, tropical Africa and tropical Bazilian Amazonia, implying that the Royal Belum forest reserve, is an important carbon reservoir.
Lin, S, Li, J, Liu, Q, Huete, A & Li, L 2018, 'Effects of Forest Canopy Vertical Stratification on the Estimation of Gross Primary Production by Remote Sensing', REMOTE SENSING, vol. 10, no. 9.View/Download from: Publisher's site
Liu, YY, van Dijk, AIJM, Miralles, DG, McCabe, MF, Evans, JP, de Jeu, RAM, Gentine, P, Huete, A, Parinussa, RM, Wang, L, Guan, K, Berry, J & Restrepo-Coupe, N 2018, 'Enhanced canopy growth precedes senescence in 2005 and 2010 Amazonian droughts', Remote Sensing of Environment, vol. 211, pp. 26-37.View/Download from: Publisher's site
© 2018 Unprecedented droughts hit southern Amazonia in 2005 and 2010, causing a sharp increase in tree mortality and carbon loss. To better predict the rainforest's response to future droughts, it is necessary to understand its behavior during past events. Satellite observations provide a practical source of continuous observations of Amazonian forest. Here we used a passive microwave-based vegetation water content record (i.e., vegetation optical depth, VOD), together with multiple hydrometeorological observations as well as conventional satellite vegetation measures, to investigate the rainforest canopy dynamics during the 2005 and 2010 droughts. During the onset of droughts in the wet-to-dry season (May–July) of both years, we found large-scale positive anomalies in VOD, leaf area index (LAI) and enhanced vegetation index (EVI) over the southern Amazonia. These observations are very likely caused by enhanced canopy growth. Concurrent below-average rainfall and above-average radiation during the wet-to-dry season can be interpreted as an early arrival of normal dry season conditions, leading to enhanced new leaf development and ecosystem photosynthesis, as supported by field observations. Our results suggest that further rainfall deficit into the subsequent dry season caused water and heat stress during the peak of 2005 and 2010 droughts (August–October) that exceeded the tolerance limits of the rainforest, leading to widespread negative VOD anomalies over the southern Amazonia. Significant VOD anomalies were observed mainly over the western part in 2005 and mainly over central and eastern parts in 2010. The total area with significant negative VOD anomalies was comparable between these two drought years, though the average magnitude of significant negative VOD anomalies was greater in 2005. This finding broadly agrees with the field observations indicating that the reduction in biomass carbon uptake was stronger in 2005 than 2010. The enhanced canopy growth pr...
Maes, WH, Huete, AR, Avino, M, Boer, MM, Dehaan, R, Pendall, E, Griebel, A & Steppe, K 2018, 'Can UAV-Based Infrared Thermography Be Used to Study Plant-Parasite Interactions between Mistletoe and Eucalypt Trees?', REMOTE SENSING, vol. 10, no. 12.View/Download from: Publisher's site
Nguyen, HT, Ma, X, Newbigin, E, Beggs, P, Davies, J & Huete, A 2018, 'Grassland Phenology and Meteorology Co-Influence Grass Pollen Counts in Victoria, Australia', ISEE Conference Abstracts, vol. 2018, no. 1.View/Download from: Publisher's site
Patel, NR, Padalia, H, Devadas, R, Huete, A, Senthil Kumar, A & Krishna Murthy, YVN 2018, 'Estimating net primary productivity of croplands in Indo-Gangetic Plains using GOME-2 sun-induced fluorescence and MODIS NDVI', Current Science, vol. 114, no. 6, pp. 1333-1337.View/Download from: Publisher's site
© 2018 Current Science Association, Bengaluru. Recently evolved satellite-based sun-induced fluorescence (SIF) spectroscopy is considered as a direct measure of photosynthetic activity of vegetation. We have used monthly averages of satellite-based SIF retrievals for three agricultural year cycles, i.e. May to April for each of the three years, viz. 2007-08, 2008-09 and 2009-10 to assess comparative performance of SIF and normalized difference vegetation index (NDVI) for predicting net primary productivity (NPP) over the Indo-Gangetic Plains, India. Results show that SIF values for C4 crop-dominated districts were higher than C3 crop-dominated districts during summer and low during winter for all three years. SIF explained more or less above 70% of variance in NPP. The variance explained by integrated NDVI ranged from 60% to 67%. Thus the present study has shown the potential of SIF data for improved modelling of agricultural productivity at a regional scale.
Peng, D, Wu, C, Zhang, X, Yu, L, Huete, AR, Wang, F, Luo, S, Liu, X & Zhang, H 2018, 'Scaling up spring phenology derived from remote sensing images', AGRICULTURAL AND FOREST METEOROLOGY, vol. 256, pp. 207-219.View/Download from: Publisher's site
Shen, J, Huete, A, Tran, NN, Devadas, R, Ma, X, Eamus, D & Yu, Q 2018, 'Diverse sensitivity of winter crops over the growing season to climate and land surface temperature across the rainfed cropland-belt of eastern Australia', Agriculture, Ecosystems and Environment, vol. 254, pp. 99-110.View/Download from: Publisher's site
© 2017 Elsevier B.V. The rainfed cropland belt in Australia is of great importance to the world grain market but has the highest climate variability of all such regions globally. However, the spatial-temporal impacts of climate variability on crops during different crop growth stages across broadacre farming systems are largely unknown. This study aims to quantify the contributions of climate and Land Surface Temperature (LST) variations to the variability of the Enhanced Vegetation Index (EVI) by using remote sensing methods. The datasets were analyzed at an 8-day time-scale across the rainfed cropland of eastern Australia. First, we found that EVI values were more variable during the crop reproductive growth stages than at any other crop life stage within a calendar year, but nevertheless had the highest correlation with crop grain yield (t ha−1). Second, climate factors and LST during the crop reproductive growth stages showed the largest variability and followed a typical east-west gradient of rainfall and a north-south temperature gradient across the study area during the crop growing season. Last, we identified two critical 8-day periods, beginning on day of the year (DoY) 257 and 289, as the key 'windows' of crop growth variation that arose from the variability in climate and LST. Our results show that the sum of the variability of the climate components within these two 8-day 'windows' explained >88% of the variability in the EVI, with LST being the dominant factor. This study offers a fresh understanding of the spatial-temporal climate-crop relationships in rainfed cropland and can serve as an early warning system for agricultural adaptation in broadacre rainfed cropping practices in Australia and worldwide.
Song, L, Guanter, L, Guan, K, You, L, Huete, A, Ju, W & Zhang, Y 2018, 'Satellite sun-induced chlorophyll fluorescence detects early response of winter wheat to heat stress in the Indian Indo-Gangetic Plains.', Global change biology, vol. 24, no. 9.View/Download from: Publisher's site
Extremely high temperatures represent one of the most severe abiotic stresses limiting crop productivity. However, understanding crop responses to heat stress is still limited considering the increases in both the frequency and severity of heat wave events under climate change. This limited understanding is partly due to the lack of studies or tools for the timely and accurate monitoring of crop responses to extreme heat over broad spatial scales. In this work, we use novel spaceborne data of sun-induced chlorophyll fluorescence (SIF), which is a new proxy for photosynthetic activity, along with traditional vegetation indices (Normalized Difference Vegetation Index NDVI and Enhanced Vegetation Index EVI) to investigate the impacts of heat stress on winter wheat in northwestern India, one of the world's major wheat production areas. In 2010, an abrupt rise in temperature that began in March adversely affected the productivity of wheat and caused yield losses of 6% compared to previous year. The yield predicted by satellite observations of SIF decreased by approximately 13.9%, compared to the 1.2% and 0.4% changes in NDVI and EVI, respectively. During early stage of this heat wave event in early March 2010, the SIF observations showed a significant reduction and earlier response, while NDVI and EVI showed no changes and could not capture the heat stress until late March. The spatial patterns of SIF anomalies closely tracked the temporal evolution of the heat stress over the study area. Furthermore, our results show that SIF can provide large-scale, physiology-related wheat stress response as indicated by the larger reduction in fluorescence yield (SIFyield ) than fraction of photosynthetically active radiation during the grain-filling phase, which may have eventually led to the reduction in wheat yield in 2010. This study implies that satellite observations of SIF have great potential to detect heat stress conditions in wheat in a timely manner and assess their imp...
Teluguntla, P, Thenkabail, PS, Oliphant, A, Xiong, J, Gumma, MK, Congalton, RG, Yadav, K & Huete, A 2018, 'A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform', ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, vol. 144, pp. 325-340.View/Download from: Publisher's site
Thien, F, Beggs, PJ, Csutoros, D, Darvall, J, Hew, M, Davies, JM, Bardin, PG, Bannister, T, Barnes, S, Bellomo, R, Byrne, T, Casamento, A, Conron, M, Cross, A, Crosswell, A, Douglass, JA, Durie, M, Dyett, J, Ebert, E, Erbas, B, French, C, Gelbart, B, Gillman, A, Harun, NS, Huete, A, Irving, L, Karalapillai, D, Ku, D, Lachapelle, P, Langton, D, Lee, J, Looker, C, MacIsaac, C, McCaffrey, J, McDonald, CF, McGain, F, Newbigin, E, O'Hehir, R, Pilcher, D, Prasad, S, Rangamuwa, K, Ruane, L, Sarode, V, Silver, JD, Southcott, AM, Subramaniam, A, Suphioglu, C, Susanto, NH, Sutherland, MF, Taori, G, Taylor, P, Torre, P, Vetro, J, Wigmore, G, Young, AC & Guest, C 2018, 'The Melbourne epidemic thunderstorm asthma event 2016: an investigation of environmental triggers, effect on health services, and patient risk factors', The Lancet Planetary Health, vol. 2, no. 6, pp. e255-e263.View/Download from: Publisher's site
© 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY NC ND 4.0 license Background: A multidisciplinary collaboration investigated the world's largest, most catastrophic epidemic thunderstorm asthma event that took place in Melbourne, Australia, on Nov 21, 2016, to inform mechanisms and preventive strategies. Methods: Meteorological and airborne pollen data, satellite-derived vegetation index, ambulance callouts, emergency department presentations, and data on hospital admissions for Nov 21, 2016, as well as leading up to and following the event were collected between Nov 21, 2016, and March 31, 2017, and analysed. We contacted patients who presented during the epidemic thunderstorm asthma event at eight metropolitan health services (each including up to three hospitals) via telephone questionnaire to determine patient characteristics, and investigated outcomes of intensive care unit (ICU) admissions. Findings: Grass pollen concentrations on Nov 21, 2016, were extremely high (>100 grains/m 3 ). At 1800 AEDT, a gust front crossed Melbourne, plunging temperatures 10°C, raising humidity above 70%, and concentrating particulate matter. Within 30 h, there were 3365 (672%) excess respiratory-related presentations to emergency departments, and 476 (992%) excess asthma-related admissions to hospital, especially individuals of Indian or Sri Lankan birth (10% vs 1%, p<0·0001) and south-east Asian birth (8% vs 1%, p<0·0001) compared with previous 3 years. Questionnaire data from 1435 (64%) of 2248 emergency department presentations showed a mean age of 32·0 years (SD 18·6), 56% of whom were male. Only 28% had current doctor-diagnosed asthma. 39% of the presentations were of Asian or Indian ethnicity (25% of the Melbourne population were of this ethnicity according to the 2016 census, relative risk [RR] 1·93, 95% CI 1·74–2·15, p <0·0001). Of ten individuals who died, six were Asian or Indian (RR 4·54, 95% CI 1·28–16·09; p=0·01). 35 ...
Wu, J, Kobayashi, H, Stark, SC, Meng, R, Guan, K, Tran, NN, Gao, S, Yang, W, Restrepo-Coupe, N, Miura, T, Oliviera, RC, Rogers, A, Dye, DG, Nelson, BW, Serbin, SP, Huete, AR & Saleska, SR 2018, 'Biological processes dominate seasonality of remotely sensed canopy greenness in an Amazon evergreen forest.', New Phytologist, vol. 217, no. 4, pp. 1507-1520.View/Download from: Publisher's site
Satellite observations of Amazon forests show seasonal and interannual variations, but the underlying biological processes remain debated. Here we combined radiative transfer models (RTMs) with field observations of Amazon forest leaf and canopy characteristics to test three hypotheses for satellite-observed canopy reflectance seasonality: seasonal changes in leaf area index, in canopy-surface leafless crown fraction and/or in leaf demography. Canopy RTMs (PROSAIL and FLiES), driven by these three factors combined, simulated satellite-observed seasonal patterns well, explaining c. 70% of the variability in a key reflectance-based vegetation index (MAIAC EVI, which removes artifacts that would otherwise arise from clouds/aerosols and sun-sensor geometry). Leaf area index, leafless crown fraction and leaf demography independently accounted for 1, 33 and 66% of FLiES-simulated EVI seasonality, respectively. These factors also strongly influenced modeled near-infrared (NIR) reflectance, explaining why both modeled and observed EVI, which is especially sensitive to NIR, captures canopy seasonal dynamics well. Our improved analysis of canopy-scale biophysics rules out satellite artifacts as significant causes of satellite-observed seasonal patterns at this site, implying that aggregated phenology explains the larger scale remotely observed patterns. This work significantly reconciles current controversies about satellite-detected Amazon phenology, and improves our use of satellite observations to study climate-phenology relationships in the tropics.
Zhang, X, Wang, N, Xie, Z, Ma, X & Huete, A 2018, 'Water loss due to increasing planted vegetation over the Badain Jaran Desert, China', Remote Sensing, vol. 10, no. 1.View/Download from: Publisher's site
© 2018 by the authors. Water resources play a vital role in ecosystem stability, human survival, and social development in drylands. Human activities, such as afforestation and irrigation, have had a large impact on the water cycle and vegetation in drylands over recent years. The Badain Jaran Desert (BJD) is one of the driest regions in China with increasing human activities, yet the connection between human management and the ecohydrology of this area remains largely unclear. In this study, we firstly investigated the ecohydrological dynamics and their relationship across different spatial scales over the BJD, using multi-source observational data from 2001 to 2014, including: total water storage anomaly (TWSA) from Gravity Recovery and Climate Experiment (GRACE), normalized difference vegetation index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS), lake extent from Landsat, and precipitation from in situ meteorological stations. We further studied the response of the local hydrological conditions to large scale vegetation and climatic dynamics, also conducting a change analysis of water levels over four selected lakes within the BJD region from 2011. To normalize the effect of inter-annual variations of precipitation on vegetation, we also employed a relationship between annual average NDVI and annual precipitation, or modified rain-use efficiency, termed the RUEmo. A focus of this study is to understand the impact of the increasing planted vegetation on local ecohydrological systems over the BJD region. Results showed that vegetation increases were largely found to be confined to the areas intensely influenced by human activities, such as croplands and urban areas. With precipitation patterns remaining stable during the study period, there was a significant increasing trend in vegetation greenness per unit of rainfall, or RUEmo over the BJD, while at the same time, total water storage as measured by satellites has been continually decreasin...
Li, L, Wang, YP, Eamus, D, Yu, Q, Huete, A, Cleverly, J, Shi, H, Cheng, L & Zhang, L 2018, 'Evaluating global land surface models in CMIP5: analysis of ecosystem water- and light-use efficiences, and rainfall partitioning', Journal of Climate, vol. 31, no. 8, pp. 2995-3008.View/Download from: Publisher's site
Li, Y, Shi, H, Zhou, L, Eamus, D, Huete, A, Li, L, Cleverly, J, Hu, Z, Harahap, M, Yu, Q, He, L & Wang, S 2018, 'Disentangling Climate and LAI Effects on Seasonal Variability in Water Use Efficiency Across Terrestrial Ecosystems in China', Journal of Geophysical Research: Biogeosciences, vol. 123, no. 8, pp. 2429-2443.View/Download from: Publisher's site
©2018. American Geophysical Union. All Rights Reserved. Water use efficiency (WUE), the ratio of gross primary productivity (GPP) over evapotranspiration (ET), is a critical ecosystem function. However, it is difficult to distinguish the individual effects of climatic variables and leaf area index (LAI) on WUE, mainly due to the high collinearity among these factors. Here we proposed a partial least squares regression-based sensitivity algorithm to confront the issue, which was first verified at seven ChinaFlux sites and then applied across China. The results showed that across all biomes in China, monthly GPP (0.42–0.65), ET (0.33–0.56), and WUE (0.01–0.31) showed positive sensitivities to air temperature, particularly in croplands in northeast China and forests in southwest China. Radiation exerted stronger effects on ET (0.55–0.78) than GPP (0.19–0.65), resulting in negative responses (−0.44 to 0.04) of WUE to increased radiation among most biomes. Increasing precipitation stimulated both GPP (0.06–0.17) and ET (0.05–0.12) at the biome level, but spatially negative effects of excessive precipitation were also found in some grasslands. Both monthly GPP (−0.01 to 0.29) and ET (0.02–0.12) showed weak or moderate responses to vapor pressure deficit among biomes, resulting in weak response of monthly WUE to vapor pressure deficit (−0.04 to 0.08). LAI showed positive effects on GPP (0.18–0.60), ET (0–0.23), and WUE (0.13–0.42) across biomes, particularly on WUE in grasslands (0.42 ± 0.30). Our results highlighted the importance of LAI in influencing WUE against climatic variables. Furthermore, the sensitivity algorithm can be used to inform the design of manipulative experiments and compare with factorial simulations for discerning effects of various variables on ecosystem functions.
Maeda, EE, Ma, X, Wagner, FH, Kim, H, Oki, T, Eamus, D & Huete, A 2017, 'Evapotranspiration seasonality across the Amazon Basin', Earth System Dynamics, vol. 8, no. 2, pp. 439-454.View/Download from: Publisher's site
© 2017 by the authors. The current standard procedure for aligning thermal imagery with structure-from-motion (SfM) software uses GPS logger data for the initial image location. As input data, all thermal images of the flight are rescaled to cover the same dynamic scale range, but they are not corrected for changes in meteorological conditions during the flight. This standard procedure can give poor results, particularly in datasets with very low contrast between and within images or when mapping very complex 3D structures. To overcome this, three alignment procedures were introduced and tested: camera pre-calibration, correction of thermal imagery for small changes in air temperature, and improved estimation of the initial image position by making use of the alignment of RGB (visual) images. These improvements were tested and evaluated in an agricultural (low temperature contrast data) and an afforestation (complex 3D structure) dataset. In both datasets, the standard alignment procedure failed to align the images properly, either by resulting in point clouds with several gaps (images that were not aligned) or with unrealistic 3D structure. Using initial thermal camera positions derived from RGB image alignment significantly improved thermal image alignment in all datasets. Air temperature correction had a small yet positive impact on image alignment in the low-contrast agricultural dataset, but a minor effect in the afforestation area. The effect of camera calibration on the alignment was limited in both datasets. Still, in both datasets, the combination of all three procedures significantly improved the alignment, in terms of number of aligned images and of alignment quality.
Pandey, AK, Mishra, AK, Kumar, R, Berwal, S, Devadas, R, Huete, A & Kumar, K 2017, 'CO variability and its association with household cooking fuels consumption over the Indo-Gangetic Plains.', Environmental Pollution, vol. 222, pp. 83-93.View/Download from: Publisher's site
This study examines the spatio-temporal trends obtained from decade long (Jan 2003-Dec 2014) satellite observational data of Atmospheric Infrared Sounder (AIRS) and Measurements of Pollution in the Troposphere (MOPITT) on carbon monoxide (CO) concentration over the Indo-Gangetic Plains (IGP) region. The time sequence plots of columnar CO levels over the western, central and eastern IGP regions reveal marked seasonal behaviour, with lowest CO levels occurring during the monsoon months and the highest CO levels occurring during the pre-monsoon period. A negative correlation between CO levels and rainfall is observed. CO vertical profiles show relatively high values in the upper troposphere at ∼200 hPa level during the monsoon months, thus suggesting the role of convective transport and advection in addition to washout behind the decreased CO levels during this period. MOPITT and AIRS observations show a decreasing trend of 9.6 × 1015 and 1.5 × 1016 molecules cm-2 yr-1, respectively, in columnar CO levels over the IGP region. The results show the existence of a spatial gradient in CO from the eastern (higher levels) to western IGP region (lower levels). Data from the Census of India on the number of households using various cooking fuels in the IGP region shows the prevalence of biomass-fuel (i.e. firewood, crop residue, cowdung etc.) use over the eastern and central IGP regions and that of liquefied petroleum gas over the western IGP region. CO emission estimates from cooking activity over the three IGP regions are found to be in the order east > central > west, which support the existence of the spatial gradient in CO from eastern to the western IGP region. Our results support the intervention of present Indian government on limiting the use of biomass-fuels in domestic cooking to achieve the benefits in terms of the better air quality, household health and regional/global climate change mitigation.
Peng, D, Zhang, B, Wu, C, Huete, AR, Gonsamo, A, Lei, L, Ponce-Campos, GE, Liu, X & Wu, Y 2017, 'Country-level net primary production distribution and response to drought and land cover change', Science of the Total Environment, vol. 574, pp. 65-77.View/Download from: Publisher's site
ï¿½ 2016 Elsevier B.V. Carbon sequestration by terrestrial ecosystems can offset emissions and thereby offers an alternative way of achieving the target of reducing the concentration of CO 2 in the atmosphere. Net primary production (NPP) is the first step in the sequestration of carbon by terrestrial ecosystems. This study quantifies moderate-resolution imaging spectroradiometer (MODIS) NPP from 2000 to 2014 at the country level along with its response to drought and land cover change. Our results indicate that the combined NPP for 53 countries represents > ï¿½90% of global NPP. From 2000 to 2014, 29 of these 53 countries had increasing NPP trends, most notably the Central African Republic (23ï¿½gï¿½C/m 2 /y). The top three and top 12 countries accounted for 30% and 60% of total global NPP, respectively, whereas the mean national NPP per unit area in the countries with the 12 lowest values was only around ~ï¿½300ï¿½gï¿½C/m 2 /y - the exception to this was Brazil, which had an NPP of 850ï¿½gï¿½C/m 2 /y. Large areas of Russia, Argentina, Peru and several countries in southeast Asia showed a marked decrease in NPP (~ï¿½15ï¿½gï¿½C/m 2 /y). About 37% of the NPP decrease was caused by drought while ~ï¿½55% of NPP variability was attributed to changes in water availability. Land cover change explained about 20% of the NPP variability. Our findings support the idea that government policies should aim primarily to improve water management in drought-afflicted countries; land use/land cover change policy could also be used as an alternative method of increasing NPP.
Peng, D, Zhang, X, Wu, C, Huang, W, Gonsamo, A, Huete, AR, Didan, K, Tan, B, Liu, X & Zhang, B 2017, 'Intercomparison and evaluation of spring phenology products using National Phenology Network and AmeriFlux observations in the contiguous United States', AGRICULTURAL AND FOREST METEOROLOGY, vol. 242, pp. 33-46.View/Download from: Publisher's site
Peng, D, Zhang, X, Zhang, B, Liu, L, Liu, X, Huete, AR, Huang, W, Wang, S, Luo, S, Zhang, X & Zhang, H 2017, 'Scaling effects on spring phenology detections from MODIS data at multiple spatial resolutions over the contiguous United States', ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, vol. 132, pp. 185-198.View/Download from: Publisher's site
Wongsai, N, Wongsai, S & Huete, AR 2017, 'Annual Seasonality Extraction Using the Cubic Spline Function and Decadal Trend in Temporal Daytime MODIS LST Data', REMOTE SENSING, vol. 9, no. 12.View/Download from: Publisher's site
Wu, J, Guan, K, Hayek, M, Restrepo-Coupe, N, Wiedemann, KT, Xu, X, Wehr, R, Christoffersen, BO, Miao, G, da Silva, R, de Araujo, AC, Oliviera, RC, Camargo, PB, Monson, RK, Huete, AR & Saleska, SR 2017, 'Partitioning controls on Amazon forest photosynthesis between environmental and biotic factors at hourly to interannual timescales.', Global change biology, vol. 23, no. 3, pp. 1240-1257.View/Download from: Publisher's site
Gross ecosystem productivity (GEP) in tropical forests varies both with the environment and with biotic changes in photosynthetic infrastructure, but our understanding of the relative effects of these factors across timescales is limited. Here, we used a statistical model to partition the variability of seven years of eddy covariance-derived GEP in a central Amazon evergreen forest into two main causes: variation in environmental drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with model parameters that govern photosynthesis and biotic variation in canopy photosynthetic light-use efficiency associated with changes in the parameters themselves. Our fitted model was able to explain most of the variability in GEP at hourly (R2 = 0.77) to interannual (R2 = 0.80) timescales. At hourly timescales, we found that 75% of observed GEP variability could be attributed to environmental variability. When aggregating GEP to the longer timescales (daily, monthly, and yearly), however, environmental variation explained progressively less GEP variability: At monthly timescales, it explained only 3%, much less than biotic variation in canopy photosynthetic light-use efficiency, which accounted for 63%. These results challenge modeling approaches that assume GEP is primarily controlled by the environment at both short and long timescales. Our approach distinguishing biotic from environmental variability can help to resolve debates about environmental limitations to tropical forest photosynthesis. For example, we found that biotically regulated canopy photosynthetic light-use efficiency (associated with leaf phenology) increased with sunlight during dry seasons (consistent with light but not water limitation of canopy development) but that realized GEP was nonetheless lower relative to its potential efficiency during dry than wet seasons (consistent with water limitation of photosynthesis in given assemblages of leaves). This work highlig...
Barraza, V, Restrepo-Coupe, N, Huete, A, Grings, F, Beringer, J, Cleverly, J & Eamus, D 2017, 'Estimation of latent heat flux over savannah vegetation across the North Australian Tropical Transect from multiple sensors and global meteorological data', Agricultural and Forest Meteorology, vol. 232, pp. 689-703.View/Download from: Publisher's site
Latent heat flux (LE) and corresponding water loss in non-moisture-limited ecosystems are well corre-lated to radiation and temperature. By contrast, in savannahs and arid and semi-arid lands LE is mostlydriven by available water and the vegetation exerts a strong control over the rate of transpiration.Therefore, LE models that use optical vegetation indices (VIs) to represent the vegetation component(transpiration as a function of surface conductance, Gs) generally overestimate water fluxes in water-limited ecosystems. In this study, we evaluated and compared optical and passive microwave indexbased retrievals of Gsand LE derived using the Penman-Monteith (PM) formulation over the North Aus-tralian Tropical Transect (NATT). The methodology was evaluated at six eddy covariance (EC) sites fromthe OzFlux network. To parameterize the PM equation for retrievals of LE (PM-Gs), a subset of Gsvalueswas derived from meteorological and EC flux observations and regressed against individual and com-bined satellite indices, from (1) MODIS AQUA: the Normalized Difference Water Index (NDWI) and theEnhanced Vegetation Index (EVI); and from (2) AMSR-E passive microwave: frequency index (FI), polar-ization index (PI), vegetation optical depth (VOD) and soil moisture (SM) products. Similarly, we combinedoptical and passive microwave indices (multi-sensor model) to estimate weekly Gsvalues, and evaluatedtheir spatial and temporal synergies. The multi-sensor approach explained 40–80% of LE variance at somesites, with root mean square errors (RMSE) lower than 20 W/m2and demonstrated better performanceto other satellite-based estimates of LE. The optical indices represented potential Gsassociated with thephenological status of the vegetation (e.g. leaf area index, chlorophyll content) at finer spatial resolution.The microwave indices provided information about water availability and moisture stress (e.g. watercontent in leaves and shallow soil depths, atmospheric demand) at a high tem...
Li, L, Wang, Y-P, Beringer, J, Shi, H, Cleverly, J, Cheng, L, Eamus, D, Huete, A, Hutley, L, Lu, X, Piao, S, Zhang, L, Zhang, Y & Yu, Q 2017, 'Responses of LAI to rainfall explain contrasting sensitivities to carbon uptake between forest and non-forest ecosystems in Australia', Science China Life Sciences, vol. 7, no. 1.View/Download from: Publisher's site
Non-forest ecosystems (predominant in semi-arid and arid regions) contribute significantly to the increasing trend and interannual variation of land carbon uptake over the last three decades, yet the mechanisms are poorly understood. By analysing the flux measurements from 23 ecosystems in Australia, we found the the correlation between gross primary production (GPP) and ecosystem respiration (Re) was significant for non-forest ecosystems, but was not for forests. In non-forest ecosystems, both GPP and Re increased with rainfall, and, consequently net ecosystem production (NEP) increased with rainfall. In forest ecosystems, GPP and Re were insensitive to rainfall. Furthermore sensitivity of GPP to rainfall was dominated by the rainfall-driven variation of LAI rather GPP per unit LAI in non-forest ecosystems, which was not correctly reproduced by current land models, indicating that the mechanisms underlying the response of LAI to rainfall should be targeted for future model development.
Shi, H, Li, L, Eamus, D, Huete, A, Cleverly, J, Tian, X, Yu, Q, Wang, S, Montagnani, L, Magliulo, V, Rotenberg, E, Pavelka, M & Carrara, A 2017, 'Assessing the ability of MODIS EVI to estimate terrestrial ecosystem gross primary production of multiple land cover types', Ecological Indicators, vol. 72, pp. 153-164.View/Download from: Publisher's site
tTerrestrial ecosystem gross primary production (GPP) is the largest component in the global carbon cycle.The enhanced vegetation index (EVI) has been proven to be strongly correlated with annual GPP withinseveral biomes. However, the annual GPP-EVI relationship and associated environmental regulationshave not yet been comprehensively investigated across biomes at the global scale. Here we exploredrelationships between annual integrated EVI (iEVI) and annual GPP observed at 155 flux sites, whereGPP was predicted with a log-log model: ln(GPP) = a × ln(iEVI) + b. iEVI was computed from MODISmonthly EVI products following removal of values affected by snow or cold temperature and withoutcalculating growing season duration. Through categorisation of flux sites into 12 land cover types, theability of iEVI to estimate GPP was considerably improved (R2from 0.62 to 0.74, RMSE from 454.7 to368.2 g C m−2yr−1). The biome-specific GPP-iEVI formulae generally showed a consistent performancein comparison to a global benchmarking dataset (R2= 0.79, RMSE = 387.8 g C m−2yr−1). Specifically, iEVIperformed better in cropland regions with high productivity but poorer in forests. The ability of iEVI inestimating GPP was better in deciduous biomes (except deciduous broadleaf forest) than in evergreendue to the large seasonal signal in iEVI in deciduous biomes. Likewise, GPP estimated from iEVI was ina closer agreement to global benchmarks at mid and high-latitudes, where deciduous biomes are morecommon and cloud cover has a smaller effect on remote sensing retrievals. Across biomes, a significant andnegative correlation (R2= 0.37, p < 0.05) was observed between the strength (R2) of GPP-iEVI relationshipsand mean annual maximum leaf area index (LAImax), and the relationship between the strength andmean annual precipitation followed a similar trend. LAImaxalso revealed a scaling effect on GPP-iEVIrelationships. Our results suggest that iEVI provides a very simple but robust approach to ...
Ashourloo, D, Matkan, AA, Huete, A, Aghighi, H & Mobasheri, MR 2016, 'Developing an Index for Detection and Identification of Disease Stages', IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, vol. 13, no. 6, pp. 851-855.View/Download from: Publisher's site
Huete, AR 2016, 'Peer review report 1 On "Parameterizing ecosystem light use efficiency and water use efficiency to estimate maize gross primary production and evapotranspiration using MODIS EVI"', Agricultural and Forest Meteorology, vol. 217, pp. 167-167.View/Download from: Publisher's site
Huete, AR 2016, 'Peer review report 1 On "Parameterizing ecosystem light use efficiency and water use efficiency to estimate maize gross primary production and evapotranspiration using MODIS EVI"', Agricultural and Forest Meteorology, vol. 217, pp. 172-172.View/Download from: Publisher's site
Koedsin, W, Intararuang, W, Ritchie, RJ & Huete, A 2016, 'An integrated field and remote sensing method for mapping seagrass species, cover, and biomass in Southern Thailand', Remote Sensing, vol. 8, no. 4, pp. 1-18.View/Download from: Publisher's site
© 2016 by the authors. Accurate and up-to-date maps of seagrass biodiversity are important for marine resource management but it is very challenging to test the accuracy of remote sensing techniques for mapping seagrass in coastal waters with variable water turbidity. In this study, Worldview-2 (WV-2) imagery was combined with field sampling to demonstrate the capability of mapping species type, percentage cover, and above-ground biomass of seagrasses in monsoonal southern Thailand. A high accuracy positioning technique, involving the Real Time Kinematic (RTK) Global Navigation Satellite System (GNSS), was used to record field sample data positions and reduce uncertainties in matching locations between satellite and field data sets. Our results showed high accuracy (90.67%) in mapping seagrass distribution and moderate accuracies for mapping percentage cover and species type (73.74% and 75.00%, respectively). Seagrass species type mapping was successfully achieved despite discrimination confusion among Halophila ovalis, Thalassia hemprichii, and Enhalus acoroides species with greater than 50% cover. The green, yellow, and near infrared spectral channels of WV-2 were used to estimate the above-ground biomass using a multiple linear regression model (RMSE of ±10.38 g·DW/m 2 , R = 0.68). The average total above-ground biomass was 23.95 ± 10.38 g·DW/m 2 . The seagrass maps produced in this study are an important step towards measuring the attributes of seagrass biodiversity and can be used as inputs to seagrass dynamic models and conservation efforts.
Maes, WH, Baert, A, Huete, AR, Minchin, PEH, Snelgar, WP & Steppe, K 2016, 'A new wet reference target method for continuous infrared thermography of vegetations', AGRICULTURAL AND FOREST METEOROLOGY, vol. 226, pp. 119-131.View/Download from: Publisher's site
Medek, DE, Beggs, PJ, Erbas, B, Jaggard, AK, Campbell, BC, Vicendese, D, Johnston, FH, Godwin, I, Huete, AR, Green, BJ, Burton, PK, Bowman, DMJS, Newnham, RM, Katelaris, CH, Haberle, SG, Newbigin, E & Davies, JM 2016, 'Regional and seasonal variation in airborne grass pollen levels between cities of Australia and New Zealand.', Aerobiologia, vol. 32, no. 2, pp. 289-302.View/Download from: Publisher's site
Although grass pollen is widely regarded as the major outdoor aeroallergen source in Australia and New Zealand (NZ), no assemblage of airborne pollen data for the region has been previously compiled. Grass pollen count data collected at 14 urban sites in Australia and NZ over periods ranging from 1 to 17 years were acquired, assembled and compared, revealing considerable spatiotemporal variability. Although direct comparison between these data is problematic due to methodological differences between monitoring sites, the following patterns are apparent. Grass pollen seasons tended to have more than one peak from tropics to latitudes of 37°S and single peaks at sites south of this latitude. A longer grass pollen season was therefore found at sites below 37°S, driven by later seasonal end dates for grass growth and flowering. Daily pollen counts increased with latitude; subtropical regions had seasons of both high intensity and long duration. At higher latitude sites, the single springtime grass pollen peak is potentially due to a cooler growing season and a predominance of pollen from C3 grasses. The multiple peaks at lower latitude sites may be due to a warmer season and the predominance of pollen from C4 grasses. Prevalence and duration of seasonal allergies may reflect the differing pollen seasons across Australia and NZ. It must be emphasized that these findings are tentative due to limitations in the available data, reinforcing the need to implement standardized pollen-monitoring methods across Australasia. Furthermore, spatiotemporal differences in grass pollen counts indicate that local, current, standardized pollen monitoring would assist with the management of pollen allergen exposure for patients at risk of allergic rhinitis and asthma.
Moore, CE, Brown, T, Keenan, TF, Duursma, RA, van Dijk, AIJM, Beringer, J, Culvenor, D, Evans, B, Huete, A, Hutley, LB, Maier, S, Restrepo-Coupe, N, Sonnentag, O, Specht, A, Taylor, JR, van Gorsel, E & Liddell, MJ 2016, 'Australian vegetation phenology: new insights from satellite remote sensing and digital repeat photography', Biogeosciences Discussions, pp. 1-30.View/Download from: Publisher's site
Moore, CE, Brown, T, Keenan, TF, Duursma, RA, van Dijk, AIJM, Beringer, J, Culvenor, D, Evans, B, Huete, A, Hutley, LB, Maier, S, Restrepo-Coupe, N, Sonnentag, O, Specht, A, Taylor, JR, van Gorsel, E & Liddell, MJ 2016, 'Reviews and syntheses: Australian vegetation phenology: new insights from satellite remote sensing and digital repeat photography', BIOGEOSCIENCES, vol. 13, no. 17, pp. 5085-5102.View/Download from: Publisher's site
Obata, K, Miura, T, Yoshioka, H, Huete, AR & Vargas, M 2016, 'Spectral Cross-Calibration of VIIRS Enhanced Vegetation Index with MODIS: A Case Study Using Year-Long Global Data', Remote Sensing, vol. 8, no. 34.View/Download from: Publisher's site
Peng, D, Wu, C, Zhang, B, Huete, A, Zhang, X, Sun, R, Lei, L, Huang, W, Liu, L, Liu, X, Li, J, Luo, S & Fang, B 2016, 'The Influences of Drought and Land-Cover Conversion on Inter-Annual Variation of NPP in the Three-North Shelterbelt Program Zone of China Based on MODIS Data.', PLoS ONE, vol. 11, no. 6, pp. 1-22.View/Download from: Publisher's site
Terrestrial ecosystems greatly contribute to carbon (C) emission reduction targets through photosynthetic C uptake.Net primary production (NPP) represents the amount of atmospheric C fixed by plants and accumulated as biomass. The Three-North Shelterbelt Program (TNSP) zone accounts for more than 40% of China's landmass. This zone has been the scene of several large-scale ecological restoration efforts since the late 1990s, and has witnessed significant changes in climate and human activities.Assessing the relative roles of different causal factors on NPP variability in TNSP zone is very important for establishing reasonable local policies to realize the emission reduction targets for central government. In this study, we examined the relative roles of drought and land cover conversion(LCC) on inter-annual changes of TNSP zone for 2001-2010. We applied integrated correlation and decomposition analyses to a Standardized Evapotranspiration Index (SPEI) and MODIS land cover dataset. Our results show that the 10-year average NPP within this region was about 420 Tg C. We found that about 60% of total annual NPP over the study area was significantly correlated with SPEI (p<0.05). The LCC-NPP relationship, which is especially evident for forests in the south-central area, indicates that ecological programs have a positive impact on C sequestration in the TNSP zone. Decomposition analysis generally indicated that the contributions of LCC, drought, and other Natural or Anthropogenic activities (ONA) to changes in NPP generally had a consistent distribution pattern for consecutive years. Drought and ONA contributed about 74% and 23% to the total changes in NPP, respectively, and the remaining 3% was attributed to LCC. Our results highlight the importance of rainfall supply on NPP variability in the TNSP zone.
Saleska, SR, Wu, J, Guan, K, Araujo, AC, Huete, A, Nobre, AD & Restrepo-Coupe, N 2016, 'Dry-season greening of Amazon forests.', Nature, vol. 531, no. 7594, pp. E4-E5.View/Download from: Publisher's site
Wu, J, Albert, LP, Lopes, AP, Restrepo-Coupe, N, Hayek, M, Wiedemann, KT, Guan, K, Stark, SC, Christoffersen, B, Prohaska, N, Tavares, JV, Marostica, S, Kobayashi, H, Ferreira, ML, Campos, KS, da Silva, R, Brando, PM, Dye, DG, Huxman, TE, Huete, AR, Nelson, BW & Saleska, SR 2016, 'Leaf development and demography explain photosynthetic seasonality in Amazon evergreen forests.', Science, vol. 351, no. 6276, pp. 972-976.View/Download from: Publisher's site
In evergreen tropical forests, the extent, magnitude, and controls on photosynthetic seasonality are poorly resolved and inadequately represented in Earth system models. Combining camera observations with ecosystem carbon dioxide fluxes at forests across rainfall gradients in Amazônia, we show that aggregate canopy phenology, not seasonality of climate drivers, is the primary cause of photosynthetic seasonality in these forests. Specifically, synchronization of new leaf growth with dry season litterfall shifts canopy composition toward younger, more light-use efficient leaves, explaining large seasonal increases (~27%) in ecosystem photosynthesis. Coordinated leaf development and demography thus reconcile seemingly disparate observations at different scales and indicate that accounting for leaf-level phenology is critical for accurately simulating ecosystem-scale responses to climate change.
Xie, Z, Huete, A, Ma, X, Restrepo-Coupe, N, Devadas, R, Clarke, K & Lewis, M 2016, 'Landsat and GRACE observations of arid wetland dynamics in a dryland river system under multi-decadal hydroclimatic extremes', JOURNAL OF HYDROLOGY, vol. 543, pp. 818-831.View/Download from: Publisher's site
Xie, Z, Huete, A, Restrepo-Coupe, N, Ma, X, Devadas, R & Caprarelli, G 2016, 'Spatial partitioning and temporal evolution of Australia's total water storage under extreme hydroclimatic impacts', Remote Sensing of Environment, vol. 183, pp. 43-52.View/Download from: Publisher's site
Australia experienced one of the worst droughts in history during the early 21st-century (termed the 'big dry'), exerting negative impacts on food production and water supply, with increased forest die-back and bushfires across large areas. Following the 'big dry', one of the largest La Niña events in the past century, in conjunction with an extreme positive excursion of the Southern Annular Mode (SAM), resulted in dramatic increased precipitation from 2010 to 2011 (termed the 'big wet'), causing widespread flooding and a recorded sea level drop. Despite these extreme hydroclimatic impacts, the spatial partitioning and temporal evolution of total water storage across Australia remains unknown. In this study we investigated the spatial-temporal impacts of the recent 'big dry' and 'big wet' events on Australia's water storage dynamics using the total water storage anomaly (TWSA) data derived from the Gravity Recovery and Climate Experiment (GRACE) satellites.
Results showed widespread, continental-scale decreases in TWS during the 'big dry', resulting in a net loss of 3.89 ± 0.47 cm (299 km3) total water, while the 'big wet' induced a sharp increase in TWS, equivalent to 11.68 ± 0.52 cm (898 km3) of water, or three times the total water loss during the 'big dry'. We found highly variable continental patterns in water resources, involving differences in the direction, magnitude, and duration of TWS responses to drought and wet periods. These responses clustered into three distinct geographic zones that correlated well with the influences from multiple large-scale climate modes. Specifically, a persistent increasing trend in TWS was recorded over northern and northeastern Australia, where the climate is strongly influenced by El Niño-Southern Oscillation (ENSO). By contrast, western Australia, a region predominantly controlled by the Indian Ocean Dipole (IOD), exhibited a continuous decline in TWS during the 'big dry' and only a subtle increase during the 'big wet',...
Xu, B, Li, J, Liu, Q, Huete, AR, Yu, Q, Zeng, Y, Yin, G, Zhao, J & Yang, L 2016, 'Evaluating Spatial Representativeness of Station Observations for Remotely Sensed Leaf Area Index Products', IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 7, pp. 3267-3282.View/Download from: Publisher's site
Continuous leaf area index (LAI) observations from global ground stations are an important reference dataset for the validation of remotely sensed LAI products. In this study, a pragmatic approach is presented for evaluating the spatial representativeness of station-observed LAI dataset in the product pixel grid. Three evaluation indicators, including dominant vegetation type percent (DVTP), relative absolute error (RAE) and coefficient of sill (CS), were established to quantify different levels of spatial representativeness. The DVTP was used to evaluate whether the station-observed vegetation type was the dominant one in the pixel grid, and the RAE and CS were applied to quantify the point-to-area consistency for a given station observation and the spatial heterogeneity caused by the different density of vegetation within the pixel, respectively. The proposed approach was applied to 25 stations from the Chinese Ecosystem Research Network, and results show significant differences of representativeness errors at different levels. The spatial representativeness for different stations varied seasonally with different vegetation growth stages due to temporal changes in heterogeneity, but the spatial representativeness remained consistent at interannual timeframes due to the relatively stable vegetation structure and pattern between adjacent years. A large error can occur in MOD15A2 product validation when the representativeness level of station LAI observations is low. This approach can effectively distinguish various levels of spatial representativeness for the station-observed LAI dataset at the pixel grid scale, which can consequently improve the reliability of LAI product validation by selecting LAI observations with a high degree of representativeness.
Zeng, Y, Li, J, Liu, Q, Huete, AR, Xu, B, Yin, G, Zhao, J, Yang, L, Fan, W, Wu, S & Yan, K 2016, 'An Iterative BRDF/NDVI Inversion Algorithm Based on A Posteriori Variance Estimation of Observation Errors', IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, vol. 54, no. 11, pp. 6481-6496.View/Download from: Publisher's site
Zeng, Y, Li, J, Liu, Q, Huete, AR, Yin, G, Xu, B, Fan, W, Zhao, J, Yan, K & Mu, X 2016, 'A Radiative Transfer Model for Heterogeneous Agro-Forestry Scenarios', IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 8, pp. 4613-4628.View/Download from: Publisher's site
Landscape heterogeneity is a common natural phenomenon but is seldom considered in current radiative transfer (RT) models for predicting the surface reflectance. This paper developed an analytical RT model for heterogeneous Agro-Forestry scenarios (RTAF) by dividing the scenario into nonboundary regions (NRs) and boundary regions (BRs). The scattering contribution of the NRs can be estimated from the scattering-by-arbitrarily-inclined-leaves-with-the-hot-spot-effect model as homogeneous canopies, whereas that of the BRs is calculated based on the bidirectional gap probability by considering the interactions and mutual shadowing effects among different patches. The multiangular airborne observations and discrete-anisotropic-RT model simulations were used to validate and evaluate the RTAF model over an agro-forestry scenario in the Heihe River Basin, China. The results suggest that the RTAF model can accurately simulate the hemispherical–directional reflectance factors (HDRFs) of the heterogeneous scenarios in the red and near-infrared (NIR) bands. The boundary effect can significantly influence the angular distribution of the HDRFs and consequently enlarge the HDRF variations between the backward and forward directions. Compared with the widely used dominant cover type (DCT) and spectral linear mixture (SLM) models, the RTAF model reduced the maximum relative error from 25.7% (SLM) and 23.0% (DCT) to 9.8% in the red band and from 19.6% (DCT) and 13.7% (SLM) to 8.7% in the NIR band. The RTAF model provides a promising way to improve the retrieval of biophysical parameters (e.g., leaf area index) from remote sensing data over heterogeneous agro-forestry scenarios.
Beringer, J, Hutley, LB, McHugh, I, Arndt, SK, Campbell, D, Cleugh, HA, Cleverly, J, Resco de Dios, V, Eamus, D, Evans, B, Ewenz, C, Grace, P, Griebel, A, Haverd, V, Hinko-Najera, N, Huete, A, Isaac, P, Kanniah, K, Leuning, R, Liddell, MJ, Macfarlane, C, Meyer, W, Moore, C, Pendall, E, Phillips, A, Phillips, RL, Prober, S, Restrepo-Coupe, N, Rutledge, S, Schroder, I, Silberstein, R, Southall, P, Sun, M, Tapper, NJ, van Gorsel, E, Vote, C, Walker, J & Wardlaw, T 2016, 'An introduction to the Australian and New Zealand flux tower network & OzFlux', Biogeosciences Discussions, vol. 13, pp. 5895-5916.View/Download from: Publisher's site
OzFlux is the regional Australian and New
Zealand flux tower network that aims to provide a
continental-scale national research facility to monitor and assess
trends, and improve predictions, of Australia's terrestrial
biosphere and climate. This paper describes the evolution,
design, and current status of OzFlux as well as provides an
overview of data processing. We analyse measurements from
all sites within the Australian portion of the OzFlux network
and two sites from New Zealand. The response of the Australian
biomes to climate was largely consistent with global
studies except that Australian systems had a lower ecosystem
water-use efficiency. Australian semi-arid/arid ecosystems
are important because of their huge extent (70 %) and they
have evolved with common moisture limitations. We also
found that Australian ecosystems had a similar radiationuse
efficiency per unit leaf area compared to global values
that indicates a convergence toward a similar biochemical
efficiency. The two New Zealand sites represented extremes
in productivity for a moist temperate climate zone, with the
grazed dairy farm site having the highest GPP of any OzFlux
site (2620 gC m−2 yr−1
) and the natural raised peat bog site
having a very low GPP (820 gC m−2 yr−1
). The paper discusses
the utility of the flux data and the synergies between
flux, remote sensing, and modelling. Lastly, the paper looks
ahead at the future direction of the network and concludes
that there has been a substantial contribution by OzFlux, and
considerable opportunities remain to further advance our understanding
of ecosystem response to disturbances, including
drought, fire, land-use and land-cover change, land management,
and climate change, which are relevant both nationally
and internationally. It is suggested that a synergistic approach
is required to address all of the spatial, ecological, human,
and cultural challenges of managing the delicately balanced
ecosystems in Australasia.
Beringer, J, Hutley, LB, McHugh, I, Arndt, SK, Campbell, D, Cleugh, HA, Cleverly, J, Resco de Dios, V, Eamus, D, Evans, B, Ewenz, C, Grace, P, Griebel, A, Haverd, V, Hinko-Najera, N, Huete, A, Isaac, P, Kanniah, K, Leuning, R, Liddell, MJ, Macfarlane, C, Meyer, W, Moore, C, Pendall, E, Phillips, A, Phillips, RL, Prober, SM, Restrepo-Coupe, N, Rutledge, S, Schroder, I, Silberstein, R, Southall, R, Yee, MS, van Gorsel, E, Vote, C, Walker, J & Wardlaw, T 2016, 'An introduction to the Australian and New Zealand flux tower network – OzFlux', Biogeosciences, vol. 13, pp. 5895-5916.View/Download from: Publisher's site
OzFlux is the regional Australian and New
Zealand flux tower network that aims to provide a
continental-scale national research facility to monitor and assess
trends, and improve predictions, of Australia's terrestrial
biosphere and climate. This paper describes the evolution,
design, and current status of OzFlux as well as provides an
overview of data processing.We analyse measurements from
all sites within the Australian portion of the OzFlux network
and two sites from New Zealand. The response of the Australian
biomes to climate was largely consistent with global
studies except that Australian systems had a lower ecosystem
water-use efficiency. Australian semi-arid/arid ecosystems
are important because of their huge extent (70 %) and they
have evolved with common moisture limitations. We also
found that Australian ecosystems had a similar radiationuse
efficiency per unit leaf area compared to global values
that indicates a convergence toward a similar biochemical
efficiency. The two New Zealand sites represented extremes
in productivity for a moist temperate climate zone, with the
grazed dairy farm site having the highest GPP of any OzFlux
site (2620 gCm 2 yr 1/ and the natural raised peat bog site
having a very low GPP (820 gCm 2 yr 1/. The paper discusses
the utility of the flux data and the synergies between
flux, remote sensing, and modelling. Lastly, the paper looks
ahead at the future direction of the network and concludes
that there has been a substantial contribution by OzFlux, and
considerable opportunities remain to further advance our understanding
of ecosystem response to disturbances, including
drought, fire, land-use and land-cover change, land management,
and climate change, which are relevant both nationally
and internationally. It is suggested that a synergistic approach
is required to address all of the spatial, ecological, human,
and cultural challenges of managing the delicately balanced
ecosystems in Australasia.
Cleverly, J, Eamus, D, Luo, Q, Coupe, NR, Kljun, N, Ma, X, Ewenz, C, Li, L, Yu, Q & Huete, A 2016, 'The importance of interacting climate modes on Australia's contribution to global carbon cycle extremes', SCIENTIFIC REPORTS, vol. 6.View/Download from: Publisher's site
Cleverly, J, Eamus, D, Restrepo Coupe, N, Chen, C, Maes, W, Li, L, Faux, R, Santini, NS, Rumman, R, Yu, Q & Huete, A 2016, 'Soil moisture controls on phenology and productivity in a semi-arid critical zone', Science of the Total Environment.View/Download from: Publisher's site
© 2016 Elsevier B.V. The Earth's Critical Zone, where physical, chemical and biological systems interact, extends from the top of the canopy to the underlying bedrock. In this study, we investigated soil moisture controls on phenology and productivity of an Acacia woodland in semi-arid central Australia. Situated on an extensive sand plain with negligible runoff and drainage, the carry-over of soil moisture content (θ) in the rhizosphere enabled the delay of phenology and productivity across seasons, until conditions were favourable for transpiration of that water to prevent overheating in the canopy. Storage of soil moisture near the surface (in the top few metres) was promoted by a siliceous hardpan. Pulsed recharge of θ above the hardpan was rapid and depended upon precipitation amount: 150mm storm-1 resulted in saturation of θ above the hardpan (i.e., formation of a temporary, discontinuous perched aquifer above the hardpan in unconsolidated soil) and immediate carbon uptake by the vegetation. During dry and inter-storm periods, we inferred the presence of hydraulic lift from soil storage above the hardpan to the surface due to (i) regular daily drawdown of θ in the reservoir that accumulates above the hardpan in the absence of drainage and evapotranspiration; (ii) the dimorphic root distribution wherein most roots were found in dry soil near the surface, but with significant root just above the hardpan; and (iii) synchronisation of phenology amongst trees and grasses in the dry season. We propose that hydraulic redistribution provides a small amount of moisture that maintains functioning of the shallow roots during long periods when the surface soil layer was dry, thereby enabling Mulga to maintain physiological activity without diminishing phenological and physiological responses to precipitation when conditions were favourable to promote canopy cooling.
Cleverly, J, Eamus, D, Van Gorsel, E, Chen, C, Rumman, R, Luo, Q, Coupe, NR, Li, L, Kljun, N, Faux, R, Yu, Q & Huete, A 2016, 'Productivity and evapotranspiration of two contrasting semiarid ecosystems following the 2011 global carbon land sink anomaly', AGRICULTURAL AND FOREST METEOROLOGY, vol. 220, pp. 151-159.View/Download from: Publisher's site
Eamus, D, Huete, A, Cleverly, J, Nolan, RH, Ma, X, Tarin, T & Santini, NS 2016, 'Mulga, a major tropical dry open forest of Australia: recent insights to carbon and water fluxes', Environmental Research Letters, vol. 11.View/Download from: Publisher's site
Mulga, comprised of a complex of closely related Acacia spp., grades from a low open forest to tall
shrublands in tropical and sub-tropical arid and semi-arid regions of Australia and experiences warmto-
hot annual temperatures and a pronounced dry season. This short synthesis of current knowledge
briefly outlines the causes of the extreme variability in rainfall characteristic of much of central
Australia, and then discusses the patterns and drivers of variability in carbon and water fluxes of a
central Australian low open Mulga forest. Variation in phenology and the impact of differences in the
amount and timing of precipitation on vegetation function are then discussed.Weuse field
observations, with particular emphasis on eddy covariance data, coupled with modelling and remote
sensing products to interpret inter-seasonal and inter-annual patterns in the behaviour of this
ecosystem.Weshow that Mulga can vary between periods of near carbon neutrality to periods of being
a significant sink or source for carbon, depending on both the amount and timing of rainfall. Further,
we demonstrate that Mulga contributed significantly to the 2011 global land sink anomaly, a result
ascribed to the exceptional rainfall of 2010/2011. Finally, we compare and contrast the hydraulic traits
of three tree species growing close to the Mulga and show how each species uses different
combinations of trait strategies (for example, sapwood density, xylem vessel implosion resistance,
phenological guild, access to groundwater and Huber value) to co-exist in this semi-arid environment.
Understanding the inter-annual variability in functional behaviour of this important arid-zone biome
and mechanisms underlying species co-existence will increase our ability to predict trajectories of
carbon and water balances for future changing climates.
Ma, X, Huete, A, Cleverly, J, Eamus, D, Chevallier, F, Joiner, J, Poulter, B, Zhang, Y, Guanter, L, Meyer, W, Xie, Z & Ponce-Campos, G 2016, 'Drought rapidly diminishes the large net CO2 uptake in 2011 over semi-arid Australia', Scientific Reports, vol. 6.View/Download from: Publisher's site
Each year, terrestrial ecosystems absorb more than a quarter of the anthropogenic carbon emissions, termed as land carbon sink. An exceptionally large land carbon sink anomaly was recorded in 2011, of which more than half was attributed to Australia. However, the persistence and spatially attribution of this carbon sink remain largely unknown. Here we conducted an observation-based study to characterize the Australian land carbon sink through the novel coupling of satellite retrievals of atmospheric CO2 and photosynthesis and in-situ flux tower measures. We show the 2010–11 carbon sink was primarily ascribed to savannas and grasslands. When all biomes were normalized by rainfall, shrublands however, were most efficient in absorbing carbon. We found the 2010–11 net CO2 uptake was highly transient with rapid dissipation through drought. The size of the 2010–11 carbon sink over Australia (0.97 Pg) was reduced to 0.48 Pg in 2011–12, and was nearly eliminated in 2012–13 (0.08 Pg). We further report evidence of an earlier 2000–01 large net CO2 uptake, demonstrating a repetitive nature of this land carbon sink. Given a significant increasing trend in extreme wet year precipitation over Australia, we suggest that carbon sink episodes will exert greater future impacts on global carbon cycle.
Restrepo Coupe, N, Huete, A, Davies, K, Cleverly, J, Beringer, J, Eamus, D, van Gorsel, E, Hutley, LB & Meyer, WS 2016, 'MODIS vegetation products as proxies of photosynthetic potential along a gradient of meteorologically and biologically driven ecosystem productivity', Biogeosciences, vol. 13, no. 19, pp. 5587-5608.View/Download from: Publisher's site
A direct relationship between gross ecosystem productivity (GEP) estimated by the eddy covariance (EC) method and Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices (VIs) has been observed in many temperate and tropical ecosystems. However, in Australian evergreen forests, and particularly sclerophyll and temperate woodlands, MODIS VIs do not capture seasonality of GEP. In this study, we re-evaluate the connection between satellite and flux tower data at four contrasting Australian ecosystems, through comparisons of GEP and four measures of photosynthetic potential, derived via parameterization of the light response curve: ecosystem light use efficiency (LUE), photosynthetic capacity (Pc), GEP at saturation (GEPsat), and quantum yield (α), with MODIS vegetation satellite products, including VIs, gross primary productivity (GPPMOD), leaf area index (LAIMOD), and fraction of photosynthetic active radiation (fPARMOD). We found that satellite-derived biophysical products constitute a measurement of ecosystem structure (e.g. leaf area index – quantity of leaves) and function (e.g. leaf level photosynthetic assimilation capacity – quality of leaves), rather than GEP. Our results show that in primarily meteorological-driven (e.g. photosynthetic active radiation, air temperature, and/or precipitation) and relatively aseasonal ecosystems (e.g. evergreen wet sclerophyll forests), there were no statistically significant relationships between GEP and satellite-derived measures of greenness. In contrast, for phenology-driven ecosystems (e.g. tropical savannas), changes in the vegetation status drove GEP, and tower-based measurements of photosynthetic activity were best represented by VIs. We observed the highest correlations between MODIS products and GEP in locations where key meteorological variables and vegetation phenology were synchronous (e.g. semi-arid Acacia woodlands) and low correlation at locations where they were asynchronous (e.g. Mediterran...
Restrepo-Coupe, N, Huete, A, Davies, K, Cleverly, J, Beringer, J, Eamus, D, van Gorsel, E, Hutley, LB & Meyer, WS 2016, 'MODIS vegetation products as proxies of photosynthetic potentialalong a gradient of meteorologically and biologically drivenecosystem productivity', Biogeosciences Discussions, vol. 13, pp. 5587-5608.View/Download from: Publisher's site
A direct relationship between gross ecosystem
productivity (GEP) estimated by the eddy covariance (EC)
method and Moderate Resolution Imaging Spectroradiometer
(MODIS) vegetation indices (VIs) has been observed in
many temperate and tropical ecosystems. However, in Australian
evergreen forests, and particularly sclerophyll and
temperate woodlands, MODIS VIs do not capture seasonality
of GEP. In this study, we re-evaluate the connection between
satellite and flux tower data at four contrasting Australian
ecosystems, through comparisons of GEP and four
measures of photosynthetic potential, derived via parameterization
of the light response curve: ecosystem light use effi-
ciency (LUE), photosynthetic capacity (Pc), GEP at saturation
(GEPsat), and quantum yield (α), with MODIS vegetation
satellite products, including VIs, gross primary productivity
(GPPMOD), leaf area index (LAIMOD), and fraction of
photosynthetic active radiation (fPARMOD). We found that
satellite-derived biophysical products constitute a measurement
of ecosystem structure (e.g. leaf area index – quantity
of leaves) and function (e.g. leaf level photosynthetic assimilation
capacity – quality of leaves), rather than GEP. Our results
show that in primarily meteorological-driven (e.g. photosynthetic
active radiation, air temperature, and/or precipitation)
and relatively aseasonal ecosystems (e.g. evergreen
wet sclerophyll forests), there were no statistically signifi-
cant relationships between GEP and satellite-derived measures
of greenness. In contrast, for phenology-driven ecosystems
(e.g. tropical savannas), changes in the vegetation status
drove GEP, and tower-based measurements of photosynthetic
activity were best represented by VIs. We observed
the highest correlations between MODIS products and GEP
in locations where key meteorological variables and vegetation
phenology were synchronous (e.g. semi-arid Acacia
woodlands) and low correlation at locations where they were
asynchronous (e.g. Medite...
Barraza, V, Restrepo-Coupe, N, Huete, A, Grings, F & Van Gorsel, E 2015, 'Passive microwave and optical index approaches for estimating surface conductance and evapotranspiration in forest ecosystems', AGRICULTURAL AND FOREST METEOROLOGY, vol. 213, pp. 126-137.View/Download from: Publisher's site
Beggs, PJ, Katelaris, CH, Medek, D, Johnston, FH, Burton, PK, Campbell, B, Jaggard, AK, Vicendese, D, Bowman, DMJS, Godwin, I, Huete, AR, Erbas, B, Green, BJ, Newnham, RM, Newbigin, E, Haberle, SG & Davies, JM 2015, 'Differences in grass pollen allergen exposure across Australia', AUSTRALIAN AND NEW ZEALAND JOURNAL OF PUBLIC HEALTH, vol. 39, no. 1, pp. 51-55.View/Download from: Publisher's site
Bi, J, Knyazikhin, Y, Choi, S, Park, T, Barichivich, J, Ciais, P, Fu, R, Ganguly, S, Hall, F, Hilker, T, Huete, A, Jones, M, Kimball, J, Lyapustin, AI, Mottus, M, Nemani, RR, Piao, S, Poulter, B, Saleska, SR, Saatchi, SS, Xu, L, Zhou, L & Myneni, RB 2015, 'Sunlight mediated seasonality in canopy structure and photosynthetic activity of Amazonian rainforests', ENVIRONMENTAL RESEARCH LETTERS, vol. 10, no. 6.View/Download from: Publisher's site
Broich, M, Huete, A, Paget, M, Ma, X, Tulbure, M, Coupe, NR, Evans, B, Beringer, J, Devadas, R, Davies, K & Held, A 2015, 'A spatially explicit land surface phenology data product for science, monitoring and natural resources management applications', ENVIRONMENTAL MODELLING & SOFTWARE, vol. 64, pp. 191-204.View/Download from: Publisher's site
Davies, JM, Beggs, PJ, Medek, DE, Newnham, RM, Erbas, B, Thibaudon, M, Katelaris, CH, Haberle, SG, Newbigin, EJ & Huete, AR 2015, 'Trans-disciplinary research in synthesis of grass pollen aerobiology and its importance for respiratory health in Australasia', SCIENCE OF THE TOTAL ENVIRONMENT, vol. 534, pp. 85-96.View/Download from: Publisher's site
Koedsin, W & Huete, A 2015, 'Mapping rubber tree stand age using pléiades satellite imagery: A case study in Thalang District, Phuket, Thailand', Engineering Journal, vol. 19, no. 4, pp. 45-56.View/Download from: Publisher's site
The rubber stand age information is an important variable for determining the distribution of carbon pools and fluxes in rubber plantation ecosystems as well as for production management. This study demonstrates the capability of high spatial resolution satellite imagery as Pléiades Satellite Imagery with the help of feature selection (i.e., Sequential Forward Floating Selection) to improve the accuracy of rubber stand age mapping at a part of Thalang district, Phuket, Thailand. The 238 sample plots were used to classification and accuracy assessment. This study found that the Pléiades imagery with the help of Sequential Forward Floating Selection can successfully classify rubber stands age between less than 7 years, 7-15 years and more than 15 years, respectively. The total testing accuracy was improved from 94.07% to 94.92% and 96.61% after applying the Principal Component and the Sequential Forward Floating Selection algorithms, respectively. Since the methodology proposed in this study can accurately classify 3 classes of rubber stand age, it is anticipated that this methodology can be used as a guideline for rubber tree stand age mapping in other study areas.
Ma, X, Huete, A, Moran, S, Ponce-Campos, G & Eamus, D 2015, 'Abrupt shifts in phenology and vegetation productivity under climate extremes', Journal of Geophysical Research: Biogeosciences, vol. 120, no. 10, pp. 2036-2052.View/Download from: Publisher's site
Amplification of the hydrologic cycle as a consequence of global warming is predicted to increase climate variability and the frequency and severity of droughts. Recent large-scale drought and flooding over numerous continents provide unique opportunities to understand ecosystem responses to climatic extremes. In this study, we investigated the impacts of the early 21st century extreme hydroclimatic variations in southeastern Australia on phenology and vegetation productivity using Moderate Resolution Imaging Spectroradiometer Enhanced Vegetation Index and Standardized Precipitation-Evapotranspiration Index. Results revealed dramatic impacts of drought and wet extremes on vegetation dynamics, with abrupt between year changes in phenology. Drought resulted in widespread reductions or collapse in the normal patterns of seasonality such that in many cases there was no detectable phenological cycle during drought years. Across the full range of biomes examined, we found semiarid ecosystems to exhibit the largest sensitivity to hydroclimatic variations, exceeding that of arid and humid ecosystems. This result demonstrated the vulnerability of semiarid ecosystems to climatic extremes and potential loss of ecosystem resilience with future mega-drought events. A skewed distribution of hydroclimatic sensitivity with aridity is of global biogeochemical significance because it suggests that current drying trends in semiarid regions will reduce hydroclimatic sensitivity and suppress the large carbon sink that has been reported during recent wet periods (e.g., 2011 La Niña).
Zeng, Y, Li, J, Liu, Q, Qu, Y, Huete, AR, Xu, B, Yin, G & Zhao, J 2015, 'An Optimal Sampling Design for Observing and Validating Long-Term Leaf Area Index with Temporal Variations in Spatial Heterogeneities', REMOTE SENSING, vol. 7, no. 2, pp. 1300-1319.View/Download from: Publisher's site
Eamus, D, Zolfaghar, S, Villalobos-Vega, R, Cleverly, J & Huete, A 2015, 'Groundwater-dependent ecosystems: recent insights from satellite and field based studies', Hydrology and Earth System Sciences, vol. 19, pp. 4229-4256.View/Download from: Publisher's site
Groundwater-dependent ecosystems (GDEs) are at risk globally due to unsustainable levels of groundwater extraction, especially in arid and semi-arid regions. In this review, we examine recent developments in the ecohydrology of GDEs with a focus on three knowledge gaps: (1) how
do we locate GDEs, (2) how much water is transpired from shallow aquifers by GDEs and (3) what are the responses of GDEs to excessive groundwater extraction? The answers to these questions will determine water allocations that are required to sustain functioning of GDEs and to guide regulations on groundwater extraction to avoid negative impacts on
We discuss three methods for identifying GDEs: (1) techniques relying on remotely sensed information; (2) fluctuations in depth-to-groundwater that are associated with diurnal variations in transpiration; and (3) stable isotope analysis of water sources in the transpiration stream. We then discuss several methods for estimating rates of GW use, including direct measurement using sapflux or eddy covariance technologies, estimation of a climate wetness index within a Budyko framework, spatial distribution of evapotranspiration (ET) using remote sensing, groundwater modelling and stable isotopes. Remote sensing methods often rely on direct measurements to calibrate the relationship between
vegetation indices and ET. ET from GDEs is also determined using hydrologic models of varying complexity, from the White method to fully coupled, variable saturation models. Combinations of methods are typically employed to obtain clearer insight into the components of groundwater discharge in GDEs, such as the proportional importance of
transpiration versus evaporation (e.g. using stable isotopes) or from groundwater versus rainwater sources. Groundwater extraction can have severe consequences for the structure and function of GDEs. In the most extreme cases, phreatophytes experience crown dieback and death
following groundwater drawdown.We provide a brief...
Eamus, D, Zolfaghar, S, Villalobos-Vega, R, Cleverly, J & Huete, A 2015, 'Groundwater-dependent ecosystems: recent insights, new techniques and an ecosystem-scale threshold response', Hydrology and Earth System Sciences Discussions, vol. 12, no. 5, pp. 4677-4754.View/Download from: Publisher's site
Abstract. Groundwater-dependent ecosystems (GDEs) are at risk globally due to unsustainable levels of groundwater extraction, especially in arid and semi-arid regions. In this review, we examine recent developments in the ecohydrology of GDEs with a focus on three knowledge gaps: (1) how do we locate GDEs, (2) how much water is transpired from shallow aquifers by GDEs; and (3) what are the responses of GDEs to excessive groundwater extraction? The answers to these questions will determine water allocations that are required to sustain functioning of GDEs and to guide regulations on groundwater extraction to avoid negative impacts on GDEs. We discuss three methods for identifying GDEs: (1) fluctuations in depth-to-groundwater that are associated with diurnal variations in transpiration, (2) stable isotope analysis of water sources in the transpiration stream; and (3) remote sensing methods. We then discuss several methods for estimating rates of GW use, including direct measurement using sapflux or eddy covariance technologies, estimation of a climate wetness index within a Budyko framework, spatial distribution of ET using remote sensing, groundwater modelling and stable isotopes. Remote sensing methods often rely on direct measurements to calibrate the relationship between vegetation indices and ET. ET from GDEs is also determined using hydrologic models of varying complexity, from the "White method" to fully coupled, variable saturation models. Combinations of methods are typically employed to obtain clearer insight into the components of groundwater discharge in GDEs, such as the proportional importance of transpiration vs. evaporation (e.g., using stable isotopes) or from groundwater vs. rainwater sources. Groundwater extraction can have severe consequences on structure and function of GDEs. In the most extreme cases, phreatophytes experience crown dieback and death following groundwater drawdown. We provide a brief review of two case studies of th...
Ashourloo, D, Mobasheri, MR & Huete, A 2014, 'Developing Two Spectral Disease Indices for Detection of Wheat Leaf Rust (Pucciniatriticina)', Remote Sensing, vol. 6, no. 6, pp. 4723-4740.View/Download from: Publisher's site
Spectral vegetation indices (SVIs) have been widely used to detect different plant diseases. Wheat leaf rust manifests itself as an early symptom with the leaves turning yellow and orange. The sign of advancing disease is the leaf colour changing to brown while the final symptom is when the leaf becomes dry. The goal of this work is to develop spectral disease indices for the detection of leaf rust. The reflectance spectra of the wheats infected and non-infected leaves at different disease stages were collected using a spectroradiometer. As ground truth, the ratio of the disease-affected area to the total leaf area and the fractions of the different symptoms were extracted using an RGB digital camera. Fractions of the various disease symptoms extracted by the digital camera and the measured reflectance spectra of the infected leaves were used as input to the spectral mixture analysis (SMA). Then, the spectral reflectance of the different disease symptoms were estimated using SMA and the least squares method. The reflectance of different disease symptoms in the 450~1000 nm were studied carefully using the Fisher function. Two spectral disease indices were developed based on the reflectance at the 605, 695 and 455 nm wavelengths. In both indices, the R2 between the estimated and the observed was as highas 0.94.
Ashourloo, D, Mobasheri, MR & Huete, A 2014, 'Evaluating the Effect of Different Wheat Rust Disease Symptoms on Vegetation Indices Using Hyperspectral Measurements', Remote Sensing, vol. 6, no. 6, pp. 5107-5123.View/Download from: Publisher's site
Spectral Vegetation Indices (SVIs) have been widely used to indirectly detect plant diseases. The aim of this research is to evaluate the effect of different disease symptoms on SVIs and introduce suitable SVIs to detect rust disease. Wheat leaf rust is one of the prevalent diseases and has different symptoms including yellow, orange, dark brown, and dry areas. The reflectance spectrum data for healthy and infected leaves were collected using a spectroradiometer in the 450 to 1000 nm range. The ratio of the disease-affected area to the total leaf area and the proportion of each disease symptoms were obtained using RGB digital images. As the disease severity increases, so does the scattering of all SVI values. The indices were categorized into three groups based on their accuracies in disease detection. A few SVIs showed an accuracy of more than 60% in classification. In the first group, NBNDVI, NDVI, PRI, GI, and RVSI showed the highest amount of classification accuracy. The second and third groups showed classification accuracies of about 20% and 40% respectively. Results show that few indices have the ability to indirectly detect plant disease.
Barraza, V, Grings, F, Ferrazzoli, P, Huete, A, Restrepo-Coupe, N, Beringer, J, Van Gorsel, E & Karszenbaum, H 2014, 'Behavior of multitemporal and multisensor passive microwave indices in Southern Hemisphere ecosystems', Journal of Geophysical Research G: Biogeosciences, vol. 119, no. 12, pp. 2231-2244.View/Download from: Publisher's site
This study focused on the time series analysis of passive microwave and optical satellite data collected from six Southern Hemisphere ecosystems in Australia and Argentina. The selected ecosystems represent a wide range of land cover types, including deciduous open forest, temperate forest, tropical and semiarid savannas, and grasslands. We used two microwave indices, the frequency index (FI) and polarization index (PI), to assess the relative contributions of soil and vegetation properties (moisture and structure) to the observations. Optical-based satellite vegetation products from the Moderate Resolution Imaging Spectroradiometer were also included to aid in the analysis. We studied the X and Ka bands of the Advanced Microwave Scanning Radiometer-EOS and Wind Satellite, resulting in up to four observations per day (1:30, 6:00, 13:30, and 18:00h). Both the seasonal and hourly variations of each of the indices were examined. Environmental drivers (precipitation and temperature) and eddy covariance measurements (gross ecosystem productivity and latent energy) were also analyzed. It was found that in moderately dense forests, FI was dependent on canopy properties (leaf area index and vegetation moisture). In tropical woody savannas, a significant regression (R2) was found between FI and PI with precipitation (R2>0.5) and soil moisture (R2>0.6). In the areas of semiarid savanna and grassland ecosystems, FI variations found to be significantly related to soil moisture (R2>0.7) and evapotranspiration (R2>0.5), while PI varied with vegetation phenology. Significant differences (p<0.01) were found among FI values calculated at the four local times.
Guanter, L, Zhang, Y, Jung, M, Joiner, J, Voigt, M, Berry, JA, Frankenberg, C, Huete, AR, Zarco-Tejada, P, Lee, J-E, Moran, MS, Ponce-Campos, G, Beer, C, Camps-Valls, G, Buchmann, N, Gianelle, D, Klumpp, K, Cescatti, A, Baker, JM & Griffis, TJ 2014, 'Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence', PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, vol. 111, no. 14, pp. E1327-E1333.View/Download from: Publisher's site
Guanter, L, Zhang, Y, Jung, M, Joiner, J, Voigt, M, Berry, JA, Frankenberg, C, Huete, AR, Zarco-Tejada, P, Lee, J-E, Moran, MS, Ponce-Campos, G, Beer, C, Camps-Valls, G, Buchmann, N, Gianelle, D, Klumpp, K, Cescatti, A, Baker, JM & Griffis, TJ 2014, 'Reply to Magnani et al.: Linking large-scale chlorophyll fluorescence observations with cropland gross primary production', PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, vol. 111, no. 25, pp. E2511-E2511.View/Download from: Publisher's site
Haberle, S, Bowman, D, Newnham, RM, Johnston, FH, Beggs, PJ, Buters, J, Campbell, B, Erbas, B, Godwin, I, Green, BJ, Huete, A, Jaggard, AK, Medek, D, Murray, F, Newbigin, E, Thibaudon, M, Vicendese, D, Williamson, GJ & Davies, JM 2014, 'The Macroecology of Airborne Pollen in Australian and New Zealand Urban Areas', PLoS One, vol. 9, no. 5.View/Download from: Publisher's site
The composition and relative abundance of airborne pollen in urban areas of Australia and New Zealand are strongly influenced by geographical location, climate and land use. There is mounting evidence that the diversity and quality of airborne pollen is substantially modified by climate change and land-use yet there are insufficient data to project the future nature of these changes. Our study highlights the need for long-term aerobiological monitoring in Australian and New Zealand urban areas in a systematic, standardised, and sustained way, and provides a framework for targeting the most clinically significant taxa in terms of abundance, allergenic effects and public health burden.
Moran, MS, Ponce-Campos, G, Huete, A, McClaran, MP, Zhang, Y, Hamerlynck, EP, Augustine, DJ, Gunter, SA, Kitchen, SG, Peters, DP, Starks, PJ & Hernandez, M 2014, 'Functional response of U.S. grasslands to the early 21st-century drought', Ecology, vol. 95, no. 8, pp. 2121-2133.View/Download from: Publisher's site
Grasslands across the United States play a key role in regional livelihood and national food security. Yet, it is still unclear how this important resource will respond to the prolonged warm droughts and more intense rainfall events predicted with climate change. The early 21st-century drought in the southwestern United States resulted in hydroclimatic conditions that are similar to those expected with future climate change. We investigated the impact of the early 21st-century drought on aboveground net primary production (ANPP) of six desert and plains grasslands dominated by C4 (warm season) grasses in terms of significant deviations between observed and expected ANPP. In desert grasslands, drought-induced grass mortality led to shifts in the functional response to annual total precipitation (PT), and in some cases, new species assemblages occurred that included invasive species. In contrast, the ANPP in plains grasslands exhibited a strong linear function of the current-year PT and the previous-year ANPP, despite prolonged warm drought. We used these results to disentangle the impacts of interannual total precipitation, intra-annual precipitation patterns, and grassland abundance on ANPP, and thus generalize the functional response of C4 grasslands to predicted climate change. This will allow managers to plan for predictable shifts in resources associated with climate change related to fire risk, loss of forage, and ecosystem services.
Obata, K & Huete, A 2014, 'Scaling effects on area-averaged fraction of vegetation cover derived using a linear mixture model with two-band spectral vegetation index constraints', Journal of Applied Remote Sensing, vol. 8, no. 1.View/Download from: Publisher's site
This study investigated the mechanisms underlying the scaling effects that apply to a fraction of vegetation cover (FVC) estimates derived using two-band spectral vegetation index (VI) isoline-based linear mixture models (VI isoline-based LMM). The VIs included the normalized difference vegetation index, a soil-adjusted vegetation index, and a two-band enhanced vegetation index (EVI2). This study focused in part on the monotonicity of an area-averaged FVC estimate as a function of spatial resolution. The proof of monotonicity yielded measures of the intrinsic area-averaged FVC uncertainties due to scaling effects. The derived results demonstrate that a factor ?, which was defined as a function of true and estimated endmember spectra of the vegetated and nonvegetated surfaces, was responsible for conveying monotonicity or nonmonotonicity. The monotonic FVC values displayed a uniform increasing or decreasing trend that was independent of the choice of the two-band VI. Conditions under which scaling effects were eliminated from the FVC were identified. Numerical simulations verifying the monotonicity and the practical utility of the scaling theory were evaluated using numerical experiments applied to Landsat7-Enhanced Thematic Mapper Plus (ETM+) data. The findings contribute to developing scale-invariant FVC estimation algorithms for multisensor and data continuity.
Thenkabail, PS, Gumma, MK, Teluguntla, P & Mohammed, IA 2014, 'HYPERSPECTRAL REMOTE SENSING OF VEGETATION AND AGRICULTURAL CROPS', PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, vol. 80, no. 8, pp. 697-709.
Zhang, Y, Guanter, L, Berry, JA, Joiner, J, van der Tol, C, Huete, A, Anatoly, G, Voigt, M & Köhler, P 2014, 'Estimation of vegetation photosynthetic capacity from space-based measurements of chlorophyll fluorescence for terrestrial biosphere models', Global Change Biology, vol. in press.View/Download from: Publisher's site
Photosynthesis simulations by terrestrial biosphere models are usually based on the Farquhar's model, in which the maximum rate of carboxylation (Vcmax) is a key control parameter of photosynthetic capacity. Even though Vcmax is known to vary substantially in space and time in response to environmental controls, it is typically parameterized in models with tabulated values associated to plant functional types. Remote sensing can be used to produce a spatially continuous and temporally resolved view on photosynthetic efficiency, but traditional vegetation observations based on spectral reflectance lack a direct link to plant photochemical processes. Alternatively, recent space-borne measurements of sun-induced chlorophyll fluorescence (SIF) can offer an observational constraint on photosynthesis simulations. Here, we show that top-of-canopy SIF measurements from space are sensitive to Vcmax at the ecosystem level, and present an approach to invert Vcmax from SIF data. We use the Soil-Canopy Observation of Photosynthesis and Energy (SCOPE) balance model to derive empirical relationships between seasonal Vcmax and SIF which are used to solve the inverse problem. We evaluate our Vcmax estimation method at six agricultural flux tower sites in the midwestern US using spaced-based SIF retrievals. Our Vcmax estimates agree well with literature values for corn and soybean plants (average values of 37 and 101 µmol m-2 s-1, respectively) and show plausible seasonal patterns. The effect of the updated seasonally varying Vcmax parameterization on simulated gross primary productivity (GPP) is tested by comparing to simulations with fixed Vcmax values. Validation against flux tower observations demonstrate that simulations of GPP and light use efficiency improve significantly when our time-resolved Vcmax estimates from SIF are used, with R2 for GPP comparisons increasing from 0.85 to 0.93, and for light use efficiency from 0.44 to 0.83. Our results support the use of space-base...
Ma, X, Huete, A, Yu, Q, Restrepo-Coupe, N, Beringer, J, Hutley, LB, Kanniah, KD, Cleverly, J & Eamus, D 2014, 'Parameterization of an ecosystem light-use-efficiency model for predicting savanna GPP using MODIS EVI', REMOTE SENSING OF ENVIRONMENT, vol. 154, pp. 253-271.View/Download from: Publisher's site
Shi, H, Li, L, Eamus, D, Cleverly, J, Huete, A, Beringer, J, Yu, Q, van Gorsel, E & Hutley, L 2014, 'Intrinsic climate dependency of ecosystem light and water-use-efficiencies across Australian biomes', Environmental Research Letters, vol. 9, no. 10, pp. 104002-104002.View/Download from: Publisher's site
The sensitivity of ecosystem gross primary production (GPP) to availability of water and photosynthetically active radiation (PAR) differs among biomes. Here we investigated variations of ecosystem light-use-efficiency (eLUE: GPP/PAR) and water-use-efficiency (eWUE: GPP/evapotranspiration) among seven Australian eddy covariance sites with differing annual precipitation, species composition and temperature. Changes to both eLUE and eWUE were primarily correlated with atmospheric vapor pressure deficit (VPD) at multiple temporal scales across biomes, with minor additional correlations observed with soil moisture and temperature. The effects of leaf area index on eLUE and eWUE were also relatively weak compared to VPD, indicating an intrinsic dependency of eLUE and eWUE on climate. Additionally, eLUE and eWUE were statistically different for biomes between summer and winter, except eWUE for savannas and the grassland. These findings will improve our understanding of how light- and water-use traits in Australian ecosystems may respond to climate change.
Mariotto, I, Thenkabail, PS, Huete, A, Slonecker, ET & Platonov, A 2013, 'Hyperspectral versus multispectral crop-productivity modeling and type discrimination for the HyspIRI mission', Remote Sensing Of Environment, vol. 139, no. 1, pp. 291-305.View/Download from: Publisher's site
Precise monitoring of agricultural crop biomass and yield quantities is critical for crop production management and prediction. The goal of this study was to compare hyperspectral narrowband (HNB) versus multispectral broadband (MBB) reflectance data in studying irrigated cropland characteristics of five leading world crops (cotton, wheat, maize, rice, and alfalfa) with the objectives of: 1. Modeling crop productivity, and 2. Discriminating crop types. HNB data were obtained from Hyperion hyperspectral imager and field ASD spectroradiometer, and MBB data were obtained from five broadband sensors: Landsat-7 Enhanced Thematic Mapper Plus (ETM +), Advanced Land Imager (ALI), Indian Remote Sensing (IRS), IKONOS, and QuickBird. A large collection of field spectral and biophysical variables were gathered for the 5 crops in Central Asia throughout the growing seasons of 2006 and 2007. Overall, the HNB and hyperspectral vegetation index (HVI) crop biophysical models explained about 25% greater variability when compared with corresponding MBB models. Typically, 3 to 7 HNBs, in multiple linear regression models of a given crop variable, explained more than 93% of variability in crop models. The evaluation of ?1 (4002500 nm) versus ?2 (4002500 nm) plots of various crop biophysical variables showed that the best two-band normalized difference HVIs involved HNBs centered at: (i) 742 nm and 1175 nm (HVI742-1175), (ii) 1296 nm and 1054 nm (HVI1296-1054), (iii) 1225 nm and 697 nm (HVI1225-697), and (iv) 702 nm and 1104 nm (HVI702-1104).
Miura, T, Turner, JP & Huete, A 2013, 'Spectral compatibility of the NDVI across VIIRS, MODIS, and AVHRR: An analysis of atmospheric effects using EO-1 hyperion', IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 3, pp. 1349-1359.View/Download from: Publisher's site
We evaluated the cross-sensor compatibilities of the normalized difference vegetation index (NDVI) across the Visible/Infrared Imager/Radiometer Suite (VIIRS), Moderate Resolution Imaging Spectroradiometer (MODIS), and the National Oceanic and Atmospheric Administration (NOAA)-14 and NOAA-19 Advanced Very High Resolution Radiometer (AVHRR) (AVHRR/2 and AVHRR/3) bandpasses using a global set of Earth Observing One Hyperion hyperspectral data. Five levels of atmospheric correction were simulated to examine the impact of the atmosphere on intersensor NDVI compatibility. These were the uncorrected âtop-of-atmosphereâ; Rayleigh (RAY); Rayleigh and ozone (RO); Rayleigh, ozone, and water vapor (ROW); and total atmosphere-corrected âtop-of-canopy (TOC)â reflectances. Among all possible sensor pairs examined, the highest compatibility was observed for VIIRS versus MODIS. Cross-sensor NDVI relationships between the two sensor bandpasses remained nearly the same throughout all levels of atmospheric correction. AVHRR/3-versus-AVHRR/2 NDVI relationships changed very little and also showed an equivalent level of compatibility to VIIRS versus MODIS across all levels of atmospheric correction although they were subject to systematic differences. Intersensor NDVI compatibilities of VIIRS and MODIS to AVHRR/2 and to AVHRR/3 were lower due primarily to the differential sensitivities of these sensorsâ near-infrared bands to the atmospheric water vapor effects. Comparisons of cross-sensor NDVI compatibilities where operational atmospheric correction schemes were assumed for each of the sensors suggest the need of VIIRS TOC NDVI for long-term continuity with MODIS and AVHRR, which is not currently produced as part of the standard VIIRS Vegetation Index Environmental Data Record.
Monteiro, AT, Fava, F, Goncalves, J, Huete, A, Gusmeroli, F, Parolo, G, Spano, D & Bocchi, S 2013, 'Landscape context determinants to plant diversity in the permanent meadows of Southern European Alps', Biodiversity and Conservation, vol. 22, no. 4, pp. 937-958.View/Download from: Publisher's site
In the Southern Alps, the role of landscape context on meadows plant diversity was evaluated using a multi-model information theoretic approach and five competing hypotheses of landscape context factors: habitat quality (H1), matrix quality (H2), habitat change (H3), matrix quality change (H4) and topography-environmental conditions (H5)- measured at three spatial scales (125, 250 and 500 m). Shannon diversity index and species richness represented plant diversity obtained in 34 plots (100 m2 size). Landscape context affected plant diversity measures differently. Matrix quality change at larger scale (500 m) was the most supported hypothesis explaining Shannon diversity index, while species richness responded mostly to topography-environmental conditions in the immediate surroundings (125 m). No effects of present-day habitat and matrix quality (H1 and H2) were found. Matrix quality change affected positively Shannon diversity index through an effect of landscape neighbourhood context on farming management practices. Due to the importance of exposure and inclination of slopes, topography-environmental conditions influenced species richness mostly through energy-driven processes and farming management strategies. In terms of scale, matrix quality change was the strongest hypothesis explaining Shannon diversity index at all scales, while the underlying process affecting species richness changed with scale (H5 or H3). Overall, landscape context explained only 2528 % of the variation in plant diversity, suggesting that landscape management may support biodiversity conservation when comprised in a global strategy including farming practices. In the study area, change in landscape diversity may be a good indicator for Shannon diversity index and south-eastern facing meadows should be preserved.
Obata, K, Miura, T, Yoshioka, H & Huete, AR 2013, 'Derivation of a MODIS-compatible enhanced vegetation index from visible infrared imaging radiometer suite spectral reflectances using vegetation isoline equations', JOURNAL OF APPLIED REMOTE SENSING, vol. 7.View/Download from: Publisher's site
Peng, D, Jiang, Z, Huete, A, Ponce Campos, GE, Nguyen, U & Luvall, JC 2013, 'Response of Spectral Reflectances and Vegetation Indices on Varying Juniper Cone Densities', Remote Sensing, vol. 5, no. 10, pp. 5330-5345.View/Download from: Publisher's site
Juniper trees are widely distributed throughout the world and are common sources of allergies when microscopic pollen grains are transported by wind and inhaled. In this study, we investigated the spectral influences of pollen-discharging male juniper cones within a juniper canopy. This was done through a controlled outdoor experiment involving ASD FieldSpec Pro Spectroradiometer measurements over juniper canopies of varying cone densities. Broadband and narrowband spectral reflectance and vegetation index (VI) patterns were evaluated as to their sensitivity and their ability to discriminate the presence of cones. The overall aim of this research was to assess remotely sensed phenological capabilities to detect pollen-bearing juniper trees for public health applications. A general decrease in reflectance values with increasing juniper cone density was found, particularly in the Green (545565 nm) and NIR (7501,350 nm) regions. In contrast, reflectances in the shortwave-infrared (SWIR, 2,000 nm to 2,350 nm) region decreased from no cone presence to intermediate amounts (90 g/m2) and then increased from intermediate levels to the highest cone densities (200 g/m2). Reflectance patterns in the Red (620700 nm) were more complex due to shifting contrast patterns in absorptance between cones and juniper foliage, where juniper foliage is more absorbing than cones only within the intense narrowband region of maximum chlorophyll absorption near 680 nm. Overall, narrowband reflectances were more sensitive to cone density changes than the equivalent MODIS broadbands. In all VIs analyzed, there were significant relationships with cone density levels, particularly with the narrowband versions and the two-band vegetation index (TBVI) based on Green and Red bands, a promising outcome for the use of phenocams in juniper phenology trait studies. These results indicate that spectral indices are sensitive to certain juniper phenologic traits that can potentially be used for juniper c...
Ponce Campos, GE, Moran, MS, Huete, A, Zhang, Y, Bresloff, C, Huxman, TE, Eamus, D, Bosch, DD, Buda, AR, Gunter, SA, Heartsill Scalley, T, Kitchen, SG, McClaran, MP, McNab, WH, Montoya, DS, Morgan, JA, Peters, DP, Sadler, EJ, Seyfried, S & Starks, PJ 2013, 'Ecosystem resilience despite large-scale altered hydroclimatic conditions', Nature, vol. 494, pp. 349-353.View/Download from: Publisher's site
Climate change is predicted to increase both drought frequency and duration, and when coupled with substantial warming, will establish a new hydroclimatological model for many regions1. Large-scale, warm droughts have recently occurred in North America, Africa, Europe, Amazonia and Australia, resulting in major effects on terrestrial ecosystems, carbon balance and food security2, 3. Here we compare the functional response of above-ground net primary production to contrasting hydroclimatic periods in the late twentieth century (19751998), and drier, warmer conditions in the early twenty-first century (20002009) in the Northern and Southern Hemispheres. We find a common ecosystem water-use efficiency (WUEe: above-ground net primary production/evapotranspiration) across biomes ranging from grassland to forest that indicates an intrinsic system sensitivity to water availability across rainfall regimes, regardless of hydroclimatic conditions. We found higher WUEe in drier years that increased significantly with drought to a maximum WUEe across all biomes; and a minimum native state in wetter years that was common across hydroclimatic periods. This indicates biome-scale resilience to the interannual variability associated with the early twenty-first century droughtthat is, the capacity to tolerate low, annual precipitation and to respond to subsequent periods of favourable water balance. These findings provide a conceptual model of ecosystem properties at the decadal scale applicable to the widespread altered hydroclimatic conditions that are predicted for later this century. Understanding the hydroclimatic threshold that will break down ecosystem resilience and alter maximum WUEe may allow us to predict land-surface consequences as large regions become more arid, starting with water-limited, low-productivity grasslands.
Potgieter, AB, Lawson, K & Huete, A 2013, 'Determining crop acreage estimates for specific winter crops using shape attributes from sequential MODIS imagery', Journal of Applied Earth Observation and Geoinformation, vol. 23, pp. 254-263.View/Download from: Publisher's site
There are increasing societal and plant industry demands for more accurate, objective and near real-time crop production information to meet both economic and food security concerns. The advent of the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite platform has augmented the capability of satellite-based applications to monitor large agricultural areas at acceptable pixel scale, cost and accuracy. Fitting parametric profiles to growing season vegetation index time series reduces the volume of data and provides simple quantitative parameters that relates to crop phenology (sowing date, flowering). In this study, we modelled various Gaussian profiles to time sequential MODIS enhanced vegetation index (EVI) images over winter crops in Queensland, Australia. Three simple Gaussian models were evaluated in their effectiveness to identify and classify various winter crop types and coverage at both pixel and regional scales across Queensland's main agricultural areas. Equal to or greater than 93% classification accuracies were obtained in determining crop acreage estimates at pixel scale for each of the Gaussian modelled approaches. Significant high to moderate correlations (log-linear transformation) were also obtained for determining total winter crop (R2 = 0.93) areas as well as specific crop acreage for wheat (R2 = 0.86) and barley (R2 = 0.83). Conversely, it was much more difficult to predict chickpea acreage (R2 = 0.26), mainly due to very large uncertainties in survey data. The quantitative approach utilised here further had additional benefits of characterising crop phenology in terms of length of growing season and providing regression diagnostics of how well the fitted profiles matched the EVI time series.
Yebra, M, Van Dijk, A, Leuning, R, Huete, A & Guerschman, JP 2013, 'Evaluation of optical remote sensing to estimate actual evapotranspiration and canopy conductance', Remote Sensing of Environment, vol. 129, pp. 250-261.View/Download from: Publisher's site
We compared estimates of actual evapotranspiration (ET) produced with six different vegetation measures derived from the MODerate resolution Imaging Spectroradiometer (MODIS) and three contrasting estimation approaches using measurements from eddy covariance flux towers at 16 FLUXNET sites located over six different land cover types. The aim was to assess optimal approaches in using optical remote sensing to estimate ET. The first two approaches directly regressed various MODIS vegetation indices (VIs) and products such as leaf area index (LAI) and fraction of photosynthetically active radiation (fPAR) with ET and evaporative fraction (EF). In the third approach, the PenmanâMonteith (PM) equation was inverted to obtain surface conductance (Gs), for dry plant canopies. The Gs values were then regressed against the MODIS data products and used to parameterize the PM equation for retrievals of ET. Jack-Knife cross-validation was used to evaluate the various regression models against observed ET. The PM-Gs approach provided the lowest root mean square error (RMSE), and highest determination coefficients (R2) across all sites, with an average RMSE= 38 W mâ2 and R2=0.72. Direct regressions of observed ET against the VIs resulted in an average RMSE= 60 W mâ2 and R2=0.22, while the EF regressions an average RMSE=42 W mâ2 and R2=0.64. The MODIS LAI and fPAR product produced the poorest estimates of ET (RMSE>44 W mâ2 and R2b0.6); while the VIs each performed best for some of the land cover types. The enhanced vegetation index (EVI) produced the best ET estimates for evergreen needleleaf forest (RMSE=28.4 W mâ2, R2=0.66). The normalized difference vegetation index (NDVI) best estimated ET in grassland (RMSE=23.8 W mâ2 and R2=0.68), cropland (RMSE=29.2 W mâ2 and R2=0.86) and woody savannas (RMSE=25.4 W mâ2 and R2=0.82), while the VI-based crop coefficient (Kc) yielded the best estimates for evergreen and deciduous broadleaf forests (RMSE=27 W mâ2 and R2=0.7 in both cases). U...
Zhang, Y, Moran, MS, Nearing, MA, Ponce Campos, GE, Huete, A, Buda, AR, Bosch, DD, Gunter, SA, Kitchen, SG, McNab, WH, Morgan, JA, McClaran, MP, Montoya, DS, Peters, DP & Starks, PJ 2013, 'Extreme precipitation patterns and reductions of terrestrial ecosystem production across biomes', Journal of Geophysical Research: Biogeosciences, vol. 118, no. 1, pp. 148-157.View/Download from: Publisher's site
Precipitation regimes are predicted to shift to more extreme patterns that are characterized by more heavy rainfall events and longer dry intervals, yet their ecological impacts on vegetation production remain uncertain across biomes in natural climatic conditions. This in situ study investigated the effects of these climatic conditions on aboveground net primary production (ANPP) by combining a greenness index from satellite measurements and climatic records during 2000â2009 from 11 long-term experimental sites in multiple biomes and climates. Results showed that extreme precipitation patterns decreased the sensitivity of ANPP to total annual precipitation (PT) at the regional and decadal scales, leading to decreased rain use efficiency (RUE; by 20% on average) across biomes. Relative decreases in ANPP were greatest for arid grassland (16%) and Mediterranean forest (20%) and less for mesic grassland and temperate forest (3%). The cooccurrence of heavy rainfall events and longer dry intervals caused greater water stress conditions that resulted in reduced vegetation production. A new generalized model was developed using a function of both PT and an index of precipitation extremes and improved predictions of the sensitivity of ANPP to changes in precipitation patterns. Our results suggest that extreme precipitation patterns have substantially negative effects on vegetation production across biomes and are as important as PT. With predictions of more extreme weather events, forecasts of ecosystem production should consider these nonlinear responses to altered extreme precipitation patterns associated with climate change.
Ma, X, Huete, A, Yu, Q, Restrepo Coupe, N, Davies, KP, Broich, M, Ratana, P, Beringer, J, Hutley, LB, Cleverly, J, Boulain, NP & Eamus, D 2013, 'Spatial patterns and temporal dynamics in savanna vegetation phenology across the North Australian Tropical Transect', Remote Sensing of Environment, vol. 139, no. 1, pp. 97-115.View/Download from: Publisher's site
The phenology of a landscape is a key parameter in climate and biogeochemical cycle models and its correct representation is central to the accurate simulation of carbon, water and energy exchange between the land surface and the atmosphere. Whereas biogeographic phenological patterns and shifts have received much attention in temperate ecosystems, much less is known about the phenology of savannas, despite their sensitivity to climate change and their coverage of approximately one eighth of the global land surface. Savannas are complex assemblages of multiple tree, shrub, and grass vegetation strata, each with variable phenological responses to seasonal climate and environmental variables. The objectives of this study were to investigate biogeographical and inter-annual patterns in savanna phenology along a 1100 km ecological rainfall gradient, known as North Australian Tropical Transect (NATT), encompassing humid coastal Eucalyptus forests and woodlands to xeric inland Acacia woodlands and shrublands. Key phenology transition dates (start, peak, end, and length of seasonal greening periods) were extracted from13 years (20002012) of Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) data using Singular Spectrum Analysis (SSA). Two distinct biogeographical patterns in phenology were observed, controlled by different climate systems. The northern (mesic) portion of the transect, from 12°S, to around 17.7°S, was influenced by the Inter-Tropical Convergence Zone (ITCZ) seasonal monsoon climate system, resulting in strong latitudinal shifts in phenology patterns, primarily associated with the functional response of the C4 grass layer.
Bargain, A, Robin, M, Le Men, E, Huete, A & Barille, L 2012, 'Spectral response of the seagrass Zostera noltii with different sediment backgrounds', Aquatic Botany, vol. 98, no. 1, pp. 45-56.View/Download from: Publisher's site
The efficiency of vegetation indices (VIs) to estimate the above-ground biomass of the seagrass species Zostera noltii Hornem. from remote sensing was tested experimentally on different substrata, since terrestrial vegetation studies have shown that VIs
Anderson, LO, Arageo, LE, Shimabukuro, YE, Almeida, S & Huete, A 2011, 'Fraction images for monitoring intra-annual phenology of different vegetation physiognomies in Amazonia', International journal of remote sensing, vol. 32, no. 2, pp. 387-408.View/Download from: Publisher's site
In this study we investigate the potential of fraction images derived from a linear spectral mixture model to detect vegetation phenology in Amazonia, and evaluate their relationships with the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices. Time series of MODIS 250-m data over three contrasting land cover types in the Amazon were used in conjunction with rainfall data, a land cover map and a forest inventory survey to support the interpretation of our findings. Each vegetation physiognomy was characterized by a particular intra-annual variability detected by a combination of the fraction images. Both vegetation and shade fractions were important to evaluate the seasonality of the open tropical forest (OTF). The association of these results with forest inventory data and the literature suggests that Enhanced Vegetation Index (EVI) and vegetation fraction images are sensitive to structural changes in the canopy of OTF. In cerrado grassland (CG) the phenology was better characterized by combined soil and vegetation fractions. Soybean (SB) areas were characterized by the highest ranges in the vegetation and soil fraction images. Vegetation fraction and vegetation indices for the OTF showed a significant positive relationship with EVI but not with Normalized Difference Vegetation Index (NDVI). Significant relationships for vegetation fraction and vegetation indices were also found for the CG and soybean areas. In contrast to vegetation index approaches to monitoring phenology, fraction images provide additional information that allows a more comprehensive exploration of the spectral and structural changes in vegetation formations.
Glenn, E, Doody, T, Guerschman, J, Huete, A, King, E, Mcvicar, T, Van, A, Van, T, Yebra, M & Zhang, Y 2011, 'Actual Evapotranspiration Estimation By Ground And Remote Sensing Methods: The Australian Experience', Hydrological Processes, vol. 25, no. 26, pp. 4103-4116.View/Download from: Publisher's site
On average, Australia is a dry continent with many competing uses for water. Hence, there is an urgent need to know actual evapotranspiration (ETa) patterns across wide areas of agricultural and natural ecosystems, as opposed to just point measurements of ETa. The Australian Government has tasked the science agencies with operationally developing monthly and annual estimates of ETa and other hydrological variables, and with forecasting water availability over periods of days to decades, as part of its national water assessment programme. To meet these needs, Australian researchers have become leaders in developing large-area methods for estimating ETa at regional and continental scales. Ground methods include meteorological models, eddy covariance towers, sap flow sensors and catchment water balance models. Remote sensing methods use thermal infrared, mid infrared and/or vegetation indices usually combined with meteorological data to estimate ETa. Ground and remote sensing ETa estimates are assimilated into the Australian Water Resource Assessment, which issues annual estimates of the state of the continental water balance for policy and planning purposes. The best ETa models are estimated to have an error or uncertainty of 10% to 20% in Australia. Developments in Australian ETa research over the past 20?years are reviewed, and sources of error and uncertainty in current methods and models are discussed.
Peng, D, Huete, A, Huang, J, Wang, F & Sun, H 2011, 'Detection and estimation of mixed paddy rice cropping patterns with MODIS data', Journal of Applied Earth Observation and Geoinformation, vol. 13, no. 1, pp. 13-23.View/Download from: Publisher's site
In this paper, we developed a more sophisticated method for detection and estimation of mixed paddy rice agriculture from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. Previous research demonstrated that MODIS data can be used to map paddy rice fields and to distinguish rice from other crops at large, continental scales with combined Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI) analysis during the flooding and rice transplanting stage. Our approach improves upon this methodology by incorporating mixed rice cropping patterns that include single-season rice crops, early-season rice, and late-season rice cropping systems. A variable EVI/LSWI threshold function, calibrated to more local rice management practices, was used to recognize rice fields at the flooding stage. We developed our approach with MODIS data in Hunan Province, China, an area with significant flooded paddy rice agriculture and mixed rice cropping patterns. We further mapped the aerial coverage and distribution of early, late, and single paddy rice crops for several years from 2000 to 2007 in order to quantify temporal trends in rice crop coverage, growth and management systems. Our results were validated with finer resolution (2.5 m) Satellite Pour l'Observation de la Terre 5 High Resolution Geometric (SPOT 5 HRG) data, land-use data at the scale of 1/10,000 and with county-level rice area statistical data. The results showed that all three paddy rice crop patterns could be discriminated and their spatial distribution quantified. We show the area of single crop rice to have increased annually and almost doubling in extent from 2000 to 2007, with simultaneous, but unique declines in the extent of early and late paddy rice. These results were significantly positive correlated and consistent with agricultural statistical data at the county level (P<0.01).
Yang, X, Huang, J, Wu, Y, Wang, J, Wang, P, Wang, X & Huete, A 2011, 'Estimating biophysical parameters of rice with remote sensing data using support vector machines', Science China Life Sciences, vol. 54, no. 3, pp. 272-281.View/Download from: Publisher's site
Hyperspectral reflectance (350â2500 nm) measurements were made over two experimental rice fields containing two cultivars treated with three levels of nitrogen application. Four different transformations of the reflectance data were analyzed for their capability to predict rice biophysical parameters, comprising leaf area index (LAI; m2 green leaf area mâ2 soil) and green leaf chlorophyll density (GLCD; mg chlorophyll mâ2 soil), using stepwise multiple regression (SMR) models and support vector machines (SVMs). Four transformations of the rice canopy data were made, comprising reflectances (R), first-order derivative reflectances (D1), second-order derivative reflectances (D2), and logarithm transformation of reflectances (LOG). The polynomial kernel (POLY) of the SVM using R was the best model to predict rice LAI, with a root mean square error (RMSE) of 1.0496 LAI units. The analysis of variance kernel of SVM using LOG was the best model to predict rice GLCD, with an RMSE of 523.0741 mg mâ2. The SVM approach was not only superior to SMR models for predicting the rice biophysical parameters, but also provided a useful exploratory and predictive tool for analyzing different transformations of reflectance data.
Ferreira, NC, Ferreira, LG & Huete, A 2010, 'Assessing the response of the MODIS vegetation indices to landscape disturbance in the forested areas of the legal Brazilian Amazon', International journal of remote sensing, vol. 31, no. 3, pp. 745-759.View/Download from: Publisher's site
In this study we assessed the impacts of forest fragmentation on the Amazon landscape using remote sensing techniques. Landscape disturbance, obtained for an area of approximately 3.5 times 106 km2 through simple spatial metrics (i.e. number of fragments, mean fragment area and border size) and principal component transformation were then compared to the MODIS (Moderate Resolution Imaging Spectroradiometer) NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) seasonal responses. As expected, higher disturbance values prevail in the southern border of the Amazon, near the intensively converted deforestation arc, and close to the major roads. NDVI seasonal responses more closely follow human-induced patterns, i.e. forest remnants from areas more intensively converted were associated with higher NDVI seasonal values. The significant correlation between NDVI seasonal responses and landscape disturbances were corroborated through analysis of geographically weighted regression (GWR) parameters and predictions. On the other hand, EVI seasonal responses were more complex with significant variations found over intact, less fragmented forest patches, thus restricting its utility to assess landscape disturbance. Although further research is needed, our results suggest that the degree of fragmentation of the forest remnants can be remotely sensed with MODIS vegetation indices. Thus, it may become possible to upscale field-based data on overall canopy condition and fragmentation status for basin-wide extrapolations.
Glenn, E, Nagler, P & Huete, A 2010, 'Vegetation Index methods for estimating evapotranspiration by remote sensing', Surveys in Geophysics, vol. 31, no. 6, pp. 531-555.View/Download from: Publisher's site
Evapotranspiration (ET) is the largest term after precipitation in terrestrial water budgets. Accurate estimates of ET are needed for numerous agricultural and natural resource management tasks and to project changes in hydrological cycles due to potential climate change. We explore recent methods that combine vegetation indices (VI) from satellites with ground measurements of actual ET (ETa) and meteorological data to project ETa over a wide range of biome types and scales of measurement, from local to global estimates. The majority of these use time-series imagery from the Moderate Resolution Imaging Spectrometer on the Terra satellite to project ET over seasons and years. The review explores the theoretical basis for the methods, the types of ancillary data needed, and their accuracy and limitations. Coefficients of determination between modeled ETa and measured ETa are in the range of 0.450.95, and root mean square errors are in the range of 1030% of mean ETa values across biomes, similar to methods that use thermal infrared bands to estimate ETa and within the range of accuracy of the ground measurements by which they are calibrated or validated.
Jenerette, DG, Scott, RL & Huete, A 2010, 'Functional differences between summer and winter season rain assessed with MODIS-derived phenology in a semi-arid region', Journal of Vegetation Science, vol. 21, no. 1, pp. 16-30.View/Download from: Publisher's site
Questions: We asked several linked questions about phenology and precipitation relationships at local, landscape, and regional spatial scales within individual seasons, between seasons, and between year temporal scales. (1) How do winter and summer phenological patterns vary in response to total seasonal rainfall? (2) How are phenological rates affected by the previous season rainfall? (3) How does phenological variability differ at landscape and regional spatial scales and at season and inter-annual temporal scales? Location: Southern Arizona, USA. Methods: We compared satellite-derived phenological variation between 38 distinct 625-km2 landscapes distributed in the northern Sonoran Desert region from 2000 to 2007. Regression analyses were used to identify relationships between landscape phenology dynamics in response to precipitation variability across multiple spatial and temporal scales. Results: While both summer and winter seasons show increases of peak greenness and peak growth with more precipitation, the timing of peak growth was advanced with more precipitation in winter, while the timing of peak greenness was advanced with more precipitation in summer. Surprisingly, summer maximum growth was negatively affected by winter precipitation. The spatial variations between summer and winter phenology were similar in magnitude and response. Larger-scale spatial and temporal variation showed strong differences in precipitation patterns; however the magnitudes of phenological spatial variability in these two seasons were similar. Conclusions: Vegetation patterns were clearly coupled to precipitation variability, with distinct responses at alternative spatial and temporal scales. Disaggregating vegetation into phenological variation, spanning value, timing, and integrated components revealed substantial complexity in precipitation-phenological relationships.
Jiang, Z & Huete, A 2010, 'Linearization of NDVI based on its relationship with vegetation fraction', Photogrammetry Engineering & Remote Sensing, vol. 76, no. 8, pp. 545-561.
The Normalized Difference Vegetation Index (NDVI) is widely used for global monitoring of land surface vegetation dynamics from space. However, it is well documented that the NDVI approaches saturation asymptotically over highly vegetated areas. In this study, a linearized NDVI (LNDVI) is derived by introducing a linearity-adjustment factor, beta, into the NDVI equation to improve the linearity of the relationship with vegetation fraction and mitigate the saturation problem encountered by NDVI. The linearity of the LNDVI is demonstrated using a ground-observed data set and a model-simulated data set. A functional relationship and consistence of LNDVI with other NDVI adaptations are found, providing independent justification of the value of the NDVI adaptations. Due to its improved linearity with vegetation fraction, this index would provide more accurate monitoring of vegetation dynamics and estimation of biophysical parameters. The LNDVI can be derived from historical NDVI datasets directly without knowledge of input reflectances.
Jiang, Z & Huete, AR 2010, 'Linearization of NDVI Based on its Relationship with Vegetation Fraction', PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, vol. 76, no. 8, pp. 965-975.View/Download from: Publisher's site
Kim, Y, Huete, AR, Miura, T & Jiang, Z 2010, 'Spectral compatibility of vegetation indices across sensors: band decomposition analysis with Hyperion data', JOURNAL OF APPLIED REMOTE SENSING, vol. 4.View/Download from: Publisher's site
Peng, D, Huang, J, Huete, A, Yang, T, Gao, P, Chen, YC, Chen, H, Li, J & Liu, ZY 2010, 'Spatial and seasonal characterization of net primary productivity and climate variables in southeastern China using MODIS data', Journal of Zhejiang University Science, vol. 11, no. 4, pp. 275-285.View/Download from: Publisher's site
We developed a sophisticated method to depict the spatial and seasonal characterization of net primary productivity (NPP) and climate variables. The role of climate variability in the seasonal variation of NPP exerts delayed and continuous effects. This study expands on this by mapping the seasonal characterization of NPP and climate variables from space using geographic information system (GIS) technology at the pixel level. Our approach was developed in southeastern China using moderate-resolution imaging spectroradiometer (MODIS) data. The results showed that air temperature, precipitation and sunshine percentage contributed significantly to seasonal variation of NPP. In the northern portion of the study area, a significant positive 32-d lagged correlation was observed between seasonal variation of NPP and climate (P<0.01), and the influences of changing climate on NPP lasted for 48 d or 64 d. In central southeastern China, NPP showed 16-d, 48-d, and 96-d lagged correlation with air temperature, precipitation, and sunshine percentage, respectively (P<0.01); the influences of air temperature and precipitation on NPP lasted for 48 d or 64 d, while sunshine influence on NPP only persisted for 16 d.
Yoshioka, H, Miura, T, Dematte, JA, Batchily, K & Huete, A 2010, 'Soil line influences on two-band vegetation indices and vegetation isolines: A numerical study', Remote Sensing, vol. 2, no. 2, pp. 545-561.View/Download from: Publisher's site
Influences of soil line variations on two-band vegetation indices (VIs) and their vegetation isolines in red and near-infrared (NIR) reflectance space are investigated based on recently derived relationships between the relative variations of VIs with variations of the soil line parameters in the accompanying paper by Yoshioka et al. . The soil line influences are first demonstrated numerically in terms of variations of vegetation isolines and VI values along with the isolines. A hypothetical case is then analyzed by assuming the discrepancies between the general and regional soil lines for a Southern Brazil area reported elsewhere. The results indicate the validity of our analytical approach for the evaluation of soil line influences and the applicability for adjustment of VI errors using external data sources of soil reflectance spectra.
Dematte, JA, Huete, A, Ferreira, LG, Nanni, MR & Fiorio, PR 2009, 'Methodology for bare soil detection and discrimination by Landsat TM image', The Open Remote Sensing Journal, vol. 2, no. 1, pp. 24-35.
The objective of this work was to develop and test a remote sensing technique to determine bare soils with pixel information from satellite images. The methodology was tested and improved on a 2,805 km2 area located in the state of São Paulo, Brazil. The pixel data from a Landsat-5/TM image was transformed into reflectances. 294 pixels were evaluated by five factors simultaneously and included the following: color composition image; vegetation index; soil brightness information (soil line concept), and a comparison between spectral curve of the pixel with spectral patterns of soils. A validation procedure was based on the discriminate analysis for the real soil related with each pixel. For this, a soil map was overlaid onto the image, and the pixels were related to its respective soil class. Soil brightness variations were readily observed in the spectral curves and in red-NIR features and corresponded to differences in texture and particle size as well in iron and organic matter content. Although qualitative, the observation of color composition was useful for pixel identification. The soil line concept was very useful as it presented a high R2 coefficient (0.90). Comparison between ground level soil spectral curves with satellite information could assist on the evaluation of the real format of the curves. Discriminate analysis indicated a 99.3% correct classification of the soils. Field work validation indicated 90% significance. The present method could help researchers acquire valuable information (i.e., soil attributes quantification), when soil data must be acquired from satellite images.
Fisher, JB, Mahli, Y, Bonal, D, da Rocha, HR, Araujo, AC, Gamo, M, Goulden, ML, Hirano, T, Huete, A, Kondo, H, Kumagai, T, Loescher, HW, Miller, SD, Nobre, AD, Nouvellon, Y, Oberbauer, SF, Panuthai, S, Roupsard, O, Saleska, SR, Tanaka, K, Tanaka, N, Tu, KP & von Randow, C 2009, 'The land-atmosphere water flux in the tropics', Global Change Biology, vol. 15, no. 11, pp. 2694-2714.View/Download from: Publisher's site
Tropical vegetation is a major source of global land surface evapotranspiration, and can thus play a major role in global hydrological cycles and global atmospheric circulation. Accurate prediction of tropical evapotranspiration is critical to our understanding of these processes under changing climate. We examined the controls on evapotranspiration in tropical vegetation at 21 pan-tropical eddy covariance sites, conducted a comprehensive and systematic evaluation of 13 evapotranspiration models at these sites, and assessed the ability to scale up model estimates of evapotranspiration for the test region of Amazonia. Net radiation was the strongest determinant of evapotranspiration (mean evaporative fraction was 0.72) and explained 87% of the variance in monthly evapotranspiration across the sites. Vapor pressure deficit was the strongest residual predictor (14%), followed by normalized difference vegetation index (9%), precipitation (6%) and wind speed (4%). The radiation-based evapotranspiration models performed best overall for three reasons: (1) the vegetation was largely decoupled from atmospheric turbulent transfer (calculated from O decoupling factor), especially at the wetter sites; (2) the resistance-based models were hindered by difficulty in consistently characterizing canopy (and stomatal) resistance in the highly diverse vegetation; (3) the temperature-based models inadequately captured the variability in tropical evapotranspiration. We evaluated the potential to predict regional evapotranspiration for one test region: Amazonia. We estimated an Amazonia-wide evapotranspiration of 1370 mm yr-1, but this value is dependent on assumptions about energy balance closure for the tropical eddy covariance sites; a lower value (1096 mm yr-1) is considered in discussion on the use of flux data to validate and interpolate models.
In this study, the performances and accuracies of three methods for converting airborne hyperspectral spectrometer data to reflectance factors were characterized and compared. The reflectance mode (RM) method, which calibrates a spectrometer against a white reference panel prior to mounting on an aircraft, resulted in spectral reflectance retrievals that were biased and distorted. The magnitudes of these bias errors and distortions varied significantly, depending on time of day and length of the flight campaign. The linear-interpolation (LI) method, which converts airborne spectrometer data by taking a ratio of linearly-interpolated reference values from the preflight and postflight reference panel readings, resulted in precise, but inaccurate reflectance retrievals. These reflectance spectra were not distorted, but were subject to bias errors of varying magnitudes dependent on the flight duration length. The continuous panel (CP) method uses a multi-band radiometer to obtain continuous measurements over a reference panel throughout the flight campaign, in order to adjust the magnitudes of the linear-interpolated reference values from the preflight and post-flight reference panel readings. Airborne hyperspectral reflectance retrievals obtained using this method were found to be the most accurate and reliable reflectance calibration method.
Potter, C, Klooster, S, Huete, A, Genovese, V, Bustamante, M, Guimaraes, FL, Cosme, DOJR & Zepp, R 2009, 'Terrestrial carbon sinks in the Brazilian Amazon and Cerrado region predicted from MODIS satellite data and ecosystem modeling', Biogeosciences, vol. 6, pp. 937-945.View/Download from: Publisher's site
A simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado re- gions over the period 2000â2004. Net ecosystem production (NEP) flux for atmospheric CO2 in the region for these years was estimated. Consistently high carbon sink fluxes in terrestrial ecosystems on a yearly basis were found in the western portions of the states of Acre and RondËonia and the northern portions of the state of Par Â´ a. These areas were not significantly impacted by the 2002â2003 El NiËno event in terms of net annual carbon gains. Areas of the region that show periodically high carbon source fluxes from terrestrial ecosystems to the atmosphere on yearly basis were found throughout the state of MaranhËao and the southern portions of the state of Amazonas. As demonstrated though tower site comparisons, NEP modeled with monthly MODIS Enhanced Vegetation Index (EVI) inputs closely resembles the mea sured seasonal carbon fluxes at the LBA Tapajos tower site. Modeling results suggest that the capacity for use of MODIS Enhanced Vegetation Index (EVI) data to predict seasonal uptake rates of CO2 in Amazon forests and Cerrado woodlands is strong.
Sun, H, Huang, J, Huete, A, Peng, D & Zhang, F 2009, 'Mapping paddy rice in China with multi-date MODIS data', Zhejiang University Journal (Science A): applied physics and engineering, vol. 10, no. 10, pp. 1509-1522.View/Download from: Publisher's site
The objective of this study was to obtain spatial distribution maps of paddy rice fields using multi-date moderate-resolution imaging spectroradiometer (MODIS) data in China. Paddy rice fields were extracted by identifying the unique characteristic of high soil moisture in the flooding and transplanting period with improved algorithms based on rice growth calendar regionalization. The characteristic could be reflected by the enhanced vegetation index (EVI) and the land surface water index (LSWI) derived from MODIS sensor data. Algorithms for single, early, and late rice identification were obtained from selected typical test sites. The algorithms could not only separate early rice and late rice planted in the same fields, but also reduce the uncertainties. The areal accuracy of the MODIS-derived results was validated by comparison with agricultural statistics, and the spatial matching was examined by ETM+ (enhanced thematic mapper plus) images in a test region. Major factors that might cause errors, such as the coarse spatial resolution and noises in the MODIS data, were discussed. Although not suitable for monitoring the inter-annual variations due to some inevitable factors, the MODIS-derived results were useful for obtaining spatial distribution maps of paddy rice on a large scale, and they might provide reference for further studies
Yoshioka, H, Miura, T, Dematte, JA, Batchily, K & Huete, A 2009, 'Derivation of soil line influence on two-band vegetation indices and vegetation isolines', Remote Sensing, vol. 1, no. 4, pp. 842-857.View/Download from: Publisher's site
This paper introduces derivations of soil line influences on two-band vegetation indices (VIs) and vegetation isolines in the red and near infra-red reflectance space. Soil line variations are described as changes in the soil line parameters (slope and offset) and the red reflectance of the soil surface. A general form of a VI model equation written as a ratio of two linear functions (e.g., NDVI and SAVI) was assumed. It was found that relative VI variations can be approximated by a linear combination of the three soil parameters. The derived expressions imply the possibility of estimating and correcting for soil-induced bias errors in VIs and their derived biophysical parameters, caused by the assumption of a general soil line, through the use of external data sources such as regional soil maps.
Glenn, E, Huete, A, Nagler, PL & Nelson, SG 2008, 'Relationship Between Remotely-sensed Vegetation Indices, Canopy Attributes and Plant Physiological Processes: What Vegetation Indices Can and Cannot Tell Us About the Landscape', Sensors, vol. 8, no. 4, pp. 2136-2160.View/Download from: Publisher's site
Vegetation indices (VIs) are among the oldest tools in remote sensing studies. Although many variations exist, most of them ratio the reflection of light in the red and NIR sections of the spectrum to separate the landscape into water, soil, and vegetation. Theoretical analyses and field studies have shown that VIs are near-linearly related to photosynthetically active radiation absorbed by a plant canopy, and therefore to light-dependent physiological processes, such as photosynthesis, occurring in the upper canopy. Practical studies have used time-series VIs to measure primary production and evapotranspiration, but these are limited in accuracy to that of the data used in ground truthing or calibrating the models used. VIs are also used to estimate a wide variety of other canopy attributes that are used in Soil-Vegetation-Atmosphere Transfer (SVAT), Surface Energy Balance (SEB), and Global Climate Models (GCM). These attributes include fractional vegetation cover, leaf area index, roughness lengths for turbulent transfer, emissivity and albedo. However, VIs often exhibit only moderate, non-linear relationships to these canopy attributes, compromising the accuracy of the models. We use case studies to illustrate the use and misuse of VIs, and argue for using VIs most simply as a measurement of canopy light absorption rather than as a surrogate for detailed features of canopy architecture. Used this way, VIs are compatible with "Big Leaf" SVAT and GCMs that assume that canopy carbon and moisture fluxes have the same relative response to the environment as any single leaf, simplifying the task of modeling complex landscapes.
Huete, A, Restrepo Coupe, N, Ratana, P, Didan, K, Saleska, SR, Ichii, K, Panuthai, S & Gamo, M 2008, 'Multiple site tower flux and remote sensing comparisons of tropical forest dynamics in Monsoon Asia', Agricultural and Forest Meteorology, vol. 148, no. 5, pp. 748-760.View/Download from: Publisher's site
The spatial and temporal dynamics of tropical forest functioning are poorly understood, partly attributed to a weak seasonality and high tree species diversity at the landscape scale. Recent neotropical rainforest studies with local tower flux measurements have revealed strong seasonal carbon fluxes that follow the availability of sunlight in intact forests, while in areas of forest disturbance, carbon fluxes more closely tracked seasonal water availability. These studies also showed a strong seasonal correspondence of satellite measures of greenness, using the Enhanced Vegetation Index (EVI) with ecosystem carbon fluxes in both intact and disturbed forests, which may enable larger scale extension of tower flux measurements. In this study, we investigated the seasonal patterns and relationships of local site tower flux measures of gross primary productivity (Pg) with independent Moderate Resolution Imaging Spectroradiometer (MODIS) satellite greenness measures across three Monsoon Asia tropical forest types, encompassing drought-deciduous, dry evergreen, and humid evergreen secondary tropical forests. In contrast to neotropical forests, the tropical forests of Monsoon Asia are more extensively degraded and heterogeneous due to intense land use pressures, and therefore, may exhibit unique seasonal patterns of ecosystem fluxes that are more likely water-limited and drought-susceptible.
Jiang, Z, Huete, A, Didan, K & Miura, T 2008, 'Development of a two-band enhanced vegetation index without a blue band', Remote Sensing Of Environment, vol. 112, no. 10, pp. 3833-3845.View/Download from: Publisher's site
The enhanced vegetation index (EVI) was developed as a standard satellite vegetation product for the Terra and Aqua Moderate Resolution Imaging Spectroradiometers (MODIS). EVI provides improved sensitivity in high biomass regions while minimizing soil and atmosphere influences, however, is limited to sensor systems designed with a blue band, in addition to the red and near-infrared bands, making it difficult to generate long-term EVI time series as the normalized difference vegetation index (NDVI) counterpart. The purpose of this study is to develop and evaluate a 2-band EVI (EVI2), without a blue band, which has the best similarity with the 3-band EVI, particularly when atmospheric effects are insignificant and data quality is good. A linearity-adjustment factor ? is proposed and coupled with the soil-adjustment factor L used in the soil-adjusted vegetation index (SAVI) to develop EVI2. A global land cover dataset of Terra MODIS data extracted over land community validation and FLUXNET test sites is used to develop the optimal parameter (L, ? and G) values in EVI2 equation and achieve the best similarity between EVI and EVI2. The similarity between the two indices is evaluated and demonstrated with temporal profiles of vegetation dynamics at local and global scales. Our results demonstrate that the differences between EVI and EVI2 are insignificant (within ± 0.02) over a very large sample of snow/ice-free land cover types, phenologies, and scales when atmospheric influences are insignificant, enabling EVI2 as an acceptable and accurate substitute of EVI. EVI2 can be used for sensors without a blue band, such as the Advanced Very High Resolution Radiometer (AVHRR), and may reveal different vegetation dynamics in comparison with the current AVHRR NDVI dataset. However, cross-sensor continuity relationships for EVI2 remain to be studied.
Paz-Pellat, F, Bolanos-Gonzalez, M, Palacios-Velez, E, Palacios-Sanchez, LA, Martinez-Menes, M & Huete, A 2008, 'OPTIMIZATION OF THE SPECTRAL VEGETATION INDEX NDVIcp', AGROCIENCIA, vol. 42, no. 8, pp. 925-937.
Bolanos-Gonzalez, MA, Paz-Pellat, F, Palacios-Velez, E, Mejia-Saenz, E & Huete, A 2007, 'Modelation of the sun-sensor geometry effects in the vegetation reflectance', AGROCIENCIA, vol. 41, no. 5, pp. 527-537.
Ferreira, NC, Ferreira, LG, Huete, A & Ferreira, ME 2007, 'An operational deforestation mapping system using MODIS data and spatial context analysis', International journal of remote sensing, vol. 28, no. 1, pp. 47-62.View/Download from: Publisher's site
The Brazilian Amazon has the world's highest absolute rate of forest loss, currently averaging nearly 2 million hectares per year. In this study, we present a near-real-time automated deforestation mapping system for the Brazilian Amazon based on the analysis of spatial context information and MODIS Vegetation Index products and implemented on an ArcGIS 9.0 platform. This system, already validated and operational, was developed as part of the Integrated Warning Deforestation System for the Amazon (SIAD), an initiative of the Brazilian government within the scope of the Amazon Protection System (SIPAM), which also comprises: (1) a spatial information module, aimed at the assessment of the causes and impacts of the deforested areas; (2) a prediction module, indicative of deforestation trends; and (3) a data and information gateway based on map server technology.
Glenn, E, Huete, A, Nagler, PL, Hirschboeck, KK & Brown, P 2007, 'Integrating Remote Sensing and Ground Methods to Estimate Evapotranspiration', Critical Reviews in Plant Sciences, vol. 26, no. 3, pp. 139-168.View/Download from: Publisher's site
Evapotranspiraton (ET) is the second largest term in the terrestrial water budget after precipitation, and ET is expected to increase with global warming. ET studies are relevant to the plant sciences because over 80% of terrestrial ET is due to transpiration by plants. Remote sensing is the only feasible means for projecting ET over large landscape units. In the past decade or so, new ground and remote sensing tools have dramatically increased our ability to measure ET at the plot scale and to scale it over larger regions. Moisture flux towers and micrometeorological stations have been deployed in numerous natural and agricultural biomes and provide continuous measurements of actual ET or potential ET with an accuracy or uncertainty of 10-30%. These measurements can be scaled to larger landscape units using remotely-sensed vegetation indices (VIs), Land Surface Temperature (LST), and other satellite data. Two types of methods have been developed. Empirical methods use time-series VIs and micrometeorological data to project ET measured on the ground to larger landscape units. Physically-based methods use remote sensing data to determine the components of the surface energy balance, including latent heat flux, which determines ET. Errors in predicting ET by both types of methods are within the error bounds of the flux towers by which they are calibrated or validated. However, the error bounds need to be reduced to 10% or less for applications that require precise wide-area ET estimates. The high fidelity between ET and VIs over agricultural fields and natural ecosystems where precise ground estimates of ET are available suggests that this might be an achievable goal if ground methods for measuring ET continue to improve.
Ichii, K, Hashimoto, H, White, MA, Pottors, C, Hutyra, LR, Huete, A, Myneni, RB & Nemani, RR 2007, 'Constraining rooting depths in tropical rainforests using satellite data and ecosystem modeling for accurate simulation of gross primary production seasonality', Global Change Biology, vol. 13, no. 1, pp. 67-77.View/Download from: Publisher's site
Accurate parameterization of rooting depth is difficult but important for capturing the spatio-temporal dynamics of carbon, water and energy cycles in tropical forests. In this study, we adopted a new approach to constrain rooting depth in terrestrial ecosystem models over the Amazon using satellite data [moderate resolution imaging spectroradiometer (MODIS) enhanced vegetation index (EVI)] and Biome-BGC terrestrial ecosystem model. We simulated seasonal variations in gross primary production (GPP) using different rooting depths (1, 3, 5, and 10 m) at point and spatial scales to investigate how rooting depth affects modeled seasonal GPP variations and to determine which rooting depth simulates GPP consistent with satellite-based observations. First, we confirmed that rooting depth strongly controls modeled GPP seasonal variations and that only deep rooting systems can successfully track flux-based GPP seasonality at the Tapajos km67 flux site. Second, spatial analysis showed that the model can reproduce the seasonal variations in satellite-based EVI seasonality, however, with required rooting depths strongly dependent on precipitation and the dry season length. For example, a shallow rooting depth (13 m) is sufficient in regions with a short dry season (e.g. 02 months), and deeper roots are required in regions with a longer dry season (e.g. 35 and 510 m for the regions with 34 and 56 months dry season, respectively). Our analysis suggests that setting of proper rooting depths is important to simulating GPP seasonality in tropical forests, and the use of satellite data can help to constrain the spatial variability of rooting depth.
Myneni, RB, Yang, W, Nemani, RR, Huete, A, Dickinson, RE, Knyazikhin, Y, Didan, K, Fu, R, Negron Juarez, RI, Saatchi, SS, Hashimoto, H, Ichii, K, Shabanov, NV, Tan, B, Ratana, P, Privette, JL, Morisette, JT, Vermote, EF, Roy, DP, Wolfe, RE, Friedl, MA, Running, SW, Votava, P, El-Saleous, N, Devadiga, S, Su, Y & Salomonson, VV 2007, 'Large seasonal swings in leaf area of Amazon rainforests', Proceedings of the National Academy of Sciences, vol. 104, no. 12, pp. 4820-4823.
Despite early speculation to the contrary, all tropical forests studied to date display seasonal variations in the presence of new leaves, ?owers, and fruits. Past studies were focused on the timing of phenological events and their cues but not on the accompanying changes in leaf area that regulate vegetationatmosphere exchanges of energy, momentum, and mass. Here we report, from analysis of 5 years of recent satellite data, seasonal swings in green leaf area of 25% in a majority of the Amazon rainforests. This seasonal cycle is timed to the seasonality of solar radiation in a manner that is suggestive of anticipatory and opportunistic patterns of net leaf ?ushing during the early to mid part of the light-rich dry season and net leaf abscission during the cloudy wet season. These seasonal swings in leaf area may be critical to initiation of the transition from dry to wet season, seasonal carbon balance between photosynthetic gains and respiratory losses, and litterfall nutrient cycling in moist tropical forests
Nagler, PL, Glenn, E, Kim, H, Emmerich, W, Scott, RL, Huxman, TE & Huete, A 2007, 'Relationship between evapotranspiration and precipitation pulses in a semiarid rangeland estimated by moisture flux towers and MODIS vegetation indices', Journal Of Arid Environments, vol. 70, no. 3, pp. 443-462.View/Download from: Publisher's site
We used moisture Bowen ratio flux tower data and the enhanced vegetation index (EVI) from the moderate resolution imaging spectrometer (MODIS) on the Terra satellite to measure and scale evapotranspiration (ET) over sparsely vegetated grassland and shrubland sites in a semiarid watershed in southeastern Arizona from 2000 to 2004. The grassland tower site had higher mean annual ET (336 mm yr-1) than the shrubland tower site (266 mm yr-1) (P<0.001). ET measured at the individual tower sites was strongly correlated with EVI (r = 0.80-0.94). ET was moderately correlated with precipitation (P), and only weakly correlated with net radiation or air temperature. The strong correlation between ET and EVI, as opposed to the moderate correlation with rainfall, suggests that transpiration (T) is the dominant process controlling ET at these sites.
Paz-Pellat, F, Palacios-Velez, E, Bolanos-Gonzalez, M, Palacios-Sanchez, LA, Martinez-Menes, M, Mejia-Saenz, E & Huete, A 2007, 'Design of a vegetation spectral index: NDVIcp', AGROCIENCIA, vol. 41, no. 5, pp. 539-554.
Potter, C, Klooster, S, Huete, A & Genovese, V 2007, 'Terrestrial Carbon Sinks for the United States Predicted from MODIS Satellite Data and Ecosystem Modeling', Earth Interactions, vol. 11, no. 13, pp. 1-21.
A simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of the conterminous United States over the period 200104. Predicted net ecosystem production (NEP) flux for atmospheric CO2 in the United States was estimated as annual net sink of about +0.2 Pg C in 2004. Regional climate patterns were reflected in the predicted annual NEP flux from the model, which showed extensive carbon sinks in ecosystems of the southern and eastern regions in 200304, and major carbon source fluxes from ecosystems in the Rocky Mountain and Pacific Northwest regions in 200304. As demonstrated through tower site comparisons, net primary production (NPP) modeled with monthly MODIS enhanced vegetation index (EVI) inputs closely resembles both the measured high- and low-season carbon fluxes. Modeling results suggest that the capacity of the NASA Carnegie Ames Stanford Approach (CASA) model to use 8-km resolution MODIS EVI data to predict peak growing season uptake rates of CO2 in irrigated croplands and moist temperate forests is strong.
Coupled climate-carbon cycle models suggest that Amazon forests are vulnerable to both long- and short-term droughts, but satellite observations showed a large-scale photosynthetic green-up in intact evergreen forests of the Amazon in response to a short, intense drought in 2005. These findings suggest that Amazon forests, although threatened by human-caused deforestation and fire and possibly by more severe long-term droughts, may be more resilient to climate changes than ecosystem models assume.
Yang, F, Ichii, K, White, MA, Hashimoto, H, Michaelis, AR, Votava, P, Zhu, A, Huete, A, Running, SW & Nemani, RR 2007, 'Developing a continental-scale measure of gross primary production by combining MODIS and AmeriFlux data through Support Vector Machine approach', Remote Sensing Of Environment, vol. 110, no. 1, pp. 109-122.View/Download from: Publisher's site
Remote sensing is a potentially powerful technology with which to extrapolate eddy covariance-based gross primary production (GPP) to continental scales. In support of this concept, we used meteorological and flux data from the AmeriFlux network and Support Vector Machine (SVM), an inductive machine learning technique, to develop and apply a predictive GPP model for the conterminous U.S. In the following four-step process, we first trained the SVM to predict flux-based GPP from 33 AmeriFlux sites between 2000 and 2003 using three remotely-sensed variables (land surface temperature, enhanced vegetation index (EVI), and land cover) and one ground-measured variable (incident shortwave radiation). Second, we evaluated model performance by predicting GPP for 24 available AmeriFlux sites in 2004. In this independent evaluation, the SVM predicted GPP with a root mean squared error (RMSE) of 1.87 gC/m2/day and an R2 of 0.71. Based on annual total GPP at 15 AmeriFlux sites for which the number of 8-day averages in 2004 was no less than 67% (30 out of a possible 45), annual SVM GPP prediction error was 32.1% for non-forest ecosystems and 22.2% for forest ecosystems, while the standard Moderate Resolution Imaging Spectroradiometer GPP product (MOD17) had an error of 50.3% for non-forest ecosystems and 21.5% for forest ecosystems, suggesting that the regionally tuned SVM performed better than the standard global MOD17 GPP for non-forest ecosystems but had similar performance for forest ecosystems
Barbosa, HA, Huete, A & Baethgen, WE 2006, 'A 20-year study of NDVI variability over the Northeast Region of Brazil', Journal Of Arid Environments, vol. 67, no. 2, pp. 288-307.View/Download from: Publisher's site
The natural ecosystems of the Northeast Region of Brazil (NEB) have experienced persistent drought episodes and environmental degradation during the past two decades. In this study, we examined the spatial heterogeneity and temporal dynamics of the NEB using a 20-year time series of Normalized Difference Vegetation Index (NDVI) observations, derived from the National Oceanographic and Atmospheric Administration (NOAA)-Advanced Very High Resolution Radiometer (AVHRR) instrument. A set of 12 000 spatially distributed NDVI values was analysed to investigate significant deviations from the mean-monthly values of the base period (19822001) in the study area. Various statistical analyses involving minimum, mean and maximum values, coefficient of variation (CV), standardized anomalies (Z-scores), and 36-month running mean were applied to monthly NDVI values to identify spatial and temporal variations in vegetation dynamics. We found strong seasonal oscillations in the vegetation-growing season (FebruaryMay) over the NEB study area, with maximum NDVI observed in AprilMay and seasonal variations, expressed by the CV, ranging from 14% to 32%. In addition, a consistent upward trend in vegetation greenness occurred over the period 19841990, and was strongly reversed in the subsequent period 19911998. These upward and downward trends in vegetation greenness followed an inter-annual oscillation of not, vert, similar78 years. We also found that dry season peak (September) latitudinal variations in NDVI were 2025% greater in 19911999 than 19821990 across the study region. The results of this study suggest that patterns in NEB vegetation variability were a result of the impact of enhanced aridity occurring over the last decade of the 20th century.
Cheng, Y, Gamon, JA, Fuentes, DA, Mao, Z, Sims, DA, Qiu, H, Claudio, H, Huete, A & Rahman, AF 2006, 'A multi-scale analysis of dynamic optical signals in a Southern California chaparral ecosystem: A comparison of field, AVIRIS and MODIS data', Remote Sensing Of Environment, vol. 103, no. 3, pp. 369-378.View/Download from: Publisher's site
Using field data, Airborne Visible Infrared Imaging Spectrometer (AVIRIS) imagery, and Moderate-Resolution Imaging SpectroRadiometer (MODIS) data, a multi-scale analysis of ecosystem optical properties was performed for Sky Oaks, a Southern California chaparral ecosystem in the SpecNet and FLUXNET networks. The study covered a four-year period (2000-2004), which included a severe drought in 2002 and a subsequent wildfire in July 2003, leading to extreme perturbation in ecosystem optical properties. Two vegetation greenness indices (Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI)) and a measure of the fraction of photosynthetically active radiation absorbed by vegetation (fPAR) were compared across sampling platforms, which ranged in pixel size from 1 meter (tram system in the field) to 1000 m (MODIS satellite sensor). For the EVI, there was excellent agreement between MODIS, AVIRIS and the ground measurements (tram system). AVIRIS and tram-based NDVI and fPAR values were in close agreement. However, MODIS NDVI and fPAR values were consistently higher than those determined from the field and the aircraft sensor, and these differences could not be entirely attributed to differences in sampling scale. Interestingly, MODIS fPAR derived from backup algorithms (NDVI driven) was closer to the AVIRIS and tram fPAR under the cloudy conditions.
Ferreira, ME, Ferreira, LG, Huete, A & Peccinini, AA 2006, 'Analise Comparativa Dos Produtos Modis Ecologia Para O Monitoramento Biofisico Ambiental Do Bioma Cerrado', Brazillian Journal of Geophysics, vol. 24, no. 2, pp. 251-260.
The Brazilian Cerrado is an extensive and complex biome, characterized by rapid and abrupt land cover changes. Due to its dimensions and physiognomic variations, the Cerrado plays an important role regarding the water, energy, and carbon fluxes at both the regional and global scales. Therefore, the correct understanding of the structure and ecological functioning of this biome, particularly in the temporal domain, is of great importance. With this respect, in this study we compared the seasonal response and land cover discrimination of the major MODIS (MODerate resolution Imaging Spectroradiometer) biophysical indices: the normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the leaf area index (LAI), and the fraction of absorbed photosynthetically active radiation (fAPAR). In spite of the fact the four indices showed similar temporal trends, the LAI showed the highest sensitivity to the seasonal variations of the natural and converted landscapes. On the other hand, the NDVI showed the best performance regarding land cover discrimination. Our results suggest a synergistic approach concerning the MODIS biophysical / ecological variables for land cover assessments and environmental monitoring of the Cerrado biome.
Ferreira, ME, Ferreira, LG, Huete, AR & Peccinini, AA 2006, 'Comparative analysis of the MODIS Ecology products for the biophysical environmental monitoring of the Cerrado biome', Revista Brasileira de Geofisica, vol. 24, no. 2, pp. 251-260.
The Brazilian Cerrado is an extensive and complex biome, characterized by rapid and abrupt land cover changes. Due to its dimensions and physiognomic variations, the Cerrado plays an important role regarding the water, energy, and carbon fluxes at both the regional and global scales, Therefore, the correct understanding of the structure and ecological functioning of this biome, particularly in the temporal domain, is of great importance, With this respect, in this study we compared the seasonal response and land cover discrimination of the major MODIS (MODerate resolution imaging Spectroradiometer) "biophysical" indices: the normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the leaf area index (LAI), and the fraction of absorbed photosynthetically active radiation (fAPAR). In spite of the fact the four indices showed similar temporal trends, the LAI showed the highest sensitivity to the seasonal variations of the natural and converted landscapes, On the other hand, the NDVI showed the best performance regarding land cover discrimination, Our results suggest a synergistic approach concerning the MCDIS biophysical / ecological variables for land cover assessments and environmental monitoring of the Cerrado biome. © 2006 Sociedade Brasileira de Geofísica.
Franklin, KA, Lyons, K, Nagler, PL, Lampkin, D, Glenn, E, Molina-Freaner, F, Markow, T & Huete, A 2006, 'Buffelgrass (Pennisetum ciliare) land conversion and productivity in the plains of Sonora, Mexico', Biological Conservation, vol. 127, pp. 62-71.View/Download from: Publisher's site
Bufflelgrass (Pennisetum ciliare syn. Cenchrus ciliaris) is an African grass that has been widely introduced in subtropical arid regions of the world to improve rangelands for cattle production. However, it can have a negative effect on the diversity of native plant communities. Buffelgrass was introduced to Sonora, Mexico in the 1970s as a means to bolster the cattle industry. Desmonte, the process by which native desert vegetation is removed in preparation for buffelgrass seeding, alters the land surface such that buffelgrass plots are easily detectable from aerial and Landsat satellite images. We estimated the extent of conversion to buffelgrass in a 1,850,000 ha area centered on Hermosillo, from MSS and TM images from 1973, 1983, 1990 and 2000. We then compared the relative above-ground productivity of buffelgrass to native vegetation using Normalized Difference Vegetation Index values (NDVI) from Landsat and Moderate Resolution Imaging Spectrometer (MODIS) satellite sensor systems. Buffelgrass pastures have increased from just 7700 ha in 1973 to over 140,000 ha in 2000. Buffelgrass pastures now cover 8% of the land surface in the study area. Buffelgrass pastures have lower net primary productivity, estimated by MODIS NDVI values, than unconverted desert land. The desmonte process removes trees and shrubs, while the buffelgrass plantings are often sparse, leading to an apparent net loss in net primary production from land conversion. We recommend that the desmonte process be discontinued until its efficacy and safety for native ecosystems can be established, and that a comprehensive plan for preserving biodiversity while accomodating economic development be established for this region of the Sonoran Desert in Mexico.
Huete, AR, Didan, K, Shimabukuro, YE, Ratana, P, Saleska, SR, Hutyra, LR, Yang, WZ, Nemani, RR & Myneni, R 2006, 'Amazon rainforests green-up with sunlight in dry season', GEOPHYSICAL RESEARCH LETTERS, vol. 33, no. 6.View/Download from: Publisher's site
Jiang, Z, Huete, A, Chen, J, Chen, Y, Liu, J, Yan, G & Zhang, X 2006, 'Analysis of NDVI and scaled difference vegetation index retrievals of vegetation fraction', Remote Sensing Of Environment, vol. 101, no. 3, pp. 366-369.View/Download from: Publisher's site
The normalized difference vegetation index (NDVI) is the most widely used vegetation index for retrieval of vegetation canopy biophysical properties. Several studies have investigated the spatial scale dependencies of NDVI and the relationship between NDVI and fractional vegetation cover, but without any consensus on the two issues. The objectives of this paper are to analyze the spatial scale dependencies of NDVI and to analyze the relationship between NDVI and fractional vegetation cover at different resolutions based on linear spectral mixing models. Our results show strong spatial scale dependencies of NDVI over heterogeneous surfaces, indicating that NDVI values at different resolutions may not be comparable. The nonlinearity of NDVI over partially vegetated surfaces becomes prominent with darker soil backgrounds and with presence of shadow. Thus, the NDVI may not be suitable to infer vegetation fraction because of its nonlinearity and scale effects. We found that the scaled difference vegetation index (SDVI), a scale-invariant index based on linear spectral mixing of red and near-infrared reflectances, is a more suitable and robust approach for retrieval of vegetation fraction with remote sensing data, particularly over heterogeneous surfaces. The proposed method was validated with experimental field data, but further validation at the satellite level would be needed.
Jiang, Z, Huete, A, Liu, J & Chen, Y 2006, 'An Analysis of Angle-Based With Ratio-Based Vegetation Indices', IEEE Transactions on Geoscience and Remote Sensing, vol. 44, no. 9, pp. 2506-2513.View/Download from: Publisher's site
Remotely sensed, angle-based vegetation indices that measure vegetation amounts by the angle between an approximated soil line and a simulated vegetation isoline in the red-near-infrared reflectance space were developed and evaluated in this paper. Unsalan and Boyer previously proposed an angle-based vegetation index, thetas (denoted as thetas NDVI in this paper), based on the normalized difference vegetation index (NDVI) with the objective of overcoming the saturation problem in the NDVI. However, thetasNDVI did not consider strong soil background influences present in the NDVI. To reduce soil background noise, an angle-based vegetation index, thetasSAVI , based on the soil-adjusted vegetation index (SAVI), was derived using trigonometric analysis. The performance of thetasNDVI and thetasSAVI was evaluated and compared with their corresponding vegetation indices, NDVI and SAVI. The soil background influence on thetasNDVI was found to be as significant as that on the NDVI. thetasNDVI was found to be more sensitive to vegetation amount than the NDVI at low vegetation density levels, but less sensitive to vegetation fraction at high vegetation density levels. Thus, the saturation effect at high vegetation density levels encountered in the NDVI was not mitigated by thetasNDVI. By contrast, thetasSAVI exhibited insignificant soil background effects and weaker saturation, as in SAVI, but also improved upon the dynamic range of SAVI. Analyses and evaluation suggest that thetasSAVI is an optimal vegetation index to assess and monitor vegetation cover across the entire range of vegetation fraction density levels and over a wide variety of soil backgrounds
Miura, T, Huete, A & Yoshioka, H 2006, 'An empirical investigation of cross-sensor relationships of NDVI and red/near-infrared reflectance using EO-1 Hyperion data', Remote Sensing Of Environment, vol. 100, no. 2, pp. 223-236.View/Download from: Publisher's site
Long term observations of global vegetation from multiple satellites require much effort to ensure continuity and compatibility due to differences in sensor characteristics and product generation algorithms. In this study, we focused on the bandpass filter differences and empirically investigated cross-sensor relationships of the normalized difference vegetation index (NDVI) and reflectance. The specific objectives were: 1) to understand the systematic trends in cross-sensor relationships of the NDVI and reflectance as a function of spectral bandpasses, 2) to examine/identify the relative importance of the spectral features (i.e., the green peak, red edge, and leaf liquid water absorption regions) in and the mechanism(s) of causing the observed systematic trends, and 3) to evaluate the performance of several empirical cross-calibration methods in modeling the observed systematic trends. A Level 1A Hyperion hyperspectral image acquired over a tropical forestsavanna transitional region in Brazil was processed to simulate atmospherically corrected reflectances and NDVI for various bandpasses, including Terra Moderate Resolution Imaging Spectroradiometer (MODIS), NOAA-14 Advanced Very High Resolution Radiometer (AVHRR), and Landsat-7 Enhanced Thematic Mapper Plus (ETM+). Data were extracted from various land cover types typically found in tropical forest and savanna biomes and used for analyses. Both NDVI and reflectance relationships among the sensors were neither linear nor unique and were found to exhibit complex patterns and bandpass dependencies.
Bauer, M, Carter, G, Dungan, JL, Foody, G, Gitelson, AA, Goetz, S, Huete, AR, Næsset, E, Peñuelas, J, Quattrochi, DA, Stehman, S, Thenkabail, P & Wigneron, JP 2005, 'Appointment of new editorial board members', Remote Sensing of Environment, vol. 95, no. 4, p. 413.View/Download from: Publisher's site
Nagler, PL, Glenn, E, Curtis, C, Hursh, K & Huete, A 2005, 'Vegetation Mapping For Change Detection On An Arid-Zone River', Environmental Monitoring and Assessment, vol. 109, no. 1-3, pp. 255-274.View/Download from: Publisher's site
A vegetation mapping system for change detection was tested at the Havasu National Wildlife Refuge (HNWR) on the Lower Colorado River. A low-cost, aerial photomosaic of the 4200 ha, study area was constructed utilizing an automated digital camera system, supplemented with oblique photographs to aid in determining species composition and plant heights. Ground-truth plots showed high accuracy in distinguishing native cottonwood (Populus fremontii) and willow (Salix gooddingii) trees from other vegetation on aerial photos. Marsh vegetation (mainly cattails, Typha domengensis) was also easily identified. However, shrubby terrestrial vegetation, consisting of saltcedar (Tamarix ramosissima), arrowweed (Pluchea sericea), and mesquite trees (Prosopis spp.), could not be accurately distinguished from each other and were combined into a single shrub layer on the final vegetation map. The final map took the form of a base, shrub and marsh layer, which was displayed as a Normalized Difference Vegetation Index map from a Landsat Enhanced Thematic Mapper (ETM+) image to show vegetation intensity.
Nagler, PL, Hinojosa-Huerta, O, Glenn, E, Garcia-Hernandez, J, Romo, R, Curtis, C, Huete, A & Nelson, SG 2005, 'Regeneration of Native Trees in the Presence of Invasive Saltcedar in the Colorado River Delta, Mexico', Conservation Biology, vol. 19, no. 6, pp. 1842-1852.View/Download from: Publisher's site
Many riparian zones in the Sonoran Desert have been altered by elimination of the normal flood regime; such changes to the flow regime have contributed to the spread of saltcedar (Tamarix ramosissma Ledeb.), an exotic, salt-tolerant shrub. It has been proposed that reestablishment of a natural flow regime on these rivers might permit passive restoration of native trees, without the need for aggressive saltcedar clearing programs. We tested this proposition in the Colorado River delta in Mexico, which has received a series of large-volume water releases from U.S. dams over the past 20 years. We mapped the vegetation of the delta riparian corridor through ground and aerial surveys (19992002) and satellite imagery (19922002) and related vegetation changes to river flood flows and fire events. Although saltcedar is still the dominant plant in the delta, native cottonwood ( Populus fremontii S. Wats.) and willow (Salix gooddingii C. Ball) trees have regenerated multiple times because of frequent flood releases from U.S. dams since 1981. Tree populations are young and dynamic (ages 510 years). The primary cause of tree mortality between floods is fire. Biomass in the floodplain, as measured by the normalized difference vegetation index on satellite images, responds positively even to low-volume (but long-duration) flood events. Our results support the hypothesis that restoration of a pulse flood regime will regenerate native riparian vegetation despite the presence of a dominant invasive species, but fire management will be necessary to allow mature tree stands to develop.
Novo, EM, Ferreira, LG, Barbosa, C, Carvalho, C, Sano, EE, Shimabukuro, YE, Huete, A, Potter, C, ROBERTS, DA, HESS, LL, MELACK, JJ, Yoshioka, H, Klooster, S, Kumar, V, Myneni, RB, Ratana, P, Didan, K & Miura, T 2005, 'Advanced remote sensing techniques for global changes and Amazon ecosystem functioning studies', Acta Amazonica, vol. 35, no. 2, pp. 259-272.
This paper aims to assess the contribution of remote sensing technology in addressing key questions raised by the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA). The answers to these questions foster the knowledge on the climatic, biogechemical and hydrologic functioning of the Amazon, as well as on the impact of human activities at regional and global scales. Remote sensing methods allow integrating information on several processes at different temporal and spatial scales. By doing so, it is possible to perceive hidden relations among processes and structures, enhancing their teleconnections. Key advances in the remote sensing science are summarized in this article, which is particularly focused on information that would not be possible to be retrieved without the concurrence of this technology
Ratana, P, Huete, A & Ferreira, L 2005, 'Analysis of Cerrado Physiognomies and Conversion in the MODIS Seasonal - Temporal Domain', Earth Interactions, vol. 9, no. 3, pp. 1-22.
The cerrado biome in central Brazil is rapidly being converted into pasture and agricultural crops with important consequences for local and regional climate change and regional carbon fluxes between the atmosphere and land surface. Satellite remote sensing provides an opportunity to monitor the highly diverse and complex cerrado biome, encompassing grassland, shrubland, woodland and gallery forests, and converted areas. In this study, the potential of Terra Moderate Resolution Imaging Spectroradiometer (MODIS) data is analyzed to discriminate among these diverse cerrado physiognomies and converted pastures based on their seasonal dynamics and phenology. Four years (200003) of MODIS 16-day composited, 250-m resolution vegetation index (VI) data were extracted over a series of biophysically sampled field study sites representing the major cerrado types. The temporal VI profiles over the cerrado formations exhibited high seasonal contrasts with a pronounced dry season from June to August and a wet growing season from November to March. The converted pasture areas showed the highest seasonal contrasts while the gallery forest formation had the lowest contrast. Seasonal VI variations were negatively correlated with woody canopy crown cover and provided a method to discriminate among converted cerrado areas, gallery forests, and the woody and herbaceous cerrado formations. The grassland and shrub cerrado formations, however, were difficult to separate based on their seasonal VI profiles. Maximum discrimination among the cerrado types occurred during the dry season where a positive linear relationship was found between VI and green cover. The annual integrated VI values showed the gallery forests and cerrado woodland as having the highest, and hence most annual productivity, while the more herbaceous shrub and grassland cerrado types were least productive.
Sano, EE, Ferreira, LG & Huete, A 2005, 'Synthetic Aperture Radar (L band) and Optical Vegetation Indices for Discriminating the Brazilian Savanna Physiognomies: A Comparative Analysis', Earth Interactions, vol. 9, no. 15, pp. 1-15.
The all-weather capability, signal independence to the solar illumination angle, and response to 3D vegetation structures are the highlights of active radar systems for natural vegetation mapping and monitoring. However, they may present significant soil background effects. This study addresses a comparative analysis of the performance of L-band synthetic aperture radar (SAR) data and optical vegetation indices (VIs) for discriminating the Brazilian cerrado physiognomies. The study area was the Brasilia National Park, Brazil, one of the test sites of the Large-Scale BiosphereAtmosphere (LBA) experiment in Amazonia. Seasonal Japanese Earth Resources Satellite-1 (JERS-1) SAR backscatter coefficients (?°) were compared with two vegetation indices [normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI)] over the five most dominant cerrados physiognomies plus gallery forest. In contrast to the VIs, ?° from dry and wet seasons did not change significantly, indicating primary response to vegetation structures. Discriminant analysis and analysis of variance (ANOVA) showed an overall higher performance of radar data. However, when both SAR and VIs are combined, the discrimination capability increased significantly, indicating that the fusion of the optical and radar backscatter observations provides overall improved classifications of the cerrado types. In addition, VIs showed good performance for monitoring the cerrado dynamics.
Shabanov, NV, Huang, D, Yang, W, Tan, B, Knyazikhin, Y, Myneni, RB, Ahl, DE, Gower, ST, Huete, A, Aragao, LE & Shimabukuro, YE 2005, 'Analysis and Optimization of the MODIS Leaf Area Index Algorithm Retrievals Over Broadleaf Forests', IEEE Transactions on Geoscience and Remote Sensing, vol. 43, no. 8, pp. 1855-1865.View/Download from: Publisher's site
Broadleaf forest is a major type of Earth's land cover with the highest observable vegetation density. Retrievals of biophysical parameters, such as leaf area index (LAI), of broadleaf forests at global scale constitute a major challenge to modern remote sensing techniques in view of low sensitivity (saturation) of surface reflectances to such parameters over dense vegetation. The goal of the performed research is to demonstrate physical principles of LAI retrievals over broadleaf forests with the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI algorithm and to establish a basis for algorithm refinement. To sample natural variability in biophysical parameters of broadleaf forests, we selected MODIS data subsets covering deciduous broadleaf forests of the eastern part of North America and evergreen broadleaf forests of Amazonia. The analysis of an annual course of the Terra MODIS Collection 4 LAI product over broadleaf forests indicated a low portion of best quality main radiative transfer-based algorithm retrievals and dominance of low-reliable backup algorithm retrievals during the growing season.
Nagler, PL, Cleverly, JR, Glenn, E, Lampkin, D, Huete, A & Zhengming, W 2005, 'Predicting riparian evapotranspiration from MODIS vegetation indices and meteorological data', Remote Sensing Of Environment, vol. 94, no. 1, pp. 17-30.View/Download from: Publisher's site
A vegetation index (VI) model for predicting evapotranspiration (ET) from data from the Moderate Resolution Imaging Spectrometer (MODIS) on the EOS-1 Terra satellite and ground meteorological data was developed for riparian vegetation along the Middle Rio Grande River in New Mexico. Ground ET measurements obtained from eddy covariance towers at four riparian sites were correlated with MODIS VIs, MODIS land surface temperatures (LSTs), and ground micrometeorological data over four years. Sites included two saltcedar (Tamarix ramosissima) and two Rio Grande cottonwood (Populus deltoides ssp. Wislizennii) dominated stands. The Enhanced Vegetation Index (EVI) was more closely correlated (r=0.76) with ET than the Normalized Difference Vegetation Index (NDVI; r=0.68) for ET data combined over sites and species. Air temperature (Ta) measured over the canopy from towers was the meteorological variable that was most closely correlated with ET (r=0.82). MODIS LST data at 1- and 5-km resolutions were too coarse to accurately measure the radiant surface temperature within the narrow riparian corridor; hence, energy balance methods for estimating ET using MODIS LSTs were not successful. On the other hand, a multivariate regression equation for predicting ET from EVI and Ta had an r2=0.82 across sites, species, and years. The equation was similar to VIET models developed for crop species. The finding that ET predictions did not require species-specific equations is significant, inasmuch as these are mixed vegetation zones that cannot be easily mapped at the species level.
Nagler, PL, Scott, RL, Westenburg, C, Cleverly, JR, Glenn, E & Huete, A 2005, 'Evapotranspiration on western U.S. rivers estimated using the Enhanced Vegetation Index from MODIS and data from eddy covariance and Bowen ratio flux towers', Remote Sensing Of Environment, vol. 97, no. 3, pp. 337-351.View/Download from: Publisher's site
We combined remote sensing and in-situ measurements to estimate evapotranspiration (ET) from riparian vegetation over large reaches of western U.S. rivers and ET by individual plant types. ET measured from nine flux towers (eddy covariance and Bowen ratio) established in plant communities dominated by five major plant types on the Middle Rio Grande, Upper San Pedro River, and Lower Colorado River was strongly correlated with Enhanced Vegetation Index (EVI) values from the Moderate Resolution Imaging Spectrometer (MODIS) sensor on the NASA Terra satellite. The inclusion of maximum daily air temperatures (Ta) measured at the tower sites further improved this relationship. Sixteen-day composite values of EVI and Ta were combined to predict ET across species and tower sites (r2 = 0.74); the regression equation was used to scale ET for 20002004 over large river reaches with Ta from meteorological stations. Measured and estimated ET values for these river segments were moderate when compared to historical, and often indirect, estimates and ranged from 851874 mm yr- 1. ET of individual plant communities ranged more widely. Cottonwood (Populus spp.) and willow (Salix spp.) stands generally had the highest annual ET rates (11001300 mm yr- 1), while mesquite (Prosopis velutina) (4001100 mm yr- 1) and saltcedar (Tamarix ramosissima) (3001300 mm yr- 1) were intermediate, and giant sacaton (Sporobolus wrightii) (500800 mm yr- 1) and arrowweed (Pluchea sericea) (300700 mm yr- 1) were the lowest. ET rates estimated from the flux towers and by remote sensing in this study were much lower than values estimated for riparian water budgets using crop coefficient methods for the Middle Rio Grande and Lower Colorado River.
Ferreira, LG & Huete, A 2004, 'Assessing the seasonal dynamics of the Brazilian Cerrado vegetation through the use of spectral vegetation indices', International journal of remote sensing, vol. 25, no. 10, pp. 1837-1860.View/Download from: Publisher's site
In this study, the response of vegetation indices (VIs) to the seasonal patterns and spatial distribution of the major vegetation types encountered in the Brazilian Cerrado was investigated. The Cerrado represents the second largest biome in South America and is the most severely threatened biome as a result of rapid land conversions. Our goal was to assess the capability of VIs to effectively monitor the Cerrado and to discriminate among the major types of Cerrado vegetation. A full hydrologic year (1995) of composited AVHRR, local area coverage (LAC) data was converted to Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) values. Temporal extracts were then made over the major Cerrado vegetation communities. Both the NDVI and SAVI temporal profiles corresponded well to the phenological patterns of the natural and converted vegetation formations and depicted three major categories encompassing the savanna formations and pasture sites, the forested areas, and the agricultural crops. Secondary differences in the NDVI and SAVI temporal responses were found to be related to their unique interactions with sun-sensor viewing geometries. An assessment of the functional behaviour of the VIs confirmed SAVI responds primarily to NIR variations, while the NDVI showed a strong dependence on the red reflectance. Based on these results, we expect operational use of the MODIS Enhanced Vegetation Index (EVI) to provide improved discrimination and monitoring capability of the significant Cerrado vegetation types.
Ferreira, LG, Yoshioka, H, Huete, A & Sano, EE 2004, 'Optical characterization of the Brazilian Savanna physiognomies for improved land cover monitoring of the cerrado biome: preliminary assessments from an airborne campaign over an LBA core site', Journal Of Arid Environments, vol. 56, no. 3, pp. 425-447.View/Download from: Publisher's site
It is estimated that approximately 40% of the Cerrado, the second largest biome in South America, have been already converted. In this study, situated within the scope of the Large Scale Biosphere-Atmosphere Experiment in Amazonia project (LBA), we conducted a wet season ground and airborne campaign over the Brasilia National Park (BNP), the largest LBA core site in the Cerrado biome, to measure the optical and biophysical properties of the major Cerrado land cover types. We investigated land cover discrimination through the analyses of fine resolution spectra, convolved spectra (MODIS bandpasses), and vegetation indicesthe normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI). At these three data levels, three major physiognomic domains (herbaceous, woody, and forested) could be readily identified, and the amount of data correctly classified into the five major land cover types found at BNP were 91% (full spectra), 78% (red and NIR), 75% (NDVI), and 71% (EVI).
Nagler, PL, Glenn, E, Thompson, TL & Huete, A 2004, 'Leaf area index and normalized difference vegetation index as predictors of canopy characteristics and light interception by riparian species on the Lower Colorado River', Agricultural and Forest Meteorology, vol. 125, no. 1-2, pp. 1-17.View/Download from: Publisher's site
Leaf area index (LAI) and normalized difference vegetation index (NDVI) were compared for riparian species along a 350 km stretch of the Lower Colorado River in the United States and Mexico. The species included two native trees, cottonwood (Populus fremontii) and willow (Salix gooddingii), and two salt-tolerant shrubs, saltcedar (Tamarix ramosissima) and arrowweed (Pluchia sericea), exhibiting large differences in leaf type and canopy architecture. LAI was measured with a Licor 2000 plant canopy analyzer calibrated against biomass measurements of LAI, whereas NDVI was measured by low-level aerial photography using a DyCam digital camera with Red (R)Blue (B)near infrared (NIR) bands. In addition, reflectance spectra were measured for leaf samples collected from plants in the field. Leaf samples of all species had similar reflectance spectra in the visible (VIS) and NIR, hence similar NDVI values, ranging from 0.62 to 0.72 (P>0.05). LAI values of field plants varied over a relatively narrow range, with mean values of 3.50, 3.28, 2.81 and 3.69 for cottonwood, willow, saltcedar and arrowweed, respectively. However, field plants showed distinct species differences in NDVI, with the following mean values: cottonwood (0.686), willow (0.600), saltcedar (0.473) and arrowweed (0.254) (all significantly different at P<0.05). Differences in NDVI among field plants could be explained by differences in the light extinction coefficient, k, for plant canopies, according to the formula: fIRs=(1-e-kLAI), where fIRs is the fraction of incident light intercepted by the canopy. At one extreme, cottonwood had broad leaves that faced the sun, and a calculated k of 1.25, whereas at the other extreme, arrowweed had linear leaves that were near to vertical, and had a k of 0.15. Ecophysiological implications of the differences among the species are discussed.
Todd, CD, Zeng, P, Rodriguez Huete, AM, Hoyos, ME & Polacco, JC 2004, 'Transcripts of MYB-like genes respond to phosphorous and nitrogen deprivation in Arabidopsis', Planta, vol. 219, no. 6, pp. 1003-1009.View/Download from: Publisher's site
In Arabidopsis thaliana (L.) Heynh., AtPhr2 and AtNsr1 encode proteins with MYB-like and α-helical domains. They resemble CrPsr1, a nuclear-localized MYB protein that is critical for acclimation to phosphorous (P) starvation in the alga Chlamydomonas reinhardtii. Reverse transcription-polymerase chain reaction analysis of the first unique exons indicated that AtPhr2 mRNA increased as early as 6 h after P deprivation (-P), whereas nitrogen deprivation (-N) had no effect. The AtNsr1 mRNA level increased exclusively under -N, an increase first noted by 2 days in -N. In spite of P- and N-specific effects on expression of AtPhr2 and AtNsr1 there appeared to be P-N cross-talk at the whole-plant level. Total non-secreted acid phosphatase activity increased under both -P and -N within 2 days of deprivation. Further, the pho2-1/pho2-1 mutant, reported to be a phosphate accumulator, showed no increase in AtPhr2 mRNA in response to -P and a 70% reduction in the response of AtNsr1 mRNA to -N. Consistent with this pattern, there was no increase in acid phosphatase activity in pho2-1/pho2-1 plants deprived of P or N. However, when deprived of P, pho2-1/pho2-1 plants accumulated much higher levels of nitrate. T-DNA disruption of AtNsr1 resulted in altered expression of at least one nitrate transporter (AtNRT2.5). Further evidence of cross-talk between N and P responses was altered expression of N-responsive genes in pho2-1/pho2-1. © Springer-Verlag 2004.
Vodkin, LO, Khanna, A, Shealy, R, Clough, SJ, Gonzalez, DO, Philip, R, Zabala, G, Thibaud-Nissen, F, Sidarous, M, Strömvik, MV, Shoop, E, Schmidt, C, Retzel, E, Erpelding, J, Shoemaker, RC, Rodriguez-Huete, AM, Polacco, JC, Coryell, V, Keim, P, Gong, G, Liu, L, Pardinas, J & Schweitzer, P 2004, 'Microarrays for global expression constructed with a low redundancy set of 27,500 sequenced cDNAs representing an array of developmental stages and physiological conditions of the soybean plant', BMC Genomics, vol. 5.View/Download from: Publisher's site
Background: Microarrays are an important tool with which to examine coordinated gene expression. Soybean (Glycine max) is one of the most economically valuable crop species in the world food supply. In order to accelerate both gene discovery as well as hypothesis-driven research in soybean, global expression resources needed to be developed. The applications of microarray for determining patterns of expression in different tissues or during conditional treatments by dual labeling of the mRNAs are unlimited. In addition, discovery of the molecular basis of traits through examination of naturally occurring variation in hundreds of mutant lines could be enhanced by the construction and use of soybean cDNA microarrays. Results: We report the construction and analysis of a low redundancy 'unigene' set of 27,513 clones that represent a variety of soybean cDNA libraries made from a wide array of source tissue and organ systems, developmental stages, and stress or pathogen-challenged plants. The set was assembled from the 5' sequence data of the cDNA clones using cluster analysis programs. The selected clones were then physically reracked and sequenced at the 3' end. In order to increase gene discovery from immature cotyledon libraries that contain abundant mRNAs representing storage protein gene families, we utilized a high density filter normalization approach to preferentially select more weakly expressed cDNAs. All 27,513 cDNA inserts were amplified by polymerase chain reaction. The amplified products, along with some repetitively spotted control or 'choice' clones, were used to produce three 9,728-element microarrays that have been used to examine tissue specific gene expression and global expression in mutant isolines. Conclusions: Global expression studies will be greatly aided by the availability of the sequence-validated and low redundancy cDNA sets described in this report. These cDNAs and ESTs represent a wide array of developmental stages and physiological co...
Ferreira, LG, Yoshioka, H, Huete, A & Sano, EE 2003, 'Seasonal landscape and spectral vegetation index dynamics in the Brazilian Cerrado: An analysis within the Large-Scale Biosphere Atmosphere Experiment in Amazonia (LBA)', Remote Sensing Of Environment, vol. 87, no. 4, pp. 534-550.View/Download from: Publisher's site
The Brazilian Cerrado biome comprises a vertically structured mosaic of grassland, shrubland, and woodland physiognomies with distinct phenology patterns. In this study, we investigated the utility of spectral vegetation indices in differentiating these physiognomies and in monitoring their seasonal dynamics. We obtained high spectral resolution reflectances, during the 2000 wet and dry seasons, over the major Cerrado types at Brasilia National Park (BNP) using the light aircraft-based Modland Quick Airborne Looks (MQUALS) package, consisting of a spectroradiometer and digital camera. Site-intensive biophysical and canopy structural measurements were made simultaneously at each of the Cerrado types including Cerrado grassland, shrub Cerrado, wooded Cerrado, Cerrado woodland, and gallery forest. We analyzed the spectral reflectance signatures, their first derivative analogs, and convolved spectral vegetation indices (VI) over all the Cerrado physiognomies.
Gao, X, Huete, A & Didan, K 2003, 'Multisensor Comparisons and Validation of MODIS Vegetation Indices at the Semiarid Jornada Experimental Range', IEEE Transactions on Geoscience and Remote Sensing, vol. 41, no. 10, pp. 2368-2381.View/Download from: Publisher's site
Vegetation indices (VIs) are one of the standard science products available from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on the Earth Observing System (EOS) Terra platform, launched in December 1999. An important requirement of MODIS science products is that they be rigorously validated. In this study, we conducted a site-intensive MODIS VI product validation at the semiarid Jornada Experimental Range, New Mexico, an EOS Land Validation Core Site. Our validation approach involved scaling up independent fine-grained datasets, including ground and airborne radiometry, and high spatial resolution imagery [Enhanced Thematic Mapper Plus (ETM+)], to the coarser MODIS spatial resolutions. The MODIS VIs were evaluated with respect to their radiometric performances, the uncertainties of the compositing methodology, and their capabilities to depict seasonal variations in vegetation. The MODIS Quick Airborne Looks (MQUALS) radiometric package was found useful in up-scaling field in situ measurements to coarser spatial resolutions. Both single-day nadir-view and 16-day composited MODIS reflectances and VIs matched well with the nadir-based atmosphere-free MQUALS observations for all the land cover types found at Jornada, with the root mean squared deviations less than 0.03.
Huete, A, Miura, T & Gao, X 2003, 'Land Cover Conversion and Degradation Analyses Through Coupled Soil-Plant Biophysical Parameters Derived From Hyperspectral EO-1 Hyperion', IEEE Transactions on Geoscience and Remote Sensing, vol. 41, no. 6, pp. 1268-1276.View/Download from: Publisher's site
Land degradation in semiarid areas results from various factors, including climate variations and human activity, and can lead to desertification. The process of degradation results in simultaneous and complex variations of many interrelated soil and vegetation biophysical parameters, rendering it difficult to develop simple and robust remote sensing mapping and monitoring approaches. In this study, we tested the use of Earth Observing 1 (EO-1) Hyperion hyperspectral data to analyze land degradation patterns within the protected Nacunan Biosphere Reserve and surrounding areas in the Monte Desert region of Argentina. The floristically diverse vegetation communities included mesquite forest (algarrobal), creosotebush (jarillal), sand-dune (medanal), and severely degraded (peladal) sites. Various optical measures of land degradation were employed, including vegetation indexes, spectral derivatives, albedo, and spectral mixture analysis. Spectral mixture analysis provided the best characterization of the unstable and spatially variable landscape encountered at the Nacunan Biosphere Reserve. Spectral unmixing provided simultaneous measures of green vegetation, nonphotosynthetic vegetation, and soil, all of which were deemed essential in characterizing land degradation. In conjunction with multitemporal data from the more commonly employed broadband sensors, hyperspectral data can provide a powerful methodology toward understanding environmental degradation.
Wang, ZX, Liu, C & Huete, A 2003, 'From AVHRR-NDVI to MODIS-EVI: Advances in vegetation index research', Acta Ecologica Sinica, vol. 23, no. 5, pp. 979-987.
Yoshioka, H, Miura, T & Huete, A 2003, 'An Isoline-Based Translation Technique of Spectral Vegetation Index Using EO-1 Hyperion Data', IEEE Transactions on Geoscience and Remote Sensing, vol. 41, no. 6, pp. 1363-1372.View/Download from: Publisher's site
The availability of similar satellite data products from multiple sensors has focused much attention on the issue of continuity across satellite data products from past, current, and future sensors. Hyperspectral datasets acquired over a variety of land cover types are extremely useful in attempting to resolve spectral differences in the global datasets from different sensors. The datasets from the Earth Observing 1 (EO-1) Hyperion sensor are very suitable for this purpose, as is airborne hyperspectral data. In this paper, we examine the possibility of translating vegetation index (VI) data between two sensors by using imagery from the Hyperion sensor and utilizing the vegetation isoline concept. The objectives of this paper are to introduce and test a VI translation technique, focused on the spectral differences associated with sensor spectral bandpass filters. The translation of global VI datasets from one sensor to another requires a methodology applicable over various land cover types and throughout the wide ranges in VI values. To meet these requirements, a technique is proposed that utilizes adjustable translation coefficients, based on an estimation of the leaf area index value relative to a numerical canopy model. The theoretical basis of the proposed translation algorithm is explained in terms of the vegetation isoline concept. Its performance was tested through a numerical experiment with a Hyperion image, focusing on the normalized difference vegetation index (NDVI) as a representative vegetation index. The results indicate the potential of the isoline-based translation technique for stable translation throughout wide ranges of NDVI values.
Zhang, X, Friedl, MA, Schaaf, CB, Strahler, AH, Hodges, JC, Gao, F, Reed, BC & Huete, A 2003, 'Monitoring vegetation phenology using MODIS', Remote Sensing Of Environment, vol. 84, no. 3, pp. 471-475.View/Download from: Publisher's site
Accurate measurements of regional to global scale vegetation dynamics (phenology) are required to improve models and understanding of inter-annual variability in terrestrial ecosystem carbon exchange and climate-biosphere interactions. Since the mid-1980s, satellite data have been used to study these processes. In this paper, a new methodology to monitor global vegetation phenology from time series of satellite data is presented. The method uses series of piecewise logistic functions, which are fit to remotely sensed vegetation index (VI) data, to represent intra-annual vegetation dynamics. Using this approach, transition dates for vegetation activity within annual time series of VI data can be determined from satellite data. The method allows vegetation dynamics to be monitored at large scales in a fashion that it is ecologically meaningful and does not require pre-smoothing of data or the use of user-defined thresholds. Preliminary results based on an annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS) data for the northeastern United States demonstrate that the method is able to monitor vegetation phenology with good success.
Huete, A, Didan, K, Miura, T, Rodriguez, EP, Gao, X & Ferreira, LG 2002, 'Overview of the radiometric and biophysical performance of the MODIS vegetation indices', Remote Sensing Of Environment, vol. 83, no. 1-2, pp. 195-213.View/Download from: Publisher's site
We evaluated the initial 12 months of vegetation index product availability from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Earth Observing System-Terra platform. Two MODIS vegetation indices (VI), the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), are produced at 1-km and 500-m resolutions and 16-day compositing periods. This paper presents an initial analysis of the MODIS NDVI and EVI performance from both radiometric and biophysical perspectives. We utilize a combination of site-intensive and regionally extensive approaches to demonstrate the performance and validity of the two indices. Our results showed a good correspondence between airborne-measured, top-of-canopy reflectances and VI values with those from the MODIS sensor at four intensively measured test sites representing semi-arid grass/shrub, savanna, and tropical forest biomes. Simultaneously derived field biophysical measures also demonstrated the scientific utility of the MODIS VI. Multitemporal profiles of the MODIS VIs over numerous biome types in North and South America well represented their seasonal phenologies. Comparisons of the MODIS-NDVI with the NOAA-14, 1-km AVHRR-NDVI temporal profiles showed that the MODIS-based index performed with higher fidelity. The dynamic range of the MODIS VIs are presented and their sensitivities in discriminating vegetation differences are evaluated in sparse and dense vegetation areas. We found the NDVI to asymptotically saturate in high biomass regions such as in the Amazon while the EVI remained sensitive to canopy variations.
Miura, T, Huete, A, Yoshioka, H & Holben, BN 2001, 'An error and sensitivity analysis of atmospheric resistant vegetation indices derived from dark target-based atmospheric correction', Remote Sensing Of Environment, vol. 78, pp. 284-298.View/Download from: Publisher's site
An error and sensitivity analysis was conducted to investigate the capabilities of the atmospheric resistant vegetation indices (VIs) for minimizing ''residual aerosol'' effects. The residual aerosol effects result from the assumptions and characteristics of the dark target (DT) approach used to estimate aerosol optical properties in the atmospheric correction scheme (referred to as the dark target-based atmospheric correction, DTAC). The performances of two atmospheric resistant VIs, the atmospherically resistant vegetation index (ARVI) and enhanced vegetation index (EVI), were evaluated and compared with the normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI). The atmospheric resistant VIs successfully minimized the residual aerosol effects, resulting in a 60% reduction of the errors from the NDVI and SAVI when a proper aerosol model was used for the estimation and correction of aerosol effects. The reductions were greater for thicker aerosol atmosphere (larger aerosol optical thickness, AOT). The atmospheric resistant VIs, however, resulted in having larger bias errors than the NDVI and SAVI when an improper aerosol model was used. The application of atmospheric resistant VIs to the DTAC-derived surface reflectances is exactly what is being carried out by the Moderate Resolution Imaging Spectroradiometer (MODIS) VI algorithm. These results raise several issues for the effective, operational use of the DTAC algorithm and atmospheric resistant VIs, which are addressed in this paper.
Nagler, PL, Glenn, E & Huete, A 2001, 'Assessment of spectral vegetation indices for riparian vegetation in the Colorado River delta, Mexico', Journal Of Arid Environments, vol. 49, pp. 91-110.View/Download from: Publisher's site
This study tested the relationship between three, commonly-used vegetation indices (VIs), percent vegetation cover (% cover) and leaf area index (LAI) over a complex riparian landscape in the Colorado River delta, Mexico. Our objective was to correlate vegetation and soil features with VIs using low-level aerial photography, in preparation for scaling up to analysis of vegetation features using satellite imagery. We used a three-band digital imaging camera (Dycam) to collect data from an aircraft flying at 150 m. A series of 84 images (67×100 m) were analysed. Nine of these sites were ground-truthed; the species, % cover, and LAI were determined. Measured LAI (nine sites) from tree, shrub, and groundcover categories were used to determine a global (GLAI) value for 63 images. We conducted both VIs:% cover and VIs:GLAI regression analyses. The normalized difference vegetation index (NDVI) was the VI that best predicted % cover (r2=0·837), but the soil adjusted vegetation index (SAVI) and enhanced vegetation index (EVI) gave nearly equal results (r2=0·807 and 0·796, respectively). Normalized difference vegetation index, SAVI and EVI were less useful in predicting GLAI (r2=0·73, 0·65, 0·64, respectively).
Zamora-Arroyo, F, Nagler, PL, Briggs, M, Radtke, D, Rodriquez, H, Garcia, J, Valdes, C, Huete, A & Glenn, E 2001, 'Regeneration of native trees in response to flood releases from the United States into the delta of the Colorado River, Mexico', Journal Of Arid Environments, vol. 49, no. 1, pp. 49-64.View/Download from: Publisher's site
Over the past 20 years, discharge of water from the United States to the delta of the Colorado River in Mexico has regenerated native trees that now account for 23% of vegetation in a 100-km, non-perennial, stretch of river below Morelos Dam at the United StatesMexico border. The discharges are associated with the filling of Lake Powell, the last large reservoir to be constructed on the river, and with ENSO cycles that bring extra winter and spring precipitation to the watershed. The discharges below Morelos Dam produce overbank floods that germinate new cohorts of Populus fremontii andSalix gooddingii trees. Relatively little flood water from the United States is required to support a pulse flood regime that can result in regrowth of native vegetation in the delta. Based on analysis of past flows and existing tree populations, we estimate that a FebruaryApril flow of 3×109m3at 80120 m3s-1is sufficient to germinate and establish new cohorts of native trees. However, there was a positive correlation between frequency of flows and total vegetation cover over the years 19921999, showing that more frequent flows would further increase vegetation cover. The results support the importance of pulse floods in restoring the ecological integrity of arid-zone rivers.
Accio, LJ & Huete, A 2000, 'Resposta espectral de solos em razao do angulo de visada, da umidade e da rugosidade superficial (Soil Spectral Response In Relation To Viewing Angle, Soil Moisture And Surface Roughness)', Pesquisa Agropecuaria Brasileira, vol. 35, no. 12, pp. 2473-2484.View/Download from: Publisher's site
The objective of this study was to characterize the bi-directional reflectance factor (BRF) of three soil series (McAllister, Stronghold, and Epitaph) located at the Walnut Gulch Experimental Watershed (Arizona, USA) as a function of the viewing angle, soil moisture and surface roughness. Soil spectra were taken in the visible, near and mid-infrared regions, convolved to match the Landsat-TM bands, and the results were nonnalized to the Nadir response and expressed as relative BRE The anisotropic behavior varies from soil to soil and it was higher when the following conditions were taken combined or individually: shorter wavelengths, higher viewing and solar zenith angles, in the backscatteling direction, soil in the dry condition as opposed to wet condition, and in the rough surface as compared to the smooth surface of Epitaph soil series (the only soil tested for the effect of roughness). Rough and smooth surfaces of Epitaph soil, however, were better discriminated in the forward scattering direction. Differences in scale and methods used to obtain the spectral curves were pointed out as responsible for the enhancement of the anisotropic behavior of the soils for lab results as compared to field results.
De Oliveiraaccioly, LJ & Huete, AR 2000, 'Soil spectral response in relation to viewing angle, soil moisture and surface roughness', PESQUISA AGROPECUARIA BRASILEIRA, vol. 35, no. 12, pp. 2473-2484.View/Download from: Publisher's site
Fardella, CE, Mosso, L, Gómez-Sánchez, C, Cortés, P, Soto, J, Gómez, L, Pinto, M, Huete, A, Oestreicher, E, Foradori, A & Montero, JI 2000, 'Primary hyperaldosteronism in essential hypertensives: Prevalence, biochemical profile, and molecular biology', Journal of Clinical Endocrinology and Metabolism, vol. 85, no. 5, pp. 1863-1867.View/Download from: Publisher's site
There is evidence that primary aldosteronism (PA) may be common in patients with essential hypertension (EH) when determinations of serum aldosterone (SA), plasma renin activity (PRA), and the SA/PRA ratio are used as screening. An inherited form of primary hyperaldosteronism is the glucocorticoid-remediable aldosteronism (GRA) caused by an unequal crossing over between the CYB11B1 and CYP11B2 genes that results in a chimeric gene, which has aldosterone synthase activity regulated by ACTH. The aim of this study was to evaluate the prevalence of PA and the GRA in 305 EH patients and 205 normotensive controls. We measured SA (1-16 ng/dL) and PRA (1-2.5 ng/mL·h) and calculated the SA/PRA ratio in all patients. A SA/PRA ratio level greater than 25 was defined as being elevated. PA was diagnosed in the presence of high SA levels (> 16 ng/dL), low PRA levels (<0.5 ng/mL·h), and very high SA/PRA ratio (>50). Probable PA was diagnosed when the SA/PRA ratio was more than 25 but the other criteria were not present. A Fludrocortisone test was done to confirm the diagnosis. GRA was differentiated from other forms of PA by: the aldosterone suppression test with dexamethasone, the high levels of 18-hydroxycortisol, and the genetic detection of the chimeric gene. In EH patients, 29 of 305 (9.5%) had PA, 13 of 29 met all the criteria for PA, and 16 of 29 were initially diagnosed as having a probable PA and confirmed by the fludrocortisone test. Plasma potassium was normal in all patients. The dexamethasone suppression test was positive for GRA in 10 of 29 and 18-hydroxycortisol levels were high in 2 of 29 patients who had also a chimeric gene. In normotensive subjects, 3 of 205 (1.46%) had PA, and 1 of 205 had a GRA. In summary, we found a high frequency of normokalemic PA in EH patients. A high proportion of PA suppressed SA with dexamethasone, but only a few had a chimeric gene or high levels of 18-hydroxycortisol. These results emphasize the need to further investigate EH pat...
Gao, X, Huete, A, Ni, W & Miura, T 2000, 'Optical-Biophysical Relationships of Vegetation Spectra without Background Contamination', Remote Sensing Of Environment, vol. 74, no. 3, pp. 609-620.View/Download from: Publisher's site
For a better evaluation of the accuracy of VIs in estimating biophysical parameters, a true VI value attributed only to the vegetation signal and free of any contamination is needed. In this article, pure vegetation spectra were extracted from a set of open and closed canopies by unmixing the green vegetation signal from the background component. Canopy model-simulation and reflectances derived from graph-based linear extrapolation were used to unmix and derive a true vegetation signal, equivalent to a perfect absorber (free boundary) canopy background reflectance condition. Opticalbiophysical relationships were then derived for a variety of canopy structures with differences in foliage clumping, horizontal heterogeneity, and leaf type. A 3-dimensional canopy radiative transfer model and a hybrid geometric optical-radiative transfer model (GORT) were used to simulate the directional-hemispherical reflectances from agricultural, grassland, and forested canopies (cereal and broadleaf crop, grass, needleleaf, and broadleaf forest). The relationships of the extracted red and near-infrared reflectances and derived vegetation indices (VIs) to various biophysical parameters (leaf area index, fraction of absorbed photosynthetically active radiation, and percent ground cover) were examined for the pure vegetation spectra. The results showed normalized difference vegetation index (NDVI) relationships with biophysical parameters to become more asymptotic over the pure vegetation condition.
Miura, T, Huete, A & Yoshioka, H 2000, 'Evaluation of Sensor Calibration Uncertainties on Vegetation Indices for MODIS', IEEE Transactions on Geoscience and Remote Sensing, vol. 38, no. 3, pp. 1399-1409.View/Download from: Publisher's site
The impact of reflectance calibration uncertainties on the accuracies of several vegetation indices (VIs) was evaluated for the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the TERRA platform. A set of uncertainty propagation equations were designed to model the propagation of calibration uncertainties from top-of-atmosphere (TOA) reflectances to atmospherically-corrected VIs. The soil-adjusted vegetation index (SAVI), the atmospherically-resistant vegetation index (ARVI), and the enhanced vegetation index (EVI) were evaluated along with the normalized difference vegetation index (NDVI). The resultant VI uncertainties associated with calibration ucal (VI) varied with both surface reflectances and atmospheric conditions. Uncertainties in the NDVI and ARVI were highly dependent on pixel brightness, with the largest uncertainties occurring over dark targets with little or no vegetation. The SAVI uncertainties were nearly constant throughout a range of target brightness and vegetation abundance. The EVI uncertainties linearly increased with increasing EVI values. Atmosphere turbidities increased calibration uncertainties in all the VIs through their effect on TOA reflectances. The VI uncertainties were also found to decrease when the calibration errors were positively correlated between bands.
Qi, J, Kerr, YH, Moran, MS, Weltz, MA, Huete, A, Sorooshian, S & Bryant, R 2000, 'Leaf Area Index Estimates Using Remotely Sensed Data and BRDF Models in a Semiarid Region', Remote Sensing Of Environment, vol. 73, no. 1, pp. 18-30.View/Download from: Publisher's site
The amount and spatial and temporal dynamics of vegetation are important information in environmental studies and agricultural practices. There has been a great deal of interest in estimating vegetation parameters and their spatial and temporal extent using remotely sensed imagery. There are primarily two approaches to estimating vegetation parameters such as leaf area index (LAI). The first one is associated with computation of spectral vegetation indices (SVI) from radiometric measurements. This approach uses an empirical or modeled LAISVI relation between remotely sensed variables such as SVI and biophysical variables such as LAI. The major limitation of this empirical approach is that there is no single LAI-SVI equation (with a set of coefficients) that can be applied to remote-sensing images of different surface types. The second approach involves using bidirectional reflectance distribution function (BRDF) models. It inverts a BRDF model with radiometric measurements to estimate LAI using an optimization procedure. Although this approach has a theoretical basis and is potentially applicable to varying surface types, its primary limitation is the lengthy computation time and difficulty of obtaining the required input parameters by the model. In this study, we present a strategy that combines BRDF models and conventional LAISVI approaches to circumvent these limitations. The proposed strategy was implemented in three sequential steps. In the first step, a BRDF model was inverted with a limited number of data points or pixels to produce a training data set consisting of leaf area index and associated pixel values. In the second step, the training data set passed through a quality control procedure to remove outliers from the inversion procedure. In the final step, the training data set was used either to fit an LAISVI equation or to train a neural fuzzy system.
Reynolds, CA, Yitayew, M, Slack, DC, Hutchinson, CF, Huete, A & Petersen, S 2000, 'Estimating crop yields and production by integrating the FAO Crop Specific Water Balance model with real-time satellite data and groundbased ancillary data', International journal of remote sensing, vol. 21, no. 18, pp. 3487-3508.View/Download from: Publisher's site
An operational crop yield model was developed by introducing realtime satellite imagery into a Geographical Information System (GIS) and the Crop Specific Water Balance (CSWB) model of the Food and Agriculture Organization (FAO). Input databases were developed with three different resolutions; agro-ecological zone (AEZ) polygons, 7.6 km and 1.1 km pixels; from archived satellite data commonly used by Early Warning Systems (EWS) to simulate maize yield and production in Kenya from 1989 to 1997. Simulated production results from the GIS-based CSWB model were compared to historical maize production reports from two Government of Kenya (GoK) agencies. The coefficients of determination (r2) between the model and GoK district reports ranged from 0.86 to 0.89. The results indicated the 7.6 km pixel-by-pixel analysis was the most favorable method due to the Rainfall Estimate (RFE) input data having the same resolution. The GIS-based CSWB model developed by this study could also be easily expanded for use in other countries, extended for other crops, and improved in the future as satellite technologies improve.
Yoshioka, H, Huete, A & Miura, T 2000, 'Derivation of Vegetation Isoline Equations in Red-NIR Reflectance Space', IEEE Transactions on Geoscience and Remote Sensing, vol. 38, no. 2, pp. 838-848.View/Download from: Publisher's site
A technique to derive vegetation isoline equations in red-NIR reflectance space for homogeneous canopies is proposed and demonstrated. A canopy radiative transfer model, known as the Cooper-Smith-Pitts model, is utilized with truncation of the higher order interaction term between the canopy and soil layers. The technique consists of two model simulations, one with a perfect absorber as canopy background and the other with an arbitrary background to estimate the canopy optical properties necessary for the determination of the isoline parameters. These cases are independent of the soil optical properties of any specific site. Hence, the results can be used for any type or series of soils to construct the vegetation isoline equation. A set of simulations was also conducted using the SAIL model to demonstrate the vegetation isoline derivation by the proposed technique. Reflectances and vegetation indices (VI) estimated from the vegetation isoline generally showed good agreement with those simulated by the SAIL model, especially for relatively darker soil. The isoline equation and derivation were found to be useful for further study of two-band VIs and their variation with canopy background
Yoshioka, H, Miura, T, Huete, A & Ganapol, BD 2000, 'Analysis of Vegetation Isolines in Red-NIR Reflectance Space', Remote Sensing Of Environment, vol. 74, pp. 313-326.View/Download from: Publisher's site
The characteristic behavior of red-near-infrared (NIR) reflectance-based vegetation isolines were analyzed by focusing on its three features: the slope, NIR-intercept, and the intersection between the vegetation isoline and the soil line. These properties are the key factors in understanding variations of vegetation index values with changes of canopy background brightness, known as background noise. The analysis was conducted based on a vegetation isoline equation derived by using the representation of canopy reflectance by the adding method. The isoline parameters, slopes, and NIR-intercepts of vegetation isolines were numerically obtained by the SAIL canopy model. Some of the known behaviors of the vegetation isoline were simulated and analyzed in detail.
Sano, EE, Huete, AR & Moran, MS 1999, 'Estimation of surface roughness in a semiarid region from C-band ERS-1 synthetic aperture radar data', Revista Brasileira de Ciência do Solo, vol. 23, no. 4, pp. 903-908.View/Download from: Publisher's site
In this study, we investigated the feasibility of using the C-band European Remote Sensing Satellite (ERS-1) synthetic aperture radar (SAR) data to estimate surface soil roughness in a semiarid rangeland. Radar backscattering coefficients were extracted from a dry and a wet season SAR image and were compared with 47 in situ soil roughness measurements obtained in the rocky soils of the Walnut Gulch Experimental Watershed, southeastern Arizona, USA. Both the dry and the wet season SAR data showed exponential relationships with root mean square (RMS) height measurements. The dry C-band ERS-1 SAR data were strongly correlated (R² = 0.80), while the wet season SAR data have somewhat higher secondary variation (R² = 0.59). This lower correlation was probably provoked by the stronger influence of soil moisture, which may not be negligible in the wet season SAR data. We concluded that the single configuration C-band SAR data is useful to estimate surface roughness of rocky soils in a semiarid rangeland.
van Leeuwen, JD, Huete, A & Laing, TW 1999, 'MODIS Vegetation Index Compositing Approach: A Prototype with AVHRR Data', Remote Sensing Of Environment, vol. 69, no. 3, pp. 264-280.View/Download from: Publisher's site
In this study, the 16-day MODIS (MODerate resolution Imaging Spectroradiometer) vegetation index (VI) compositing algorithm and product were described, evaluated, and compared with the current AVHRR (Advanced Very High Resolution Spectroradiometer) maximum value composite (MVC) approach. The MVC method selects the highest NDVI (normalized difference vegetation index) over a certain time interval. The MODIS VI compositing algorithm emphasizes a global and operational view angle standardization approach: a reflectance-based BRDF (Bidirectional Reflectance Distribution Function) model, succeeded by a back-up MVC algorithm that includes a view angle constraint. A year's worth of daily global AVHRR data was used to prototype the MODIS vegetation index compositing algorithm. The composite scenarios were evaluated with respect to: 1) temporal evolution of the VI for different continents and vegetation types, 2) spatial continuity of the VI, 3) quality flags related to data integrity, cloud cover, and composite method, and 4) view angle distribution of the composited data. On a continental scale, the composited NDVI values from the MODIS algorithm were as much as 30% lower than the mostly, off-nadir NDVI results based on the MVC criterion. The temporal evolution of the NDVI values derived with the MODIS algorithm were similar to the NDVI values derived from the MVC algorithm. A simple BRDF model was adequate to produce nadir equivalent reflectance values from which the NDVI could be computed. Application of the BRDF and back-up components in the MODIS algorithm were dependent on geographic location and season, for example, the BRDF interpolation was most frequently applied in arid and semiarid regions, and during the dry season over humid climate vegetation types. Examples of a MODIS-like global NDVI map and associated quality flags were displayed using a pseudo color bit mapping scheme.
Justice, CO, Vermote, EF, Townshend, JR, Defries, R, Roy, DP, Hall, DK, Salomonson, VV, Privette, JL, Riggs, G, Strahler, A, Lucht, W, Myneni, RB, Knyazikhin, Y, Running, SW, Nemani, RR, Wan, Z, Huete, A, Leeuwen, W, Wolfe, RE, Giglio, L, Muller, J, Lewis, P & Barnsley, MJ 1998, 'The Moderate Resolution Imaging Spectroradiometer (MODIS): Land Remote Sensing for Global Change Research', IEEE Transactions on Geoscience and Remote Sensing, vol. 36, no. 4, pp. 1228-1249.View/Download from: Publisher's site
The first Moderate Resolution Imaging Spectroradiometer (MODIS) instrument is planned for launch by NASA in 1998. This instrument will provide a new and improved capability for terrestrial satellite remote sensing aimed at meeting the needs of global change research. The MODIS standard products will provide new and improved tools for moderate resolution land surface monitoring. These higher order data products have been designed to remove the burden of certain common types of data processing from the user community and meet the more general needs of global-to-regional monitoring, modeling, and assessment. The near-daily coverage of moderate resolution data from MODIS, coupled with the planned increase in high-resolution sampling from Landsat 7, will provide a powerful combination of observations. The full potential of MODIS will be realized once a stable and well-calibrated time-series of multispectral data has been established. In this paper the proposed MODIS standard products for land applications are described along with the current plans for data quality assessment and product validation
Miura, T, Huete, A, van Leeuwen, JD & Didan, K 1998, 'Vegetation detection through smoke-filled A VIRIS images: an assessment using MODIS band passes', Journal Of Geophysical Research-Atmospheres, vol. 103, no. D24, pp. 32001-32011.View/Download from: Publisher's site
Abstract. Radiomelrtcally calibrated, Airborne Visible Infrared Imaging SpectromeIer (AVIRIS) images acquired during the Smoke, Clouds and Radiation in Brazil (SCAR-B) experiment were processed to simulate vegetation index (VI) imagery with the Moderate Resolution Imaging SpectroradiomeIer (MODIS) band passes. Data sets were extracted from tropical forested areas, burned fields, and shrub/grassland areas over both clear and variable smoke conditions wIth average aerosol optical thickness (AOT) values at 0.67 flm of 0.14, 1.1, and 1.9, respectively. The atmospheric resistant VIs and various middle-infrared (MlR) derived Vis were then analyzed with respect to their ability 10 minimize atmospheric "smoke" contamination. The atmospheric resistant VIs utilized the blue band for correction of !he red band, while !he MlR-derived Vis used !he MIR region (1.3 - 2.5 flm) as a substitute for the red band since it is relatively transparent to smoke, yet remains sensitive to green vegetation. The performance of lhese indices were assessed and compared wi!h !he normalized difference vegetation index (NDVI) and !he soil-adjusIed vegetation index (SAVI). Over !he tropical forests !he NDVI and SAVI had high relative errors over all smoke-filled atmospheric conditions (50-80% error), while !he atmospheric resistant VIs resulted in a 50-80% relative error only over thick levels of smoke.
Sano, EE, Huete, AR, Troufleau, D, Moran, MS & Vidal, A 1998, 'Relation between ERS-1 synthetic aperture radar data and measurements of surface roughness and moisture content of rocky soils in a semiarid rangeland', WATER RESOURCES RESEARCH, vol. 34, no. 6, pp. 1491-1498.View/Download from: Publisher's site
Sano, EE, Jiaguo Qi, Huete, AR & Moran, MS 1998, 'The use of SAR/TM synergy for estimating soil moisture content over a semi-arid rangeland', Second Latino-American seminar on radar remote sensing image processing techniques, pp. 175-183.
The C-band ERS-1 SAR data were combined with the Landsat TM data to improve the soil moisture estimates in a semiarid region. The SAR data were compared with the soil moisture measurements at three conditions: a) without any correction for soil roughness and vegetation effects; b) corrected for soil roughness effects; and c) corrected for both soil roughness and vegetation effects. The soil roughness effects were taken into account by using a dry season SAR image. The vegetation influence was considered by using an empirical relationship between SAR and leaf area index data, the latter being derived from TM images. Results indicated that the contribution of soil roughness and vegetation in the radar backscatter were significant and they must be taken into account to obtain accurate soil moisture estimations.
Sano, EE, Moran, MS, Huete, A & Miura, T 1998, 'C- and Multiangle Ku-Band Synthetic Aperture Radar Data for Bare Soil Moisture Estimation in Agricultural Areas', Remote Sensing Of Environment, vol. 64, no. 1, pp. 77-90.View/Download from: Publisher's site
A sensitivity analysis of C-band (5.3 GHz) and Ku-band (14.85 GHz) synthetic aperture radar (SAR) data to the bare soil moisture content of agricultural fields was conducted in this study. The C-band data were obtained with a 23° incidence angle, whereas the Ku-band data were obtained with 35°, 55°, and 75° incidence angles. The fields presented either a small-scale or an intermediate-scale periodic soil roughness components, associated with level-basin and furrow irrigation systems, respectively. For fields with a small-scale roughness component, the SAR data were sensitive to soil moisture, particularly at the C-band with a 23° incidence angle and Ku-band with a 35° incidence angle. For fields with a intermediate-scale roughness component, both C- and Ku-band data were nearly insensitive to soil moisture. By using a theoretical surface scattering model, this study also analyzed the effects of different soil roughness components [root mean square (RMS) height h, correlation length, and periodic row structure] in the SAR data. For fields with RMS height <0.3 cm, a small variation in h (from 0.1 to 0.3 cm) provoked a significant variation in the SAR data (up to 8 dB).
Huete, A, Liu, HQ, Batchily, K & Leeuwen, W 1997, 'A Comparison of Vegetation Indices over a Global Set of TM Images for EOS-MODIS', Remote Sensing Of Environment, vol. 59, pp. 440-451.View/Download from: Publisher's site
A set of Landsat Thematic Mapper images representing a wide range of vegetation conditions from the NASA Landsat Pathfinder, global land cover test site (GLCTS) initiative were processed to simulate the Moderate Resolution Imaging Spectroradiometer (MODIS), global vegetation index imagery at 250 m pixel size resolution. The sites included boreal forest, temperate coniferous forest, temperate deciduous forest, tropical rainforest, grassland, savanna, and desert biomes. Differences and similarities in sensitivity to vegetation conditions were compared among various spectral vegetation indices (VIs). All VIs showed a qualitative relationship to variations in vegetation. However, there were significant differences among the VIs over desert, grassland, and forested biomes. The normalized difference vegetation index (NDVI) was sensitive to and responded primarily to the highly absorbing red reflectance band, while other indices such as the soil and atmosphere resistant vegetation index (SARVI) were more responsive to variations in the near-infrared (NIR) band. As a result, we found the NDVI to mimic red reflectances and saturate over the forested sites while the SARVI, by contrast, did not saturate and followed variations in NIR reflectances. In the arid and semiarid biomes, the NDVI was much more sensitive to canopy background variations than the SARVI. Maximum differences among vegetation index behavior occurred over the evergreen needleleaf forest sites relative to the deciduous broadleaf forests and drier, grassland, and shrub sites. These differences appear to be useful in complementing the NDVI for improved monitoring of vegetation, with the NDVI sensitive to fraction of absorbed photosynthetic active radiation and the SARVI more sensitive to structural canopy parameters such as leaf area index and leaf morphology.
Santibanez, F, Morales, L, la, FJ, Cellier, P & Huete, A 1997, 'Topoclimatic modeling for minimum temperature prediction at a regional scale in the Central Valley of Chile', Agronomy for Sustainable Development, vol. 17, no. 6-7, pp. 307-314.View/Download from: Publisher's site
Spring frost may strongly affect fruit production in the Central Valley of Chile. Minimum temperatures are spatially variable owing to topography and soil conditions. A methodology for forecasting minimum temperature at a regional scale in the Central Valley of Chile, integrating spatial variability of temperature under radiative frost conditions, has been developed. It uses simultaneously a model for forecasting minimum temperatures at a reference station using air temperature and humidity measured at 6 pm, and topoclimatic models, based on satellite infra-red imagery (NOAA/AVHRR) and a digital elevation model, to extend the prediction at a regional scale. The methodological developments were integrated in a geographic information system for georeferencing of a meteorological station with satellite imagery and modeled output. This approach proved to be a useful tool for short range (12 h) minimum temperature prediction by generating thermal images over the Central Valley of Chile. It may also be used as a tool for frost risk assessment, in order to adapt production to local climatological conditions.
van Leeuwen, JD, Huete, A, Walthall, CL, Prince, SD, Begue, A & Roujean, JL 1997, 'Deconvolution of remotely sensed spectral mixtures for retrieval of LAI, fAPAR and soil brightness', Journal Of Hydrology, vol. 188-189, no. 1, pp. 697-724.View/Download from: Publisher's site
Linear mixture models have been used to invert spectral reflectances of targets at the Earth's surface into proportions of plant and soil components. However, operational use of mixture models has been limited by a lack of biophysical interpretation of the results. The main objectives of this study were (1) to relate the deconvolved components of a mixture model with biophysical properties of vegetation and soil at the surface and (2) to apply the mixture model results to remotely sensed imagery. A radiative transfer model (SAIL: Scattering by Arbitrarily Inclined Leaves) was used to generate reflectance `mixtures from leaf and bare soil spectral measurements made at HAPEX-Sahel (Hydrological Atmospheric Pilot EXperiment) study sites. The SAIL model was used to create canopy reflectances and fractions of absorbed photosynthetically active readiation (fAPAR) for a range of mixed targets with varying leaf area index (LAI) and soils. A spectral mixture model was used to deconvolve the simulated reflectance data into component fractions, which were then calibrated to the SAIL-generated LAI, fAPAR and soil brightness. The calibrated relationships were validated with observational ground data (LAI, fAPAR and reflectance) measured at the HAPEX Sahel fallow bush/grassland, fallow grassland and millet sites. Both the vegetation and soil component fractions were found to be dependent upon soil background brightness, such that inclusion of the soil fraction information significantly improved the derivation of vegetation biophysical parameters. Soil brightness was also shown to be a useful parameter to infer soil properties.
Bannari, A, Huete, A, Morin, D & Zagolski, F 1996, 'Effects de la couleur et de la brillance du sol les indices de vegetation', International journal of remote sensing, vol. 17, no. 10, pp. 1885-1906.View/Download from: Publisher's site
Variations in the spectral properties of soils related to their colour and brightness considerably influence the detection of sparse vegetation in heterogeneous environments using vegetation indices. During the last decade, a new generation of vegetation indices (NDVI, PVI, SAVI, MSAVI, TSAVI, TSARVI, ARVI, GEMI, and AVI) was developed in order to minimize these effects. To evaluate the sensitivity of these indices to soil colour and brightness and to test their potential for a more precise description of the vegetation cover for different cover rates, a number of simulations were carried out using a first order radiative transfer model. The model was adapted for studying directly the contribution of the optical properties of bare soils on the vegetation index. The results show that the first order radiative transfer model constitutes a valuable tool for analysing and understanding the interactions between the electromagnetic radiation, the vegetation cover and bare soil. It makes it possible to analyse the effect of colour and brightness on the reflectance factor and, consequently, on the vegetation index. The GEMI, AVI, NDVI, ARVI and PVI indices show lower performance for the management of sparse or moderately dense vegetation environments. They are marked by non-negligible errors related to the optical properties of bare soils. The AVI leads to results that do not reflect the theoretical behaviour of vegetation indices. As to the TSAVI, TSARVI, SAVI and MSAVI indices, they are more resistant to changes in the optical properties of soils and permit better discrimination between the vegetation from the bare soil background in an heterogeneous and relatively complex environment.
Bannari, A, Huete, AR, Morin, D & Zagolski, F 1996, 'Effects of soil color and brightness on vegetation indexes', INTERNATIONAL JOURNAL OF REMOTE SENSING, vol. 17, no. 10, pp. 1885-1906.View/Download from: Publisher's site
Bannari, A, Huete, AR, Morin, D & Zagolski, F 1996, 'Effets de la couleur et de la brillance du sol sur les indices de végétation', International Journal of Remote Sensing, vol. 17, no. 10, pp. 1885-1906.View/Download from: Publisher's site
Variations in the spectral properties of soils related to their colour and brightness considerably influence the detection of sparse vegetation in heterogeneous environments using vegetation indices. During the last decade, a new generation of vegetation indices (NDVI, PVI, SAVI, MSAVI, TSAVI, TSARVI, ARVI, GEMI, and AVI) was developed in order to minimize these effects. To evaluate the sensitivity of these indices to soil colour and brightness and to test their potential for a more precise description of the vegetation cover for different cover rates, a number of simulations were carried out using a first order radiative transfer model. The model was adapted for studying directly the contribution of the optical properties of bare soils on the vegetation index. The results show that the first order radiative transfer model constitutes a valuable tool for analysing and understanding the interactions between the electromagnetic radiation, the vegetation cover and bare soil. It makes it possible to analyse the effect of colour and brightness on the reflectance factor and, consequently, on the vegetation index. The GEMI, AVI, NDVI, ARVI and PVI indices show lower performance for the management of sparse or moderately dense vegetation environments. They are marked by non-negligible errors related to the optical properties of bare soils. The AVI leads to results that do not reflect the theoretical behaviour of vegetation indices. As to the TSAVI, TSARVI, SAVI and MSAVI indices, they are more resistant to changes in the optical properties of soils and permit better discrimination between the vegetation from the bare soil background in an heterogeneous and relatively complex environment. © 1996 Taylor & Francis Ltd.
Begue, A, Roujean, JL, Hanan, NP, Prince, SD, Thawley, M, Huete, A & Tanre, D 1996, 'Shortwave radiation budget of Sahelian vegetation 1. Techniques of measurement and results during HAPEX-Sahel', Agricultural and Forest Meteorology, vol. 79, no. 1-2, pp. 79-96.View/Download from: Publisher's site
Shortwave radiative budgets of Sahelian savannas and a millet crop were measured during the 1992 HAPEX-Sahel field experiment, in Niger, West Africa. Measurements were conducted on four land cover types: shrub fallow, grass fallow, degraded shrubland, and a millet field. Each land unit was equipped with sets of sensors to measure the photosynthetically active radiation (PAR) and near-infrared (NIR) radiative fluxes within the canopies, and were operated throughout the entire growing season. Daily fractional PAR and NIR interception by vegetation was rather low (less than 60% and 30% for natural vegetation and crop, respectively). The sparse vegetation and bright sandy soils meant that the PAR absorption and interception were similar (they were equal at a value of approximately 20%). The albedo of the plots varied little diurnally and seasonally, and was strongly affected by the reflection from the soil. The interception and absorption and, to a lesser degree, the albedo exhibited distinct directional effects related to solar zenith angle.
van Leeuwen, JD & Huete, A 1996, 'Effects of Standing Litter on the Biophysical Interpretation of Plant Canopies with Spectral Indices', Remote Sensing Of Environment, vol. 55, no. 2, pp. 123-138.View/Download from: Publisher's site
Litter is frequently present within vegetation canopies and thus contributes to the overall spectral response of a canopy. Consequently, litter will affect spectral indices designed to be sensitive to green vegetation, soil brightness or other features. The main objectives of the current research were to 1) evaluate the spectral properties of green vegetation and litter and 2) quantify the effect of standing litter on the performance of spectral indices. The SAIL (scattering by arbitrarily inclined leaves) model was used to generate canopy reflectance mixtures and to estimate fractions of absorbed photosynthetically active radiation (fAPAR) with varying leaf area index (LAI), soil background, combinations of vegetation component spectral properties, and one or two horizontal vegetation layers. Spectral measurements of different bare soils and mature green and senescent leaves of representative plant species at the HAPEX-Sahel (Hydrological Atmospheric Pilot Experiment) study sites were used as input. The normalized difference vegetation index (NDVI), the soil adjusted vegetation index (SAVI), and the modified NDVI (MNDVI) and mixture model spectral indices were selected to evaluate their performance with respect to standing litter and green vegetation mixtures. Spectral reflectance signatures of leaf litter varied significantly, but strongly resembled soil spectral characteristics. The biophysical phyameters (LAI, fAPAR), derived from spectral vegetation indices, tended to be overestimated for randomly distributed, sparse green and litter vegetation cover mixtures, and underestimated for randomly distributed dense green and litter vegetation cover mixtures.
In the field of remote sensing applications, scientists have developed vegetation indices (VI) for qualitatively and quantitatively evaluating vegetative covers using spectral measurements. The spectral response of vegetated areas presents a complex mixture of vegetation, soil brightness, environmental effects, shadow, soil color and moisture. Moreover, the VI is affected by spatial-temporal variations of the atmosphere. Over forty vegetation indices have been developed during the last two decades in order to enhance vegetation response and minimize the effects of the factors described above. This paper summarizes, refers and discusses most of the vegetation indices found in the literature. It presents different existing classifications of indices and proposes to group them in a new classification.
Epiphanio, JC & Huete, A 1995, 'Dependence of NDVI and SAVI on Sun/Sensor Geometry and Its Effect on fAPAR Relationships in Alfalfa', Remote Sensing Of Environment, vol. 51, no. 3, pp. 351-360.View/Download from: Publisher's site
This article describes the impacts of sensor view and solar zenith angles on two vegetation indices -NDVI (normalized difference vegetation index) and SAVI (soil adjusted vegetation index). An evaluation of these geometric factors on the relationships between these VIs (vegetation indices) and fAPAR (fraction of photosynthetically active radiation absorbed by the canopy) was performed. To accomplish this, an experiment was conducted in Phoenix, Arizona, over plots of bare soil and low, medium, and high alfalfa. Reflectances were measured from 0.4 ?m to 1.0 ?m in nine view angles (from -40° to + 40°, in 10° steps) over varying solar zenith angles. This was done simultaneously with fAPAR measurements. Changes in view angle caused variations in the indices to be as high as 50% in relation to nadir. However, there was an opposite view angle behavior between NDVI and SAVI, with the former increasing from antisolar to forward scattering view direction. A derivative analysis of the indices showed the SAVI to exhibit a more linear relationship than NDVI with the individual bands. The relationships between both VIs and fAPAR were, in general, linear. However, view angle variations perturbed these relationships and caused an over- or underestimation of fAPAR, depending on view direction (antisolar or forward), view angle, and vegetation index (NDVI or SAVI).
Liu, HQ & Huete, A 1995, 'A Feedback Based Modification of the NDVI to Minimize Canopy Background and Atmospheric Noise', IEEE Transactions on Geoscience and Remote Sensing, vol. 33, no. 2, pp. 457-465.
The Normalized Difference Vegetation Index (NDVI) equation has a simple, open loop structure (no feedback), which renders it susceptible to large sources of error and uncertainty over variable atmospheric and canopy background conditions. In this study, a systems analysis approach is used to examine noise sources in existing vegetation indices (VIs) and to develop a stable, modified NDVI (MNDVI) equation. The MNDVI, a closed-loop version of the NDVI, was constructed by adding 1) a soil and atmospheric noise feedback loop, and 2) an atmospheric noise compensation forward loop. The coefficients developed for the MNDVI are physically-based and are empirically related to the expected range of atmospheric and background boundary conditions. The MNDVI can be used with data uncorrected for atmosphere, as well as with Rayleigh corrected and atmospherically corrected data. In the field observational and simulated data sets tested, the MNDVI was found to considerably reduce noise for any complex soil and atmospheric situation. The resulting uncertainty, expressed as vegetation equivalent noise, was ±0.11 leaf area index (LAI) units, which was 7 times less than encountered with the NDVI (±0.8 LAI). These results indicate that the MNDVI may be satisfactory in meeting the need for accurate, long term vegetation measurements for the Earth Observing System (EOS) program
CHEHBOUNI, A, KERR, YH, QI, J, HUETE, AR & SOROOSHIAN, S 1994, 'TOWARD THE DEVELOPMENT OF A MULTIDIRECTIONAL VEGETATION INDEX', WATER RESOURCES RESEARCH, vol. 30, no. 5, pp. 1281-1286.View/Download from: Publisher's site
Franklin, J, Duncan, J, Huete, A, van Leeuwen, JD, Li, X & Begue, A 1994, 'Radiative transfer in shrub savanna sites in Niger: preliminary results from HAPEX-Sahel. 1. Modelling surface reflectance using a geometric-optical approach', Agricultural and Forest Meteorology, vol. 69, no. 3-4, pp. 223-245.View/Download from: Publisher's site
To use optical remote sensing to monitor land surface-climate interactions over large areas, algorithms must be developed to relate multispectral measurements to key variables controlling the exchange of matter (water, carbon dioxide) and energy between the land surface and the atmosphere. The proportion of the ground covered by vegetation and the interception of photosynthetically active radiation (PAR) by vegetation are examples of two variables related to evapotranspiration and primary production, respectively. An areal-proportion model of the multispectral reflectance of shrub savanna, composed of scattered shrubs with a grass, forb or soil understory, predicted the reflectance of two 0.5 km2 sites as the area-weighted average of the shrub and understory or `background reflectances. Although the shaded crown and shaded background have darker reflectances, ignoring them in the area-weighted model is not serious when shrub cover is low and solar zenith angle is small. A submodel predicted the reflectance of the shrub crown as a function of the foliage reflectance and amount of plant material within the crown, and the background reflectance scattered or transmitted through canopy gaps (referred to as a soilplant `spectral interaction term). One may be able to combine these two models to estimate both the fraction of vegetation cover and interception of PAR by green vegetation in a shrub savanna.
Huete, A & Liu, HQ 1994, 'An Error and Sensitivity Analysis of the Atmospheric- and Soil-Correcting Variants of the NDVI for the MODIS-EOS', Invalid Code, vol. 32, no. 4, pp. 897-905.
This publication focuses on the theory, concepts, and techniques of science and engineering as applied to sensing the earth, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information. This journal publishes technical papers disclosing new and significant research.
One of the primary interests of the NASA Earth Observing System (EOS) program is to study the role of vegetation in biospheric processes. Currently, the normalized difference vegetation index (NDVI) is utilized to study and monitor vegetation activity on an operational basis at global scales. Recently developed variants to the NDVI equation, based on improved knowledge of atmosphere, canopy background, and sensor-view geometry, are being considered for use with the EOS Moderate-Resolution Imaging Spectrometer (MODIS) sensor. A set of criteria is established to evaluate their performance with respect to the vegetation signal and atmospheric and soil sources of noise. These include the vegetation signal-to-noise ratio (S/N), % relative error, and vegetation equivalent noise (VEN), which form the basis for the evaluation and comparison of vegetation indices (VIs) across a wide range in vegetation covers. The NDVI variant equations outperformed the NDVI by minimizing atmospheric and/or soil background sources of contamination as well as increasing vegetation signal sensitivity. Preliminary estimates, based on the data sets tested here, indicate an overall level of uncertainty of ± 0.4 LAI (? 15% cover) with the use of the soil adjusted and atmospherically resistant vegetation index (SARVI), compared with ± 0.8 LAI (30% cover) for the NDVI. Eventually, the final evaluation and validation of VIs for MODIS will include a field campaign strategy, simulation studies, and a worldwide establishment of test sites that collectively cover a diverse range of biomes. Lastly, the retrieval of canopy biophysical information from these VIs are discussed.
PINKER, RT, KUSTAS, WP, LASZLO, I, MORAN, MS & HUETE, AR 1994, 'BASIN-SCALE SOLAR IRRADIANCE ESTIMATES IN SEMIARID REGIONS USING GOES 7', WATER RESOURCES RESEARCH, vol. 30, no. 5, pp. 1375-1386.View/Download from: Publisher's site
Qi, J, Chehbouni, A, Huete, A, Kerr, YH & Sorooshian, S 1994, 'A Modified Soil Adjusted Vegetation Index', Remote Sensing Of Environment, vol. 48, no. 2, pp. 119-126.View/Download from: Publisher's site
There is currently a great deal of interest in the quantitative characterization of temporal and spatial vegetation patterns with remotely sensed data for the study of earth system science and global change. Spectral models and indices are being developed to improve vegetation sensitivity by accounting for atmosphere and soil effects. The soil-adjusted vegetation index (SAVI) was developed to minimize soil influences on canopy spectra by incorporating a soil adjustment factor L into the denominator of the normalized difference vegetation index (NDVI) equation. For optimal adjustment of the soil effect, however, the L factor should vary inversely with the amount of vegetation present. A modified SAVI (MSAVI) that replaces the constant L in the SAVI equation with a variable L function is presented in this article. The L function may be derived by induction or by using the product of the NDVI and weighted difference vegetation index (WDVI). Results based on ground and aircraft-measured cotton canopies are presented. The MSAVI is shown to increase the dynamic range of the vegetation signal while further minimizing the soil background influences, resulting in greater vegetation sensitivity as defined by a vegetation signal to soil noise ratio.
QI, J, HUETE, AR, CABOT, F & CHEHBOUNI, A 1994, 'BIDIRECTIONAL PROPERTIES AND UTILIZATIONS OF HIGH-RESOLUTION SPECTRA FROM A SEMIARID WATERSHED', WATER RESOURCES RESEARCH, vol. 30, no. 5, pp. 1271-1279.View/Download from: Publisher's site
Running, SW, Justice, CO, Salomonson, VV, Hall, D, Barker, J, Kaufmann, YJ, Strahler, AH, Huete, A, Muller, JP, Vanderbilt, V, Wan, ZM, Teillet, P & Carneggie, D 1994, 'Terrestrial remote sensing science and algorithms planned for EOS/MODIS', International journal of remote sensing, vol. 15, no. 17, pp. 3587-3620.View/Download from: Publisher's site
The Moderate Resolution Imaging Spectroradiometer (MODIS) will be the primary daily global monitoring sensor on the NASA Earth Observing System (EOS) satellites, scheduled for launch on the EOS-AM platform in June 1998 and the EOS-PM platform in December 2000. MODIS is a 36 channel radiometer covering 0·415-14·235 ?m wavelengths, with spatial resolution from 250 m to 1 km at nadir. MODIS will be the primary EOS sensor for providing data on terrestrial biospheric dynamics and process activity. This paper presents the suite of global land products currently planned for EOSDIS implementation, to be developed by the authors of this paper, the MODIS land team (MODLAND). These include spectral albedo, land cover, spectral vegetation indices, snow and ice cover, surface temperature and fire, and a number of biophysical variables that will allow computation of global carbon cycles, hydrologic balances and biogeochemistry of critical greenhouse gases. Additionally, the regular global coverage of these variables will allow accurate surface change detection, a fundamental determinant of global change.
van Leeuwen, JD, Huete, A, Duncan, J & Franklin, J 1994, 'Radiative transfer in shrub savanna sites in Niger: preliminary results from HAPEX-Sahel. 3. Optical dynamics and vegetation index sensitivity to biomass and plant cover', Agricultural and Forest Meteorology, vol. 69, no. 3-4, pp. 267-288.View/Download from: Publisher's site
A shrub savannah landscape in Niger was optically characterized utilizing blue, green, red and near-infrared wavelengths. Selected vegetation indices were evaluated for their performance and sensitivity to describe the complex Sahelian soil/vegetation canopies. Bidirectional reflectance factors (BRF) of plants and soils were measured at several view angles, and used as input to various vegetation indices. Both soil and vegetation targets had strong anisotropic reflectance properties, rendering all vegetation index (VI) responses to be a direct function of sun and view geometry. Soil background influences were shown to alter the response of most vegetation indices. N-space greenness had the smallest dynamic range in VI response, but the n-space brightness index provided additional useful information. The global environmental monitoring index (GEMI) showed a large VI dynamic range for bare soils, which was undesirable for a vegetation index. The view angle response of the normalized difference vegetation index (NDVI), atmosphere resistant vegetation index (ARVI) and soil atmosphere resistant vegetation index (SARVI) were asymmetric about nadir for multiple view angles, and were, except for the SARVI, altered seriously by soil moisture and/or soil brightness effects. The soil adjusted vegetation index (SAVI) was least affected by surface soil moisture and was symmetric about nadir for grass vegetation covers. Overall the SAVI, SARVI and the n-space vegetation index performed best under all adverse conditions and were recommended to monitor vegetation growth in the sparsely vegetated Sahelian zone.
Qi, J, Huete, A, Moran, MS, Chehbouni, A & Jackson, RD 1993, 'Interpretation of Vegetation Indices Derived from Multi-temporal SPOT Images', Remote Sensing Of Environment, vol. 44, no. 1, pp. 89-101.View/Download from: Publisher's site
A temporal sequence of 15 SPOT HRV images and low altitude aircraft reflectance data were obtained over soil and cotton fields at the Maricopa Agricultural Center, Arizona from April to October 1989. The SPOT data included different view angles (- 28° - + 24°) while the aircraft data were obtained with a nadir-viewing radiometer equipped with SPOT filters. View angle/direction, atmosphere, and soil influences on individual band and vegetation indices were observed in the SPOT data. The relative magnitude among the three influences was dependent on surface conditions, varied with canopy growth, and was different for red and near-infrared (NIR) reflectances and vegetation indices (VIs). View angle effects were most pronounced in red and NIR reflectance data and were secondary with the use of VIs. View angle variations, and to some extent soil variations, influenced VI responses from partial canopies while relative atmospheric influences became most dominant at higher densities of vegetation. The results suggest that the current compositing routine for temporal vegetation index imagery may not be entirely adequate.
Huete, A, Hua, G, Qi, J, Chehbouni, A & van Leeuwen, JD 1992, 'Normalization of Multidirectional Red and NIR Reflectances with the SAVI', Remote Sensing Of Environment, vol. 41, no. 2-3, pp. 143-154.View/Download from: Publisher's site
Directional reflectance measurements were made over a semidesert gramma (Bouteloua spp.) grassland at various times of the growing season. Azimuthal strings of view angle measurements from + 40° to - 40° were made for various solar zenith angles and soil moisture conditions. The sensitivity of the normalized difference vegetation index (NDVI) and the soil-adjusted vegetation index (SAVI) to these bidirectional measurements was assessed for purposes of improving remote temporal monitoring of vegetation activity. The NDVI response from the grassland canopy was strongly anisotropic about nadir view angles while the SAVI response was symmetric about nadir. This occurred for all sun angles, soil moisture condition, and grass densities. This enabled variations in SAVI-view angle response to be minimized with a cosine function. It is expected that this study will aid in improving the characterization of vegetation temporal activity from Landsat TM, SPOT, AVHRR, and the Earth Observing System MODIS sensor.
ESCADAFAL, R & HUETE, A 1991, 'IMPROVEMENT IN REMOTE-SENSING OF LOW VEGETATION COVER IN ARID REGIONS BY CORRECTING VEGETATION INDEXES FOR SOIL NOISE', COMPTES RENDUS DE L ACADEMIE DES SCIENCES SERIE II, vol. 312, no. 11, pp. 1385-1391.
Huete, A & Escadafal, R 1991, 'Assessment of Biophysical Soil Properties Through Spectral Decomposition Techniques', Remote Sensing Of Environment, vol. 35, no. 2-3, pp. 149-159.View/Download from: Publisher's site
A mixture model was utilized to extract soil biophysical properties from fine resolution soil spectra (400900 nm) measured outdoors with a portable spectroradiometer. The objective of this study was to fully characterize soil spectral signatures in the visible and near-infrared in terms of underlying basis curves, key wavelengths, and dimensionality. Through spectral decomposition and mixture modeling, the reflectance response of a wide, genetic range of soil materials were separated into four independent sources of spectral variability (basis curves), which in linear combination were able to reconstitute the experimental data set. Stepwise spectral reconstruction was then utilized to isolate organic carbon and free iron oxide basis curves. This enabled a good global measure of soil properties irrespective of soil type or brightness. We anticipate the EOS-MODIS and HIRIS sensors to provide the spectral data needed for inversion of satellite data into soil surface properties and processes.
Huete, A & Tucker, CJ 1991, 'Investigation of soil influences in AVHRR red and near-infrared vegetation index imagery', International journal of remote sensing, vol. 12, no. 6, pp. 1223-1242.View/Download from: Publisher's site
The effects of soil optical properties on vegetation index imagery are analysed with ground-based spectral measurements and both simulated and actual AVHRR data from the NOAA satellites. Soil effects on vegetation indices were divided into primary variations associated with the brightness of bare soils, secondary variations attributed to 'colour' differences among bare soils, and soil-vegetation spectral mixing. Primary variations were attributed to shifts in the soil line owing to atmosphere or soil composition. Secondary soil variance was responsible for the Saharan desert 'artefact' areas of increased vegetation index response in AVHRR imagery. The impact of soil effects is discussed with a transect of vegetation index data derived from NOAA data from desert to equatorial forest.
Remotely sensed spectral vegetation indices are widely used and have benefited numerous disciplines interested in the assessment of biomass, water use, plant stress, plant health and crop production. The successful use of these indices requires knowledge of the units of the input variables used to form the indices, and an understanding of the manner in which the external environment and the architectural aspects of a vegetation canopy influence and alter the computed index values. Although vegetation indices were developed to extract the plant signal only, the soil background, moisture condition, solar zenith angle, view angle, as well as the atmosphere, alter the index values in complex ways. The nature of these problems are explored both in an empirical and in a theoretical sense, and suggestions are offered for the effective use and interpretation of vegetation indices.
Kustas, WP, Goodrich, DC, Moran, MS, Amer, SA, Bach, LB, Blanford, JH, Chehbouni, A, Claassen, H, Clements, WE, Doraiswamy, PC, Dubois, P, Clarke, TR, Daughtry, CS, Gellman, DI, Grant, TA, Hipps, LE, Huete, A, Humes, KS, Jackson, TJ, Keefer, TO, Nichols, WD, Parry, R, Perry, EM, Pinker, RT, Pinter, JPJ, Qi, J, Riggs, AC, Schmugge, TJ, Shutko, AM, Stannard, DI, Swiatek, E, van, LJD, Zyl, J, Vidal, A, Washburne, J & Weltz, MA 1991, 'An Interdisciplinary field study of the energy and water fluxes in the atmosphere-biosphere system over semiarid rangelands: Description and some preliminary results', Bulletin American Meteorological society, vol. 72, no. 11, pp. 1683-1705.View/Download from: 2.0.CO;2">Publisher's site
Arid and semiarid rangelands comprise a significant portion of the earth's land surface. Yet little is known about the effects of temporal and spatial changes in surface soil moisture on the hydrologic cycle, energy balance, and the feedbacks to the atmosphere via thermal forcing over such environments. Understanding this interrelationship is crucial for evaluating the role of the hydrologic cycle in surface-atmosphere interactions. This study focuses on the utility of remote sensing to provide measurements of surface soil moisture, surface albedo, vegetation biomass, and temperature at different spatial and temporal scales. Remote-sensing measurements may provide the only practical means of estimating some of the more important factors controlling land surface processes over large areas. Consequently, the use of remotely sensed information in biophysical and geophysical models greatly enhances their ability to compute fluxes at catchment and regional scales on a routine basis. However, model calculations for different climates and ecosystems need verification. This requires that the remotely sensed data and model computations be evaluated with ground-truth data collected at the same areas scales. The present study (MONSOON 90) attempts to address this issue for semiarid rangelands. The experimental plan included remotely sensed data in the visible, near-infrared, thermal, and microwave wavelengths from ground and aircraft platforms and, when available, from satellites. Collected concurrently were ground measurements of soil moisture and temperature, energy and water fluxes, and profile data in the atmospheric boundary layer in a hydrologically instrumented semiarid rangeland watershed. Field experiments were conducted in 1990 during the dry and wet or monsoon season for the southwestern United States. A detailed description of the field campaigns, including measurements and some preliminary results are given.
Huete, A & Warrick, AW 1990, 'Assessment of Vegetation and Soil Water Regimes in Partial Canopies with Optical Remotely Sensed Data', Remote Sensing Of Environment, vol. 32, no. 2-3, pp. 155-167.View/Download from: Publisher's site
The optical properties of a partially vegetated cotton field with spatially and temporally dynamic soil water conditions were analyzed with coincident aircraft and satellite data. The study was conducted at the Maricopa Agricultural Center in Arizona during June 1988. The dynamics of soil surface drying made it difficult to evaluate plant cover and assess soil condition with combined thermal, brightness, and normalized difference vegetation index (NDVI) spectral parameters as all three parameters were sensitive to the three stages of soil drying. A soil-adjusted vegetation index (SAVI) minimized both spatial and temporal variations in soil spectral behavior and was found useful in vegetation analysis and in further qualitative assessment of soil condition. Due to the complex dynamics of soil surface drying and variability in soil properties, soil water content at the surface (0 5 cm) could not be determined with the Thematic Mapper moisture bands, or with the various wetness indicators.
Levitt, DG, Simpson, JR & Huete, A 1990, 'Estimates of Surface Soil Water Content Using Linear Combinations of Spectral Wavebands', Theoretical and Applied Climatology, vol. 42, no. 4, pp. 245-252.View/Download from: Publisher's site
Surface reflectance factors from bare field soil were measured to determine the relationship between surface soil water content and spectral reflectance. Reflectance in the six reflective Thematic Mapper (TM) bands plus a 1.15 to 1.30 µm bandpass (referred to as MMR 5) was measured using a groundbased radiometer across a soil water gradient provided by a line source sprinkler system. A spectral index of soil brightness (Brightness) derived using the Gram-Schmidt process and utilizing reflectance information was calculated for each band and for combinations of bands. The results of this study show that TM band 7 (2.052.30 µm) provided improved estimates of surface soil water content (00.5 cm depth) over estimates using reflectance information from all seven bands. Good correlations were also found between band ratio spectral indices of TM 5 (1.551.75 µm) / TM 7, MMR 5/TM 7, and MMR 5/TM 5 and surface soil water content. Results indicate that surface reflectance factors within bandpasses that partially overlap water absorption regions, such as TM 7, are most highly correlated with surface soil moisture. Band ratios utilizing a bandpass partially overlapping a water absorption region such as TM 7 and a non-water-absorbing bandpass such as MMR 5 yield close correlations with surface soil water content.
A transformation technique is presented to minimize soil brightness influences from spectral vegetation indices involving red and near-infrared (NIR) wavelengths. Graphically, the transformation involves a shifting of the origin of reflectance spectra plotted in NIR-red wavelength space to account for first-order soil-vegetation interactions and differential red and NIR flux extinction through vegetated canopies. For cotton (Gossypium hirsutum L. var DPI-70) and range grass (Eragrosticslehmanniana Nees) canopies, underlain with different soil backgrounds, the transformation nearly eliminated soil-induced variations in vegetation indices. A physical basis for the soil-adjusted vegetation index (SAVI) is subsequently presented. The SAVI was found to be an important step toward the establishment of simple °lobal that can describe dynamic soil-vegetation systems from remotely sensed data.
An atmospheric radiant transfer model was used to compare ground-measured radiances over partially vegetated canopies with their simulated responses at the top of a clear (100 km meteorological range) and a turbid (10 km) atmosphere. Radiance measurements in the first four bands of the Thematic Mapper were taken over incomplete cotton (Gossypium hirsutum L.) and Lehmann lovegrass (Eragrostis lehmanniana Nees) canopies with different soil backgrounds separately inserted underneath. Atmospheric influences on the spectra of partial canopies were found to be significantly dependent on the brightness of the underlying soil. The change in canopy red and near-infrared radiance between the ground and the top of the atmosphere was such that an increase, decrease, or no change could be observed, depending on the magnitude of the canopy substrate contribution. Both increasing soil brightness and atmospheric turbidity lowered the ratio (RVI) and normalized difference vegetation index values (NDVI). Consequently, atmospheric-induced RVI and NDVI degradation were greatest over canopies with darker soils and were not detectable over canopies with light-colored soils. In contrast, soil and atmospheric effects on the perpendicular vegetation index were independent with atmosphere degradation being similar across all soil backgrounds. Soil influences on vegetation indices from partial canopies were found to be of similar magnitude to those attributed to the atmosphere for the range of soil and atmosphere conditions examined here.
The spectral behaviour of an incomplete cotton canopy was analysed in relation to solar zenith angle and soil background variations. Soil and vegetation spectral contributions towards canopy response were separated using a first-order interactive model and consequently used to compare the relative sensitivity of canopy spectra to soil background and solar angle differences. Canopy reflectance behaviour with solar angle increased, decreased or remained invariant depending on the reflectance properties of the underlying soil. Sunlit and shaded soil contributions were found to alter vegetation index behaviour significantly over different Sun angles.
Amajor problem in the use of remote sensing techniques to assess plant biomass and condition over incomplete canopies concerns the soil background contribution toward measured spectral response. An understanding of this soil signal is essential 10 better relate canopy spectra with plant properties. An interactive, plant-soil radiant flux model was developed to separate spectral variations associated with soil background from those attrlbutable to vegetation. Field measured spectra taken over It developing cotton (Gossypinm hirsutum L.) canopy with four soil types (Cumnlic Cryoboroll, Typic TorriHuvent, Ustollic Haplargid, and Typic Calciorthid) alternately inserted underneath were decomposed into soil and vegetation spectra by utilizing the model in It principal component analysis. The soil component included all radiation penetrating the canopy and inter~ acting with the underlying soil. The vegetation compOnent repre· seoted all radiation reflected directly from the plant tover with no soil interaction. The soil component was found to resemble the spectral response of green vegetation due to the scattering and trans-mittance properties of the overlying plant canopy. Results show how the soil signal mixes into various vegetation indices inhibiting reliable vegetation discrimination. The potential improvements in veg· etation analysis that can result from filtering soil background response from planHanopy spectra are also discussed.
Huete, A & Jackson, RD 1987, 'Suitability of Spectral Indices for Evaluating Vegetation Characteristics on Arid Rangelands', Remote Sensing Of Environment, vol. 23, no. 2, pp. 213-232.View/Download from: Publisher's site
The spectral behavior of an arid, Lehmann lovegrass (Eragrostis lehmanniana), range canopy with varying quantities of live, green grass, senesced, yellow grass, weathered, gray litter, and different soil backgrounds was analyzed with a ground based radiometer. The analysis included rangeland field plots and artificial mixtures of live and dead grass. Senesced grass and weathered litter were found to significantly alter the spectral response of the range canopy in the first four Thematic Mapper wavebands (0.450.52; 0.520.60; 0.630.69; 0.760.90 ?m). These influences seriously hampered the utility of spectral vegetation indices in assessing green phytomass levels. Gray litter lowered the response of the green vegetation index (GVI) and perpendicular vegetation index (PVI) while minimally influencing the ratio vegetation index (RVI) and the normalized difference vegetation index (NDVI). Yellow, senesced grass increased the greenness response of plots without green vegetation and decreased the greenness response of plots with green vegetation. Higher reflecting soils increased the GVI and PVI response and decreased the RVI and NDVI response of comparable range canopy mixtures. Small amounts of 30 cm tall, green grass (750 kg/ha) could not be detected within a 75 cm tall, senesced grass stand (5000 kg/ha). The results of this study show spectral vegetation indices to be unreliable measures of green phytomass in arid rangelands. A mixture model employing principal component analysis was used to extract a green vegetation signal, but green phytomass detection was not improved. Apparently, the green vegetation signal emerging from range canopies is diminished by the scattering influences of the vertically oriented elements of the senesced grass phytomass.
A factor-analytic inversion model is presented which enables a data set of spectral mixtures to be decomposed into the sum of unique reflecting components weighted by their corresponding amounts. Spectral mixtures are decomposed into abstract eigenspectra and eigenvector matrices. The eigenspectra are then transformed into pure component spectral signatures through a target testing procedure that allows one to individually search for the presence of ground reflecting features. Soil-plant mixtures with variable soil moisture and plant densities were successfully decomposed into dry soil, wet soil, and vegetation components and their respective amounts in all spectral mixtures were determined. Potential uses of factor analysis in soil identification and biomass assessment are discusse
Post, DF, Huete, A & Pease, DS 1986, 'A comparison of soil scientist estimations and laboratory determination of some Arizona soil properties', Journal of soil and water conservation, vol. 41, no. 6, pp. 421-424.
Samples of representative Arizona soils were sent to 36 soil scientists who were asked to estimate the sand, silt, and clay percentage; organic matter percentage; cation exchange capacity; carbonate content; and wilting point of each soil. These estimates were then correlated with laboratory analyses of these soils. The mean correlation coefficients for the individual estimations were highest for sand and clay (.88 and .86) and lowest for percent carbonates and cation exchange capacity (.56 and .65). Linear regression equation slopes and intercepts for all estimates differ from 1 and 0, respectively, indicating the absolute agreements were in error. Coefficients of variation show how estimates varied among soil scientists. Information about the soil scientists' degree of confidence, their estimations, and their performance also are presented
HUETE, AR, JACKSON, RD & POST, DF 1985, 'SPECTRAL RESPONSE OF A PLANT CANOPY WITH DIFFERENT SOIL BACKGROUNDS', REMOTE SENSING OF ENVIRONMENT, vol. 17, no. 1, pp. 37-53.View/Download from: Publisher's site
Huete, A & Mc Coll, JG 1984, 'Soil Cation leaching by "Acid Rain" with Varying Nitrate-to-Sulfate Ratios', Journal of Environmental Quality, vol. 13, no. 3, pp. 366-371.View/Download from: Publisher's site
The influence of soil background on vegetation discrimination in four-band reflectance space was examined. Dry and wet reflectance data were obtained for 20 soils covering a wide range in spectral properties with a hand-held radiometer. Principal components analysis was used to study the distribution of soil spectra in 4-space and to define a mean soil line. Soil-specific background lines were similarly derived and used to examine the overall cloud of soil spectra in individual soil form. Reflectance data from a full-canopy wheat plot were used to compute unit vector coefficients in the greenness direction from the mean soil line and from the individual soil lines. Analysis of the mean soil line showed that it was not possible to discriminate bare soil from low vegetation densities. Greenness measurements were shown to be sensitive to both soil type and soil moisture condition. In contrast, the use of individual soil lines as a base to measure greenness minimized soil background influence and improved vegetation assessment, particularly at low green plant canopy covers
Miller, TE, Wing, JS & Huete, A 1984, 'The agricultural potential of selected C4 plants in arid environments', Journal Of Arid Environments, vol. 7, no. 1, pp. 275-286.
Due to the increasing amount of dry lands in the world, C4 plants which are highly efficient in water use need to be investigated as potential crop species. This study examined the arid-land agricultural potential ofseveral specific C4 species: Amaramhus hypochondriacus, Amaranthus retrOjlexus, and Portulaca oleracea. Germination responses of each species to both temperature and moisture were determined in growth chambers and contrasted with the response of two C3 species, Beta vulgaris var. cida and Chenopodium album. The growth response of each species [Q temperature, water availability, and soil salinity was investigated in a series of greenhouse experiments in Tucson, Arizona. The nutritional qualities of both seeds and vegetative matter (per cent moisture, fat, protein, fiber, ash, and amino acid composition) were detennined for the experimental species.
MILLER, TE, WING, JS & HUETE, AR 1984, 'THE AGRICULTURAL POTENTIAL OF SELECTED C-4 PLANTS IN ARID ENVIRONMENTS', JOURNAL OF ARID ENVIRONMENTS, vol. 7, no. 3, pp. 275-286.
Broich, M, Huete, A, Tulbure, MG, Ma, X, Xin, Q, Paget, M, Restrepo-Coupe, N, Davies, K, Devadas, R & Held, A, 'Land surface phenological response to decadal climate variability across Australia using satellite remote sensing', Biogeosciences Discussions, vol. 11, no. 5, pp. 7685-7719.View/Download from: Publisher's site
Abstract. Land surface phenological cycles of vegetation greening and browning are influenced by variability in climatic forcing. Quantitative information on phenological cycles and their variability is important for agricultural applications, wildfire fuel accumulation, land management, land surface modeling, and climate change studies. Most phenology studies have focused on temperature-driven Northern Hemisphere systems, where phenology shows annually reoccurring patterns. Yet, precipitation-driven non-annual phenology of arid and semi-arid systems (i.e. drylands) received much less attention, despite the fact that they cover more than 30% of the global land surface. Here we focused on Australia, the driest inhabited continent with one of the most variable rainfall climates in the world and vast areas of dryland systems. Detailed and internally consistent studies investigating phenological cycles and their response to climate variability across the entire continent designed specifically for Australian dryland conditions are missing. To fill this knowledge gap and to advance phenological research, we used existing methods more effectively to study geographic and climate-driven variability in phenology over Australia. We linked derived phenological metrics with rainfall and the Southern Oscillation Index (SOI). We based our analysis on Enhanced Vegetation Index (EVI) data from the MODerate Resolution Imaging Spectroradiometer (MODIS) from 2000 to 2013, which included extreme drought and wet years. We conducted a continent-wide investigation of the link between phenology and climate variability and a more detailed investigation over the Murray–Darling Basin (MDB), the primary agricultural area and largest river catchment of Australia. Results showed high inter- and intra-annual variability in phenological cycles. Phenological cycle peaks occurred not only during the austral summer but at any time of the year, and their timing varied by more than a month i...
González Lanteri, D, Huete, A, Kim, H & Didan, K, 'ESTIMATION OF THE FRACTION OF CANOPY COVER FROM MULTISPECTRAL DATA TO BE USED IN A WATER SOIL EROSION PREDICTION MODEL', Gayana (Concepción), vol. 68, no. 2.View/Download from: Publisher's site
Huete, A, Eamus, D, Ma, X, Restrepo-Coupe, N, Boulain, N & Hutley, L, 'MONITORING PHENOLOGICAL VARIABILITY ACROSS A TROPICAL SAVANNA ARIDITY GRADIENT WITH REMOTE SENSING ACROSS SEASONAL TO ANNUALAND EXTREME EVENTS', ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXVIII-8/W20, pp. 19-19.View/Download from: Publisher's site
Abstract. Evapotranspiration (ET) of Amazon forests is a main driver of regional climate patterns and an important indicator of ecosystem functioning. Despite its importance, the seasonal variability of ET over Amazon forests, and its relationship with environmental drivers, is still poorly understood. In this study, we carry out a water balance approach to analyse seasonal patterns in ET and their relationships with water and energy drivers over five sub-basins across the Amazon basin. We used in-situ measurements of river discharge, and remotely sensed estimates of terrestrial water storage, rainfall, and solar radiation. We show that the characteristics of ET seasonality in all sub-basins differ in timing and magnitude. The highest mean annual ET was found in the northern Rio Negro basin (~ 1497 mm year−1) and the lowest values in the Solimões River basin (~ 986 mm year−1). For the first time in a basin-scale study, using observational data, we show that factors limiting ET vary across climatic gradients in the Amazon, confirming local-scale eddy covariance studies. Both annual mean and seasonality in ET are driven by a combination of energy and water availability, as neither rainfall nor radiation alone could explain patterns in ET. In southern basins, despite seasonal rainfall deficits, deep root water uptake allows increasing rates of ET during the dry season, when radiation is usually higher than in the wet season. We demonstrate contrasting ET seasonality with satellite greenness across Amazon forests, with strong asynchronous relationships in ever-wet watersheds, and positive correlations observed in seasonally dry watersheds. Finally, we compared our results with estimates obtained by two ET models, and we conclude that neither of the two tested models could provide a consistent representation of ET seasonal patterns across the Amazon.
Newlands, NK, Porcelli, TA, Potgieter, AB, Kouadio, L, Huete, A & Guo, W, 'Editorial: Building and Delivering Real-World, Integrated Sustainability Solutions: Insights, Methods and Case-Study Applications', Frontiers in Environmental Science, vol. 7.View/Download from: Publisher's site
Potter, C, Klooster, S, Huete, A, Genovese, V, Bustamante, M, Guimaraes Ferreira, L, Cosme de Oliveira Junior, R & Zepp, R, 'Terrestrial carbon sinks in the Brazilian Amazon and Cerrado region predicted from MODIS satellite data and ecosystem modeling', Biogeosciences Discussions, vol. 6, no. 1, pp. 947-969.View/Download from: Publisher's site
Abstract. A simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000–2004. Net ecosystem production (NEP) flux for atmospheric CO2 in the region for these years was estimated. Consistently high carbon sink fluxes in terrestrial ecosystems on a yearly basis were found in the western portions of the states of Acre and Rondônia and the northern portions of the state of Pará. These areas were not significantly impacted by the 2002–2003 El Niño event in terms of net annual carbon gains. Areas of the region that show periodically high carbon source fluxes from terrestrial ecosystems to the atmosphere on yearly basis were found throughout the state of Maranhão and the southern portions of the state of Amazonas. As demonstrated though tower site comparisons, NEP modeled with monthly MODIS Enhanced Vegetation Index (EVI) inputs closely resembles the measured seasonal carbon fluxes at the LBA Tapajos tower site. Modeling results suggest that the capacity for use of MODIS Enhanced Vegetation Index (EVI) data to predict seasonal uptake rates of CO2 in Amazon forests and Cerrado woodlands is strong.
Songsom, V, Koedsin, W, Ritchie, RJ & Huete, A, 'Mangrove Phenology and Environmental Drivers Derived from Remote Sensing in Southern Thailand', Remote Sensing, vol. 11, no. 8, pp. 955-955.View/Download from: Publisher's site
Vegetation phenology is the annual cycle timing of vegetation growth. Mangrove phenology is a vital component to assess mangrove viability and includes start of season (SOS), end of season (EOS), peak of season (POS), and length of season (LOS). Potential environmental drivers include air temperature (Ta), surface temperature (Ts), sea surface temperature (SST), rainfall, sea surface salinity (SSS), and radiation flux (Ra). The Enhanced vegetation index (EVI) was calculated from Moderate Resolution Imaging Spectroradiometer (MODIS, MOD13Q1) data over five study sites between 2003 and 2012. Four of the mangrove study sites were located on the Malay Peninsula on the Andaman Sea and one site located on the Gulf of Thailand. The goals of this study were to characterize phenology patterns across equatorial Thailand Indo-Malay mangrove forests, identify climatic and aquatic drivers of mangrove seasonality, and compare mangrove phenologies with surrounding upland tropical forests. Our results show the seasonality of mangrove growth was distinctly different from the surrounding land-based tropical forests. The mangrove growth season was approximately 8–9 months duration, starting in April to June, peaking in August to October and ending in January to February of the following year. The 10-year trend analysis revealed significant delaying trends in SOS, POS, and EOS for the Andaman Sea sites but only for EOS at the Gulf of Thailand site. The cumulative rainfall is likely to be the main factor driving later mangrove phenologies.
Tran, NN, Huete, A, Nguyen, H, Grant, I, Miura, T, Ma, X, Lyapustin, A, Wang, Y & Ebert, E, 'Seasonal Comparisons of Himawari-8 AHI and MODIS Vegetation Indices over Latitudinal Australian Grassland Sites', Remote Sensing, vol. 12, no. 15, pp. 2494-2494.View/Download from: Publisher's site
The Advanced Himawari Imager (AHI) on board the Himawari-8 geostationary (GEO) satellite offers comparable spectral and spatial resolutions as low earth orbiting (LEO) sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors, but with hypertemporal image acquisition capability. This raises the possibility of improved monitoring of highly dynamic ecosystems, such as grasslands, including fine-scale phenology retrievals from vegetation index (VI) time series. However, identifying and understanding how GEO VI temporal profiles would be different from traditional LEO VIs need to be evaluated, especially with the new generation of geostationary satellites, with unfamiliar observation geometries not experienced with MODIS, VIIRS, or Advanced Very High Resolution Radiometer (AVHRR) VI time series data. The objectives of this study were to investigate the variations in AHI reflectances and normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and two-band EVI (EVI2) in relation to diurnal phase angle variations, and to compare AHI VI seasonal datasets with MODIS VIs (standard and sun and view angle-adjusted VIs) over a functional range of dry grassland sites in eastern Australia. Strong NDVI diurnal variations and negative NDVI hotspot effects were found due to differential red and NIR band sensitivities to diurnal phase angle changes. In contrast, EVI and EVI2 were nearly insensitive to diurnal phase angle variations and displayed nearly flat diurnal profiles without noticeable hotspot influences. At seasonal time scales, AHI NDVI values were consistently lower than MODIS NDVI values, while AHI EVI and EVI2 values were significantly higher than MODIS EVI and EVI2 values, respectively. We attributed the cross-sensor differences in VI patterns to the year-round smaller phase angles and backscatter observations from AHI, in which the sunlit canopies induced a po...
Aneece, IP, Thenkabail, PS, Lyon, JG, Huete, A & Slonecker, T 2018, 'Spaceborne Hyperspectral EO-1 Hyperion Data Pre-Processing' in Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation, CRC Press, pp. 251-272.View/Download from: Publisher's site
Huete, A, Koedsin, W & Wu, J 2018, 'Hyperspectral Applications to Landscape Phenology' in Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation, CRC Press, pp. 131-144.View/Download from: Publisher's site
Thenkabail, PS, Lyon, JG & Huete, A 2018, 'Advances in Hyperspectral Remote Sensing of Vegetation and Agricultural Crops' in Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation, CRC Press, pp. 3-37.View/Download from: Publisher's site
Thenkabail, PS, Lyon, JG & Huete, A 2018, 'Fifty Years of Advances in Hyperspectral Remote Sensing of Agriculture and Vegetation—Summary, Insights, and Highlights of Volume II' in Hyperspectral Indices and Image Classifications for Agriculture and Vegetation, CRC Press, pp. 251-286.View/Download from: Publisher's site
Thenkabail, PS, Lyon, JG & Huete, A 2018, 'Fifty Years of Advances in Hyperspectral Remote Sensing of Agriculture and Vegetation—Summary, Insights, and Highlights of Volume III' in Biophysical and Biochemical Characterization and Plant Species Studies, CRC Press, pp. 303-341.View/Download from: Publisher's site
Thenkabail, PS, Lyon, JG & Huete, A 2018, 'Fifty Years of Advances in Hyperspectral Remote Sensing of Agriculture and Vegetation—Summary, Insights, and Highlights of Volume IV' in Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation, CRC Press, pp. 339-378.View/Download from: Publisher's site
Thenkabail, PS, Lyon, JG & Huete, A 2018, 'Fifty-Years of Advances in Hyperspectral Remote Sensing of Agriculture and Vegetation—Summary, Insights, and Highlights of Volume I' in Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation, CRC Press, pp. 395-436.View/Download from: Publisher's site
Huete, A, Ponce-Campos, G, Zhang, Y, Restrepo-Coupe, N, Ma, X & Moran, MS 2016, 'Monitoring Photosynthesis from Space' in Thenkabail, P (ed), Land Resources Monitoring, Modeling, and Mapping with Remote Sensing, CRC Press, Boca Raton, pp. 3-22.
Miura, T, Obata, K, Azuma, JT, Huete, A & Yoshioka, H 2015, 'Inter-and intrasensor spectral compatibility and calibration of the enhanced vegetation indices' in Remotely Sensed Data Characterization, Classification, and Accuracies, pp. 155-174.View/Download from: Publisher's site
© 2016 Taylor and Francis Group, LLC. NIR Near-infrared NOAA National Oceanic and Atmospheric Administration NPP National Polar-orbiting Partnership OLI Operational Land Imager PAC Partial atmosphere correction RMSD Root mean square diference SAVI Soil-Adjusted Vegetation Index SeaWiFS Sea-Viewing Wide Field-of-View Sensor SGLI Second-generation Global Imager SPOT Système Pour l'Observation de la Terre sRMPD Systematic square root of mean product diference TM Yematic Mapper TOA Top of the atmosphere TOC Top of canopy uRMPD Unsystematic square root of mean product diference VGT VEGETATION VIIRS Visible Infrared Imaging Radiometer Suite Ye Enhanced Vegetation Index (EVI), an index developed for the National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) mission (Huete et al., 2002), has been shown useful across a wide range of terrestrial vegetation studies. xese include climate-vegetation interactions (Saleska
Glenn, EP, Nagler, PL & Huete, AR 2014, 'Change Detection Using Vegetation Indices and Multiplatform Satellite Imagery at Multiple Temporal and Spatial Scales' in Weng, Q (ed), Scale Issues in Remote Sensing, John Wiley & Sons, USA, pp. 8-107.View/Download from: Publisher's site
© 2014 by John Wiley & Sons, Inc. All rights reserved. This chapter describes emerging methods for using satellite imagery across temporal and spatial scales using a case study approach to illustrate some of the opportunities now available for combining observations across scales. It explores the use of multiplatform sensor systems to characterize ecological change, as exemplified by efforts to scale the effects of a biocontrol insect (the leaf beetle Diorhabda carinulata) on the phenology and water use of Tamarix shrubs (Tamarix ramosissima and related species and hybrids) targeted for removal on western U.S. rivers, from the level of individual leaves to the regional level of measurement. Finally, the chapter summarizes the lessons learned and emphasize the need for ground data to calibrate and validate remote sensing data and the types of errors inherent in scaling point data over wide areas, illustrated with research on evapotranspiration (ET) of Tamarix using a wide range of ground measurement and remote sensing methods.
Huete, A, Miura, T, Yoshioka, H, Ratana, P & Broich, M 2014, 'Indices of vegetation activity' in Hanes, JM (ed), Biophysical Applications of Satellite Remote Sensing, Springer, New York, pp. 1-41.View/Download from: Publisher's site
Huete, A, Miura, T, Yoshioka, H, Ratana, P & Broich, M 2014, 'Indices of Vegetation Activity' in Springer Remote Sensing/Photogrammetry, Springer Berlin Heidelberg, pp. 1-41.View/Download from: Publisher's site
Wensink, H & Alpers, W 2014, 'SAR-Based Bathymetry' in Encyclopedia of Remote Sensing, Springer New York, pp. 719-722.View/Download from: Publisher's site
Huete, A 2012, 'Soil Properties' in Njoku Eni, G (ed), Encyclopedia of Remote Sensing, Springer, Germany, pp. 1-6.
Soils. Soils are three-dimensional living bodies, with spatially variable biologic, physical, and chemical properties, that form the outer skin of the Earths terrestrial surface. Soil formation. Soils form slowly over time and develop distinguishing properties as a function of climate, geologic and organic parent materials, topography, time, vegetation type, and land use history. Soil profile. The vertical depth of a soil body varies from a few centimeters up to several meters and contain a series of soil horizons. The surface layers are termed the O (organic) or A (mineral) horizons, while a lower zone of clay accumulation is the B horizon, and the lowest zone that interfaces with the parent material is the C horizon.
Huete, A & Glenn, EP 2011, 'Recent advances in remote sensing of ecosystem structure and function' in Weng, Q (ed), Advances in Environmental Remote Sensing: Sensors, Algorithms, and Applications, CRC Press, Taylor and Francis Group, Boca Raton, Florida USA, pp. 291-319.
Earth-observing remote sensing technologies are becoming widely adopted within the resource management, ecosystem sciences, and sustainable development communities. Satellite data offer unprecedented capabilities to capture the spatial and temporal detail of ecosystem properties at regional to global scales, and remote sensing tools are now employed in characterising ecosystem structure and biologic properties and in monitoring ecosystem health, seasonal dynamics and functional processes.
Huete, A, Didan, K, Leeuwen, W, Miura, T & Glenn, E 2011, 'MODIS Vegetation Indices' in Ramachandran, B, Justice, CO & Abrams, M (eds), Land Remote Sensing and Global Environmental Change: NASA's Earth Observing System and the Science of ASTER and MODIS, Springer, New York, pp. 579-602.View/Download from: Publisher's site
Assessments of vegetation condition, cover, change, and processes are major components of global change research prograrns, and are topics of considerable societal relevance. Spectral vegetation indices are among the most widely used satellite data products, which provide key measurements for climate, hydrologic, and biogeochemical studies; phenology, land cover, and land cover change detection; natural resource management and sustainable development.
Huete, A, Solano-Barajas, R, Glenn, EP & Restrepo Coupe, N 2011, 'Monitoreo de propiedades y procesos ecosistamicos con indices de vegetacion MODIS' in Jean-Francois Mas (ed), Aplicaciones del sensorMODIS para el monitoreo del territorio, Secretaria de Medio Ambiente, Mexico, pp. 195-230.
En este capÃtulo revisamos los importantes avances y las aplicaciones en el uso de Ãndices de vegetaciÃ³n (IV) de MODIS como herramientas para el anÃ¡lisis y monitoreo de propiedades y procesos ecosistÃ©micos, incluyendo aquellos relacionados con la fotosÃntesis y la transpiraciÃ³n del dosel. Presentamos las caracterÃsticas bÃ¡sicas de los productos IV-MODIS estÃ¡ndar, incluidas las series de tiempo, las medidas cualitativas, el mÃ©todo de composiciÃ³n y las incertidumbres presentes en las series de datos. Discutimos construcciones alternativas de las series de datos temporales de IV, incluyendo aquellos de la recepciÃ³n directa de datos. Los perfiles de los IV interanuales y estacionales son presentados y analizados en varios sitios de cobertura terrestre en MÃ©xico y los IV MODIS son comparados con mediciones temporales de productividad bruta y evapotranspiraciÃ³n de ecosistemas realizadas con torres de mediciÃ³n de flujo en La Paz, Baja California Sur. Se muestra que los IV-MODIS son herramientas de inestimable valor en el estudio temporal de las dinÃ¡micas de los ecosistemas.
Huete, AR & Glenn, EP 2011, 'Remote sensing of ecosystem structure and function' in Advances in Environmental Remote Sensing: Sensors, Algorithms, and Applications, pp. 291-320.
Thenkabail, P, Lyon, J & Huete, A 2011, 'Hyperspectral Remote Sensing of Vegetation and Agricultural Crops' in Hyperspectral Remote Sensing of Vegetation, CRC Press, pp. 663-688.View/Download from: Publisher's site
Thenkabail, P, Lyon, JG & Huete, A 2011, 'Advances in hyperspectral remote sensing of vegetation and agricultural croplands' in Thenkabail, PS, Lyon, JG & Huete, A (eds), Hyperspectral Remote Sensing of Vegetation, Taylor & Francis, USA, pp. 3-35.
Thenkabail, P, Lyon, JG & Huete, A 2011, 'Hyperspectral remote sensing of vegetation and agricultural crops: Knowledge gain and knowledge gap after 40 years of research' in Thenkabail, PS, Lyon, JG & Huete, A (eds), Hyperspectral Remote Sensing of Vegetation, Taylor & Francis, USA, pp. 663-688.
Erasmi, S, Ardiansyah, M, Propastin, P & Huete, A 2010, 'Spatiotemporal trends of forest cover change in Southeast Asia' in Teja Tscharntke (ed), Tropical Rainforests and Agroforests under Global Change, Ecological and Socio-economic Valuations, Springer, Gottingen, Germany, pp. 269-291.View/Download from: Publisher's site
The current state of tropical forest cover and its change have been identified as key variables in modelling and measuring the consequences of human action on ecosystems. The conversion of tropical forest cover to any other land cover (deforestation) directly contributes to the two main environmental threats of the recent past: 1) the alteration of the global climate by the emission of carbon to the atmosphere and 2) the decline in tropical biodiversity by land use intensification and habitat conversion. The sub-continent of Southeast Asia exhibits one of the highest rates of forest loss and comprises one of the regions with the highest amount and diversity of flora and fauna species, worldwide.
Huete, A, Didan, K, van Leeuwen, W, Miura, T & Glenn, E 2010, 'MODIS Vegetation Indices' in Land Remote Sensing and Global Environmental Change, Springer New York, pp. 579-602.View/Download from: Publisher's site
Huete, A, Kim, Y, Ratana, P, Didan, K, Shimabukuro, YE & Miura, T 2008, 'Assessment of phenologic variability in Amazon tropical rainforests using hyperspectral and MODIS satellite data' in Kalacska, M & Sanchez-Azofeifa, A (eds), Hyperspectral Remote Sensing of Tropical and Sub-Tropical Forests, CRC Press, Boca Raton, Florida, USA, pp. 233-259.
Miura, T, Huete, A, Ferreira, LG, Sano, EE & Yoshioka, H 2008, 'A technique for reflectance calibration of airborne hyperspectral spectrometer data using a broad, multi-band radiometer' in Kalacska, M & Sanchez-Azofeifa, A (eds), Hyperspectral Remote Sensing of Tropical and Sub-Tropical Forests, CRC Press, Boca Raton, Florida, USA, pp. 213-231.
Anyamba, A, Tucker, CJ, Huete, A & Boken, VJ 2005, 'Monitoring Drought Using Coarse-Resolution Polar-Orbiting Satellite Data' in Boken, V, Cracknell, AP & Heathcote, RL (eds), Monitoring and Predicting Agricultural Drought: A Global Study, Oxford University Press, Oxford, UK, pp. 57-78.
Huete, A 2005, 'Estimation of Soil Properties Using Hyperspectral VIS/IR Sensors' in Anderson, MG (ed), Encyclopedia of Hydrological Sciences, John Wiley & Sons, Ltd, New York, pp. 887-902.
Knowledge of soil properties and processes are crucial to the understanding of the terrestrial hydrologic cycle and the functioning of terrestrial ecosystems. In this paper, we present the current state and potential of hyperspectral remote sensing techniques for quantitative retrieval of soil properties. Remote sensing is used to detect chemical and physical soil properties either (i) directly from the bare soil pixels, (ii) through advanced spectroscopy methods in mixed soil-vegetation-litter pixels, and (iii) by measurements of the overlying vegetated canopy to infer soil properties and moisture status. Optical-geometric properties of soil surfaces reveal information on soil physical features, such as soil structure, crusting, and erosion. We also investigate the use of vegetation water indices to infer soil drying and wetting in the soil root zone. We conclude with a discussion on future needs and directions for remote sensing of soil properties.
Xie, Q, Liu, Y, Huete, A & Nguyen, H 2020, 'Multi-scale phenology from digital time-lapse camera to Sentinel-2 and MODIS over Australian pastures', Vienna, Austria.View/Download from: Publisher's site
Huete, A, Tran, NN, Nguyen, H, Xie, Q & Katelaris, C 2019, 'Forecasting Pollen Aerobiology with Modis EVI, Land Cover, and Phenology Using Machine Learning Tools', IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, IEEE International Geoscience and Remote Sensing Symposium, IEEE, Yokohama, Japan, pp. 5429-5432.View/Download from: Publisher's site
Grass pollens are a major source of aeroallergens globally, inducing allergic asthma and hay fever in up to 500 million people worldwide. Pollen forecasting research and methods are site-dependent and tend to be empirically derived composites of expert knowledge and weather data. In this study we utilize satellite-based information of landscape conditions and phenology to better discern and predict grass pollen evolution. We employed machine learning approaches to formulate and better understand relationships between landscape phenology and seasonal flowering-induced pollen concentrations. We show that machine learning approaches significantly improved pollen prediction capabilities and provided key information to better attribute changes in pollen counts driven by shifting ecological landscapes from climate change drivers.
Davies, JM, Ebert, E, Huete, A, Newbigin, E, Silver, J & Beggs, P 2017, 'Aerobiological, biogeographical, and meteorological features of the November 2016 fatal thunderstorm asthma event in Melbourne, Australia', ALLERGY, Congress of the European-Academy-of-Allergy-and-Clinical-Immunology, WILEY, Helsinki, FINLAND, pp. 803-804.
Medek, D, Katelaris, C, Erbas, B, Lampugnani, ER, Newbiggin, E, Haberle, S, Huete, A, Beggs, PJ, Ebert, B, van Klinken, R & Davies, JM 2017, 'IMPLEMENTATION OF THE AUSPOLLEN PARTNERSHIP PROJECT AND PRE-EVALUATION SURVEY OF USER PERCEPTION OF THE VALUE OF LOCAL POLLEN INFORMATION', INTERNAL MEDICINE JOURNAL, WILEY, pp. 21-21.View/Download from: Publisher's site
Tran, NN, Huete, A & Hardtke, L 2017, 'Impact of bidirectional reflectance distribution function on modis vegetation indices in southeast Asia tropical forests', 38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017, Asian Conference on Remote Sensing, AARS, Delhi, India, pp. 1-6.
Copyright © 2017 ISRS, All Rights Reserved. Tropical forests play important roles on global climate and biodiversity. The Moderate Resolution Imaging Spectroradiometer (MODIS), with high temporal resolution, provide a useful tool to study tropical forest dynamics, including seasonality and inter-annual variation. However, optical satellite data have cloud, aerosol and bidirectional reflectance distribution function (BRDF) effects, that create uncertainty in tropical forest studies. In the Amazon, some researchers demonstrated the difficulties in separating true forest dynamics from BRDF artefacts and seasonal cloud and aerosol influences. Lastly, optical reflectance saturation in dense tropical forests may restrict the retrieval of phenology information. In this study, we investigated the impact of BRDF effects on MODIS vegetation indices (VI) in Southeast Asia (SEA) tropical forests, the least studied area compared to other major tropical forests (South America and Central Africa). Moreover, unlike Amazon tropical forests, VI seasonality in SEA forests is not synchronous with sun-sensor geometries. We used 10-year data of daily MODIS BRDF (MCD43A1) collection 6 product, a kernel-driven model product that allows us to retrieve VI values for a range of fixed solar zenith angles (SZA). We compared these with the standard VI products (MOD13A1, MYD13A1) to analyse BRDF influences. The results show significant BRDF effects in all forest sites. Generally, smaller SZA yielded higher VI signals in forests. We found tradeoff's between VI robustness to BRDF effects and saturation that impacted upon the retrievals of phenology parameters.
Devadas, R, Vicendese, D, Erbas, B, Medek, D, Haberle, SG, Newnham, RM, Johnston, FH, Beggs, PJ, Jaggard, AK, Campbell, B, Burton, PK, Katelaris, CH, Newbigin, E, Thibaudon, M, Huete, AR & Davies, JM 2016, 'Remote sensing of phenology: a dynamic tool to inform allergenic grass pollen aerobiology', ALLERGY, Meeting of the European-Academy-of-Allergy-and-Clinical-Immunology, WILEY-BLACKWELL, Vienna, AUSTRIA, pp. 196-196.
Giovannini, L, Ma, X & Huete, A 2016, 'Drought resilience of Australian rangelands under intense hydroclimatic variability', International Geoscience and Remote Sensing Symposium (IGARSS), IEEE International Geoscience and Remote Sensing Symposium, IEEE, Beijing, China, pp. 5467-5469.View/Download from: Publisher's site
© 2016 IEEE.Rangelands comprise ∼81% of Australia's landmass, extend over a broad range of climates and vegetation types, and provide important social-economical functions (Fig. 1). The climate of Australia's rangelands is extremely variable. This variability was reflected in recent events of extreme flooding immediately following one of the most intense droughts in history over the early 21st century [1,2]. These extreme climatic events provide an opportunity to assess how Australian rangelands respond to hydroclimatic variations, and further generalise knowledge regarding resilience of these ecosystems to contrasting drought and wet extremes.
Huete, A, Restrepo-Coupe, N, Wu, J & Saleska, S 2016, 'Climate and leaf phenology controls on tropical forest photosynthesis', Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International, IEEE International Geoscience and Remote Sensing Symposium, IEEE, Beijing, China, pp. 1731-1733.View/Download from: Publisher's site
© 2016 IEEE.Discerning photosynthetic seasonality in tropical forests is fundamental to both basic ecology (plant strategies for resource acquisition when resources are limiting) and the need to understand vegetation responses and feedbacks to a changing climate. The seasonality question provides an important threshold test to advance predictions of tropical forest response to future climate changes. Despite its importance, spatial and temporal photosynthesis patterns in tropical forests are highly uncertain and remain controversial as ecosystem models yield divergent results while satellite-based observations are subject to various artifacts associated with cloud leakage, aerosols, and sensor-sun observation geometries. In this research, in situ seasonal tower carbon flux and leaf-scale phenology measures from cameras were combined with satellite data to investigate the roles of climate drivers and biologic processes (leaf phenology and demography traits) on vegetation canopy photosynthesis. Our results show the importance of phenology traits on controls on seasonal photosynthesis.
Shen, J, Tran, NN, Devadas, R, Huete, A, Zhang, H & Yu, Q 2016, 'Climate impacts on wheat phenology and production using mutisource data in NSW, Australia', International Geoscience and Remote Sensing Symposium (IGARSS), IEEE International Geoscience and Remote Sensing Symposium, IEEE, Beijing, China, pp. 6296-6299.View/Download from: Publisher's site
© 2016 IEEE.Wheat is the most important grain crop in Australia, which plays a significant role in world grain-trading market. However, climate warming, water shortage, as well as more frequent extreme weather events (e.g., heatwaves, droughts and floods), under pressure of food demand, would pose great risks to all aspects of wheat production worldwide, especially in Australia with high climate variability. This study aggregated multi-source observational data by using meteorological statistics, in-situ investigation data and the MODIS Enhanced Vegetation Index (EVI) product to explore and examine the correlation between climate variability and spatial-temporal patterns of wheat phenology metrics and productivity. The results from tests over 370 wheat trial sites showed: 1) narrower and earlier sowing and harvesting windows occurred in a drought year (2006) compared with a normal year (2005). Differences in sowing and harvesting window lengths were 9 and 5 days, respectively; 2) different weather patterns in each agro-climatic zone were followed by different remotely sensed crop EVI seasonality profiles. Crop growth was least affected by climate variability in agro-climate region E2, which is located in the south part of study area. This study reveals new information on cropland-climate relationships across the wheat belt in NSW in a changing climate.
Sidiqui, P, Huete, A & Devadas, R 2016, 'Spatio-temporal mapping and monitoring of Urban Heat Island patterns over Sydney, Australia using MODIS and Landsat-8', 4th International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2016 - Proceedings, International Workshop on Earth Observation and Remote Sensing Applications, IEEE, Guangzhou, China, pp. 217-221.View/Download from: Publisher's site
© 2016 IEEE.Most cities have become net sources of heat with well-documented examples of anthropogenic climate modification in urban areas driving the Urban Heat Island (UHI) effect. This is defined as having higher temperatures (air /surface) in the built environment of cities compared with the surrounding and in rural areas. In this study we integrated remotely sensed satellite data to map and monitor the UHI effect over the Sydney region in Australia. Terra/Aqua MODIS Land Surface Temperature (LST) time series data for 2003 to 2015 were analysed to determine the spatio-temporal dynamics of UHI intensity. Land cover data from the MODIS were used to delineate the urban, rural and water class for the Sydney region. The UHI intensities were extracted from LST images by normalising rural LST patterns for each date. A Gaussian approximation was then applied in order to quantify spatial extent, centre and magnitude of UHI intensities. The temporal analysis on seasonal and interannual variations of UHI, revealed maximum intensities in daytime periods, particularly during the summer season. The daytime UHI intensity in Sydney could be as large as 7 - 8 °C in summer days. However, relatively weak UHI intensities were observed in night-time periods during all seasons. It was observed from the time series data that there were slight non-significant increasing trend in daytime UHI magnitudes for Sydney. However, pixel based UHI intensities at dense urban suburbs showed significant increasing trends for daytime and no defined trend for night time observations. To better characterise the locational nature of UHI, Landsat-8 land surface temperature data were analysed for summer period. Landsat data were helpful in extracting the information on hot spots in urban area more precisely. Satellite data of MODIS and Landsat provided efficient results for monitoring, mapping and characterizing UHI patterns over time and space. Future work involves classification of urban areas using...
Huete, A, Xie, Z, Restrepo-Coupe, N, Devadas, R, Davies, K & Waston, C 2015, 'Terrestrial Total Water Storage Dynamics Of Australia's Recent Dry And Wet Events', Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), IEEE, Milan, pp. 992-995.View/Download from: Publisher's site
Australia recently experienced a long-term continental drought ("big dry", 2001-2009) followed by an anomalous wet two-year period ("big wet", 2010-2011). Despite the significance of the two extreme events, continental-wide information regarding the effects of the high and low precipitation conditions on the hydrological components, stress and recovery is not available. In this paper, we use terrestrial total water storage changes (ATWS) from the Gravity Recovery and Climate Experiment (GRACE) and precipitation data from the Tropical Rainfall Measuring Mission (TRMM) spanning from 2002 to 2013, where ATWS represents the main source of water available for human consumption, agriculture and natural ecosystems. We rely on a combination of temporal trend analysis and spatial statistics methods in order to evaluate the terrestrial total water storage (TWS) dynamics and the relationship between TWS and rainfall during the "big dry" and "big wet" events. Here we report the occurrence of hydrological cycle intensification during the study period in Australia which exhibited strong spatial variations: the wet areas (the northern and northeast regions) got wetter while the dry areas (the west and interior of the continent) became drier. By contrast, in southeastern Australia TWS changes over time showed sudden extreme responses to both events. Our results constitute a step beyond quantifying droughts/anomalous wet years that rely solely on precipitation data. This work demonstrates the ability of TWS observations as a significant indicator of hydrological system performance during hydroclimatic events and also an important tool for understanding continental-wide and regional spatial and temporal patterns of water availability.
Watson, CJ, Coupe, NR & Huete, AR 2013, 'Hyperspectral assessments of condition and species composition of Australian grasslands', Proceedings of the 2013 IEEE International Geoscience & Remote Sensing Symposium, IEEE International Geoscience and Remote Sensing Symposium, IEEE, Melbourne, VIC, Australia, pp. 2770-2773.View/Download from: Publisher's site
Temperate grasslands in Australia show dynamic responses to climate, which renders them difficult to study using conventional remote sensing tools. However, the need to adequately describe native grassland variables is critical in maintaining ecological and agricultural values. We used a spectroradiometer to measure leaf-and canopy-level spectra from grassland plots in a controlled environment and compared results to fractional cover and species type. We found that the target species, Themeda australis and Poa labillardierei were separable at canopy and leaf level for both healthy and senescent foliage. In particular, we found differences in the 470-510 nm and 660-700 nm spectral regions. Comparison of narrow band vegetation indices for different combinations of photosynthetic and non-photosynthetic material showed strong relationships across a range of fractional cover values which was co-linear for both species. This method demonstrates the potential for remote sensing to identify Australian grasslands of different quality and composition.
Rasaiah, BA, Malthus, TJ, Bellman, C, Chisholm, L, Gamon, J, Hueni, A, Huete, A, Jones, SD, Ong, C, Phinn, S, Roelfsema, C, Suarez, L, Townsend, P, Trevithick, R & Wyatt, M 2013, 'Approaches to establishing a metadata standard for field spectroscopy datasets', International Geoscience and Remote Sensing Symposium (IGARSS), IEEE International Geoscience and Remote Sensing Symposium, IEEE, VIC, Australia, pp. 4523-4526.View/Download from: Publisher's site
There is an urgent need within the international remote sensing community to establish a metadata standard for field spectroscopy that ensures high quality, interoperable metadata sets that can be archived and shared efficiently within Earth observation data sharing systems. Careful examination of all stages of metadata collection and analysis can inform a robust standard that is applicable to a range of field campaigns. This paper presents approaches towards a standard that encompasses in situ metadata collection and initiatives towards sharing metadata within intelligent archiving systems. © 2013 IEEE.
Ma, X, Huete, A, Yu, Q, Davies, KP & Restrepo Coupe, N 2012, 'Monitoring spatial patterns of vegetation phenology in an Australian tropical transect using MODIS EVI', International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXII International Society for Photogrammetry & Remote Sensing Congress., ISPRS Society, Melbourne, Australia, pp. 271-276.View/Download from: Publisher's site
Phenology is receiving increasing interest in the area of climate change and vegetation adaptation to climate. The phenology of a landscape can be used as a key parameter in land surface models and dynamic global vegetation models to more accurately simulate carbon, water and energy exchanges between land cover and atmosphere. However, the characterisation of phenology is lacking in tropical savannas which cover more than 30% of global land area, and are highly vulnerable to climate change. The objective of this study is to investigate the spatial pattern of vegetation phenology along the Northern Australia Tropical Transect (NATT) where the major biomes are wet and dry tropical savannas. For this analysis we used more than 11 years Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) product from 2000 to 2011. Eight phenological metrics were derived: Start of Season (SOS), End of Season (EOS), Length of Season (LOS), Maximum EVI (MaxG), Minimum EVI (MinG), annual amplitude (AMP), large integral (LIG), and small integral (SIG) were generated for each year and each pixel. Our results showed there are significant spatial patterns and considerable interannual variations of vegetation phenology along the NATT study area. Generally speaking, vegetation growing season started and ended earlier in the north, and started and ended later in the south, resulting in a southward decrease of growing season length (LOS). Vegetation productivity, which was represented by annual integral EVI (LIG), showed a significant descending trend from the northern part of NATT to the southern part. Segmented regression analysis showed that there exists a distinguishable breakpoint along the latitudinal gradient, at least in terms of annual minimum EVI (EVI), which is located between 18.84"S to 20.04"S.
Huete, A, Eamus, D, Ma, X, Restrepo-Coupe, N, Boulain, N & Hutley, L 2011, 'MONITORING PHENOLOGICAL VARIABILITY ACROSS A TROPICAL SAVANNA ARIDITY GRADIENT WITH REMOTE SENSING ACROSS SEASONAL TO ANNUALAND EXTREME EVENTS', ISPRS BHOPAL 2011 WORKSHOP EARTH OBSERVATION FOR TERRESTRIAL ECOSYSTEM, ISPRS Bhopal Workshop on Earth Observation for Terrestrial Ecosystem, COPERNICUS GESELLSCHAFT MBH, Bhopal, INDIA, pp. 19-19.
Jiang, Z, Huete, A, Wang, Y & Lyapustin, A 2011, 'Evaluation of MODIS VI products using the AERONET-based surface reflectance validation network dataset', 34th International Symposium on Remote Sensing of Environment - The GEOSS Era: Towards Operational Environmental Monitoring.
MODIS vegetation index (VI) products (MOD13) are widely used in many science applications that aim to monitor and characterize spatial and temporal vegetation dynamics from space. The quality and reliability of the MODIS VI products are vital to these studies, and thus there is a need to assess their quality. In this study, the AERONET-based Surface Reflectance Validation Network (ASRVN) dataset is used to evaluate the quality of the MODIS 1 km, 16-day composite NDVI and EVI products. Our results show a positive bias of red reflectances, which is responsible for bias in the MODIS NDVI and two-band EVI (EVI2). The negative bias of the MODIS blue reflectance nullifies this effect on the standard EVI, resulting in insignificant bias in EVI. EVI and NDVI temporal profiles match ASRVN VI profiles even during higher aerosol optical thickness (AOT) periods, indicating that the VI products are not significantly affected by aerosols.
Luvall, JC, Sprigg, W, Levetin, E, Huete, A, Nickovic, S, Pejanovic, G, Van de Water, P, Myers, O, Budge, A, Crimmins, T, Krapfl, H & Zelicoff, A 2011, 'Use of MODIS Satellite Images and an Atmospheric Dust Transport Model To Evaluate Juniperus Spp. Pollen Phenology and Dispersal to Support Public Health Alerts', JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY, American-Academy-of-Allergy-Asthma-and-Immunology Annual Meeting, MOSBY-ELSEVIER, San Francisco, CA, pp. AB19-AB19.View/Download from: Publisher's site
Ponce, G, Moran, S, Huete, A, Bresloff, C, Huxman, T, Bosch, D, Bradford, J, Buda, A, Gunter, S, McNab, H, McClaran, M, Peters, D, Sadler, J, Seyfried, M, Starks, P, Sutherland Montoya, D & Heartsill, T 2011, 'Convergence of dynamic vegetation net productivity responses to precipitation variability from 10 years of MODIS EVI', 34th International Symposium on Remote Sensing of Environment - The GEOSS Era: Towards Operational Environmental Monitoring, International Symposium on Remote Sensing of Environment (ISRSE), Sydney Convention and Exhibition Centre, Australia.
According to Global Climate Models (GCMs) the occurrence of extreme events of precipitation will be more frequent in the future. Therefore, important challenges arise regarding climate variability, which are mainly related to the understanding of ecosystem responses to changes in precipitation patterns. Previous studies have found that Above-ground Net Primary Productivity (ANPP) was positively related to increases in annual precipitation and this relation may converge across biomes during dry years. One challenge in studying this ecosystem response at the continental scale is the lack of ANPP field measurements over extended areas. In this study, the MODIS EVI was utilized as a surrogate for ANPP and combined with precipitation datasets from twelve different experimental sites across the United States over a 10-year period. Results from this analysis confirmed that integrated-EVI for different biomes converged toward common precipitation use efficiency during water-limited periods and may be a viable surrogate for ANPP measurements for further ecological research.
Huete, AR & Ponce, G 2010, 'SATELLITE OBSERVED SHIFTS IN SEASONALITY AND VEGETATION -RAINFALL RELATIONSHIPS IN THE SOUTHWEST USA', NETWORKING THE WORLD WITH REMOTE SENSING, 8th Symposium on Networking the World with Remote Sensing of ISPRS-Technical-Commission, COPERNICUS GESELLSCHAFT MBH, Kyoto, JAPAN, pp. 775-777.
Huete, AR & Saleska, SR 2010, 'Remote Sensing of Tropical Forest Phenology: Issues and Controversies', NETWORKING THE WORLD WITH REMOTE SENSING, 8th Symposium on Networking the World with Remote Sensing of ISPRS-Technical-Commission, COPERNICUS GESELLSCHAFT MBH, Kyoto, JAPAN, pp. 539-541.
Freitas, RM, Shimabukuro, YE, Rosa, RR & Huete, A 2009, 'FRACTION IMAGES DERIVED FROM EO-1 HYPERION MULTITEMPORAL DATA FOR DRY SEASON GREEN UP ANALYSIS IN TAPAJOS NATIONAL FOREST, BRAZILIAN AMAZONIA', 2009 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-5, IEEE International Geoscience and Remote Sensing Symposium, IEEE, Cape Town, SOUTH AFRICA, pp. 3395-+.View/Download from: Publisher's site
Hess, L, Ratana, P, Huete, A, Potter, C & Melack, J 2009, 'USE OF MODIS ENHANCED VEGETATION INDEX TO DETECT SEASONAL PATTERNS OF LEAF PHENOLOGY IN CENTRAL AMAZON VARZEA FOREST', 2009 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-5, IEEE International Geoscience and Remote Sensing Symposium, IEEE, Cape Town, SOUTH AFRICA, pp. 3387-+.View/Download from: Publisher's site
Huete, AR 2007, 'Satellite and tower flux comparisons of tropical forest functioning in the Mekong Region', 28th Asian Conference on Remote Sensing 2007, ACRS 2007, pp. 316-321.
Recent neotropical rainforest studies with local tower flux measurements and satellite observations have shown a strong correspondence of seasonal ecosystem carbon fluxes with satellite measures of greenness that follow the availability of sunlight. However, in drier tropical forests and in areas of forest disturbance, fluxes were more likely to track seasonal water availability. The tropical forests of the Mekong Region in Southeast Asia are more extensively degraded due to intense land use pressures and thus may be more drought susceptible. In this study, we investigated the seasonal patterns of Terra-MODIS satellite measures of enhanced vegetation index (EVI) greenness across a series of tropical forest types, encompassing intact drought-deciduous and dry evergreen tropical forests. Climate and environmental controls on the resulting phenologic profiles were then evaluated. The satellite time series data were compared with local site tower flux measures of gross primary productivity (GPP) for calibration and possible extension of tower flux measures to regional scales. Our results show large phenologic variability and differences in moisture and light controls on productivity across the different tropical forests with the drier forest sites primarily water-limited, and the more humid evergreen forests showing a positive trend with light availability. Disturbed forest areas were increasingly drought-susceptible. Satellite greenness observations were generally consistent and linearly related with tower flux GPP measurements at the tower sites, providing opportunities for regional scaling of carbon fluxes across the heterogeneous surface states of the Mekong Region.
Jiang, Z, Huete, AR, Kim, Y & Didan, K 2007, '2-band enhanced vegetation index without a blue band and its application to AVHRR data', REMOTE SENSING AND MODELING OF ECOSYSTEMS FOR SUSTAINABILITY IV, Conference on Remote Sensing and Modelling of Ecosystems for Sustainability IV, SPIE-INT SOC OPTICAL ENGINEERING, San Antonio, CA.View/Download from: Publisher's site
Kim, Y, Huete, AR, Jiang, Z & Miura, T 2007, 'Multisensor reflectance and vegetation index comparisons of amazon tropical forest phenology with hyperspectral hyperion data', REMOTE SENSING AND MODELING OF ECOSYSTEMS FOR SUSTAINABILITY IV, Conference on Remote Sensing and Modelling of Ecosystems for Sustainability IV, SPIE-INT SOC OPTICAL ENGINEERING, San Antonio, CA.View/Download from: Publisher's site
Huete, AR, Miura, T, Kim, Y, Didan, K & Privette, J 2006, 'Assessments of multisensor vegetation index dependencies with hyperspectral and tower flux data', REMOTE SENSING AND MODELING OF ECOSYSTEMS FOR SUSTAINABILITY III, Conference on Remote Sensing and Modeling of Ecosystems for Sustainability III, SPIE-INT SOC OPTICAL ENGINEERING, San Diego, CA.View/Download from: Publisher's site
Huete, AR, Running, S & Myneni, R 2006, 'Monitoring Rainforest Dynamics in the Amazon with MODIS Land Products', 2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8, IEEE International Geoscience and Remote Sensing Symposium (IGARSS), IEEE, Denver, CO, pp. 263-+.View/Download from: Publisher's site
Ratana, P, Huete, AR & Didan, K 2006, 'MODIS EVI-based Variability in Amazon Phenology across the Rainforest-Cerrado Ecotone', 2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8, IEEE International Geoscience and Remote Sensing Symposium (IGARSS), IEEE, Denver, CO, pp. 1942-1944.View/Download from: Publisher's site
Shimabukuro, YE, Anderson, LO, Aragao, LEOC & Huete, A 2006, 'USING FRACTION IMAGES TO STUDY NATURAL LAND COVER CHANGES IN THE AMAZON', 2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8, IEEE International Geoscience and Remote Sensing Symposium (IGARSS), IEEE, Denver, CO, pp. 2103-+.View/Download from: Publisher's site
Ferreira, NC, Ferreira, LG, Huete, A, Didan, K & Miura, T 2005, 'A GIS based change detection system for the Amazon forest: Advantages and implications for the environmental monitoring and regional sustainable development', IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium, Vols 1-8, Proceedings, 25th IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2005), IEEE, Seoul, SOUTH KOREA, pp. 3474-3476.
Huete, A, Kim, HJ & Miura, T 2005, 'Scaling dependencies and uncertainties in vegetation index - Biophysical retrievals in heterogeneous environments', IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium, Vols 1-8, Proceedings, 25th IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2005), IEEE, Seoul, SOUTH KOREA, pp. 5029-5032.
Huete, AR 2005, 'Global variability of terrestrial surface properties derived from MODIS visible to thermal-infrared measurements', IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium, Vols 1-8, Proceedings, 25th IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2005), IEEE, Seoul, SOUTH KOREA, pp. 4938-4941.
Ratana, P, Yin, Y, Huete, AR & Jacobson, A 2005, 'Interrelationship among among MODIS vegetation products across an amazon eco-climatic gradient', IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium, Vols 1-8, Proceedings, 25th IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2005), IEEE, Seoul, SOUTH KOREA, pp. 3009-3012.
Didan, K & Huete, A 2004, 'Analysis of the global vegetation dynamic metrics using MODIS vegetation index and land cover products', IGARSS 2004: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM PROCEEDINGS, VOLS 1-7, IEEE International Geoscience and Remote Sensing Symposium, IEEE, Anchorage, AK, pp. 2058-2061.
Ferreira, LG, Ferreira, ME, Ferreira, NC, Sano, EE, de Jesus, ET & Huete, AR 2004, 'Evaluation of MODIS vegetation indices and change thresholds for the monitoring of the Brazilian Cerrado', IGARSS 2004: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM PROCEEDINGS, VOLS 1-7, IEEE International Geoscience and Remote Sensing Symposium, IEEE, Anchorage, AK, pp. 4340-4343.
Huete, A & Didan, K 2004, 'MODIS seasonal and inter-annual responses of semiarid ecosystems to drought in the southwest USA', IGARSS 2004: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM PROCEEDINGS, VOLS 1-7, IEEE International Geoscience and Remote Sensing Symposium, IEEE, Anchorage, AK, pp. 1538-1541.
Ratana, P & Huete, A 2004, 'Seasonal dynamics of native and converted cerrado physiognomies with MODIS data', IGARSS 2004: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM PROCEEDINGS, VOLS 1-7, IEEE International Geoscience and Remote Sensing Symposium, IEEE, Anchorage, AK, pp. 4336-4339.
Kaurivi, JZU, Huete, AR & Didan, K 2003, 'Multitemporal MODIS-EVI relationships with precipitation and temperature at the Santa Rita experimental range', SANTA RITA EXPERIMENTAL RANGE: 100 YEARS (1903 TO 2003) OF ACCOMPLISHMENTS AND CONTRIBUTIONS, CONFERENCE PROCEEDINGS, Conference on Santa Rita Experimental Range, US DEPT AGR, FOREST SERV ROCKY MT FOREST & RANGE EXPTL STN, Tucson, AZ, pp. 121-124.
Huete, A, Miura, T & Gao, X 2002, 'Land cover conversion and degradation analyses through coupled soil-plant biophysical parameters derived from hyperspecral EO-1 Hyperion', IGARSS 2002: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM AND 24TH CANADIAN SYMPOSIUM ON REMOTE SENSING, VOLS I-VI, PROCEEDINGS, IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2002)/24th Canadian Symposium on Remote Sensing, IEEE, TORONTO, CANADA, pp. 799-801.
Miura, T, Huete, A, Yoshioka, H & Kim, HJ 2002, 'An application of airborne hyperspectral and EO-1 Hyperion data for inter-sensor calibration of vegetation indices for regional-scale monitoring', IGARSS 2002: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM AND 24TH CANADIAN SYMPOSIUM ON REMOTE SENSING, VOLS I-VI, PROCEEDINGS, IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2002)/24th Canadian Symposium on Remote Sensing, IEEE, TORONTO, CANADA, pp. 3118-3120.
Yoshioka, H, Miura, T, Yamamoto, H & Huete, A 2002, 'A technique of inter-sensor VI translations using EO-1 hyperion data to minimize systematic differences in spectral band-pass filters', IGARSS 2002: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM AND 24TH CANADIAN SYMPOSIUM ON REMOTE SENSING, VOLS I-VI, PROCEEDINGS, IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2002)/24th Canadian Symposium on Remote Sensing, IEEE, TORONTO, CANADA, pp. 2211-2213.
Huete, A, Didan, K, Miura, T, Yoshioka, H, Ferreira, L, Gao, X & Batchily, K 2000, 'Validation of the MODIS vegetation indices over a global set of test sites: preliminary results', REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY II, Conference on Remote Sensing for Agriculture, Ecosystems, and Hydrology II, SPIE-INT SOC OPTICAL ENGINEERING, BARCELONA, SPAIN, pp. 194-203.View/Download from: Publisher's site
Huete, A, Gao, X, Asner, G, Kim, HJ & Miura, T 2001, 'Characterization of vegetation conditions at the Nacunan and Chancani Reserves in Argentina with ground- air- and EO-1 hyperion data', IGARSS 2001: SCANNING THE PRESENT AND RESOLVING THE FUTURE, VOLS 1-7, PROCEEDINGS, IEEE International Geoscience and Remote Sensing Symposium, IEEE, UNIV NEW S WALES, SYDNEY, AUSTRALIA, pp. 308-310.
Miura, T, Didan, K, Huete, AR & Rodriguez, EP 2001, 'A performance evaluation of the MODIS vegetation index compositing algorithm', IGARSS 2001: SCANNING THE PRESENT AND RESOLVING THE FUTURE, VOLS 1-7, PROCEEDINGS, IEEE International Geoscience and Remote Sensing Symposium, IEEE, UNIV NEW S WALES, SYDNEY, AUSTRALIA, pp. 1812-1814.
Yoshioka, H, Ferreira, L, Huete, A, Kim, HJ & Miura, T 2001, 'A translation algorithm of NDVI to minimize biases caused by differences in spectral band-pass filters', IGARSS 2001: SCANNING THE PRESENT AND RESOLVING THE FUTURE, VOLS 1-7, PROCEEDINGS, IEEE International Geoscience and Remote Sensing Symposium, IEEE, UNIV NEW S WALES, SYDNEY, AUSTRALIA, pp. 1835-1837.
Ferreira, LG, Huete, A, Yoshioka, H & Sano, E 2000, 'Preliminary analysis of MODIS vegetation indices over the LBA sites in the Cerrado Region, Brazil', IGARSS 2000: IEEE 2000 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOL I - VI, PROCEEDINGS, IEEE International Geoscience and Remote Sensing Symposium, IEEE, HONOLULU, HI, pp. 524-526.
Gao, X & Huete, AR 2000, 'Validation of MODIS land surface reflectance and vegetation indices with multi-scale high spatial resolution data', IGARSS 2000: IEEE 2000 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOL I - VI, PROCEEDINGS, IEEE International Geoscience and Remote Sensing Symposium, IEEE, HONOLULU, HI, pp. 533-535.
Huete, A, Didan, K, Shimabokuro, Y, Ferreira, L & Rodriguez, E 2000, 'Regional Amazon Basin and global analyses of MODIS vegetation indices: Early results and comparisons with AVHRR', IGARSS 2000: IEEE 2000 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOL I - VI, PROCEEDINGS, IEEE International Geoscience and Remote Sensing Symposium, IEEE, HONOLULU, HI, pp. 536-538.
Justice, C, Townshend, J, Vermote, E, Sohlberg, R, Descloitres, J, Roy, D, Hall, D, Salomonson, V, Riggs, G, Huete, A, Didan, K, Miura, T, Wan, ZM, Strahler, A, Schaaf, C, Myneni, R, Running, S, Glassy, J, Nemani, R, El Saleous, N & Wolfe, R 2000, 'Preliminary land surface products from the NASA moderate resolution imaging spectroradiometer (MODIS)', IGARSS 2000: IEEE 2000 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOL I - VI, PROCEEDINGS, IEEE International Geoscience and Remote Sensing Symposium, IEEE, HONOLULU, HI, pp. 1157-1162.
Miura, T, Huete, AR, Didan, K, van Leeuwen, WJD & Yoshioka, H 2000, 'An assessment of the MODIS vegetation index compositing algorithm using quality assurance flags and sun/view angles', IGARSS 2000: IEEE 2000 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOL I - VI, PROCEEDINGS, IEEE International Geoscience and Remote Sensing Symposium, IEEE, HONOLULU, HI, pp. 545-547.
Huete, A, Didan, K, van Leeuwen, W & Vermote, E 1999, 'Global-scale analysis of vegetation indices for moderate resolution monitoring of terrestrial vegetation', REMOTE SENSING FOR EARTH SCIENCE, OCEAN, AND SEA ICE APPLICATIONS, Conference on Remote Sensing for Earth Science, Ocean, and Sea Ice Applications, SPIE-INT SOC OPTICAL ENGINEERING, FLORENCE, ITALY, pp. 141-151.View/Download from: Publisher's site
van Leeuwen, WJD, Huete, AR, Laing, TW & Didan, K 1999, 'Vegetation change monitoring with spectral indices: The importance of view and sun angle standardized data', REMOTE SENSING FOR EARTH SCIENCE, OCEAN, AND SEA ICE APPLICATIONS, Conference on Remote Sensing for Earth Science, Ocean, and Sea Ice Applications, SPIE-INT SOC OPTICAL ENGINEERING, FLORENCE, ITALY, pp. 445-454.View/Download from: Publisher's site
Caetano, MR, Huete, AR, Pereira, JMC & Ni, WG 1998, 'Forest understory characterization at regional levels with satellite data: a conceptual approach', REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY, Conference on Remote Sensing for Agriculture, Ecosystems, and Hydrology, SPIE-INT SOC OPTICAL ENGINEERING, BARCELONA, SPAIN, pp. 245-256.View/Download from: Publisher's site
Caetano, MR, Ni, WG, Pereira, JC & Huete, AR 1998, 'Evaluation of the importance of non-linear spectral mixing in coniferous forests', REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY, Conference on Remote Sensing for Agriculture, Ecosystems, and Hydrology, SPIE-INT SOC OPTICAL ENGINEERING, BARCELONA, SPAIN, pp. 257-269.View/Download from: Publisher's site
Huete, AR, Kerola, D, Didan, K, van Leeuwen, WJD & Ferreira, L 1998, 'Terrestrial biosphere analysis of SeaWiFS data over the Amazon region with MODIS and GLI prototype vegetation indices', IGARSS '98 - 1998 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, PROCEEDINGS VOLS 1-5, 1998 International Geoscience and Remote Sensing Symposium (IGARSS 98) on Sensing and Managing the Environment, IEEE, SEATTLE, WA, pp. 785-787.View/Download from: Publisher's site
van Leeuwen, WJD, Huete, AR & Laing, TW 1998, 'Evaluation of the MODIS vegetation index compositing algorithm using SeaWiFS data', IGARSS '98 - 1998 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, PROCEEDINGS VOLS 1-5, 1998 International Geoscience and Remote Sensing Symposium (IGARSS 98) on Sensing and Managing the Environment, IEEE, SEATTLE, WA, pp. 1445-1447.View/Download from: Publisher's site
Huete, AR, Liu, HQ & vanLeeuwen, WJD 1997, 'The use of vegetation indices in forested regions: Issues of linearity and saturation', IGARSS '97 - 1997 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, PROCEEDINGS VOLS I-IV, 1997 International Geoscience and Remote Sensing Symposium (IGARSS 97) on Remote Sensing - A Scientific Vision for Sustainable Development, I E E E, SINGAPORE, SINGAPORE, pp. 1966-1968.
Sano, EE, Moran, MS, Huete, AR & Miura, T 1997, 'Ku-band SAR data for bare soil moisture retrieval over agricultural fields', IGARSS '97 - 1997 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, PROCEEDINGS VOLS I-IV, 1997 International Geoscience and Remote Sensing Symposium (IGARSS 97) on Remote Sensing - A Scientific Vision for Sustainable Development, I E E E, SINGAPORE, SINGAPORE, pp. 98-100.
van Leeuwen, WJD, Huete, AR, Didan, K & Laing, T 1997, 'Modeling bi-directional reflectance factors for different land cover types and surface components to standardize vegetation indices', PHYSICAL MEASUREMENTS AND SIGNATURES IN REMOTE SENSING, VOLS 1 AND 2, 7th International Symposium on Physical Measurements and Signatures in Remote Sensing, A A BALKEMA PUBLISHERS, COURCHEVEL, FRANCE, pp. 373-380.
vanLeeuwen, WJD, Laing, TW & Huete, AR 1997, 'Quality assurance of global vegetation index compositing algorithms using AVHRR data', IGARSS '97 - 1997 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, PROCEEDINGS VOLS I-IV, 1997 International Geoscience and Remote Sensing Symposium (IGARSS 97) on Remote Sensing - A Scientific Vision for Sustainable Development, I E E E, SINGAPORE, SINGAPORE, pp. 341-343.
Sano, EE, Huete, AR, Troufleau, D, Moran, MS & Vidal, A 1996, 'Analysis of ERS-1 SAR data to study soil moisture content in rocky soils', IGARSS '96 - 1996 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM: REMOTE SENSING FOR A SUSTAINABLE FUTURE, VOLS I - IV, 1996 International Geoscience and Remote Sensing Symposium (IGARSS 96) - Remote Sensing for a Sustainable Future, I E E E, LINCOLN, NE, pp. 157-159.
vanLeeuwen, WJD, Heute, AR, Jia, S & Walthall, CL 1996, 'Comparison of vegetation index compositing scenarios: BRDF versus maximum VI approaches', IGARSS '96 - 1996 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM: REMOTE SENSING FOR A SUSTAINABLE FUTURE, VOLS I - IV, 1996 International Geoscience and Remote Sensing Symposium (IGARSS 96) - Remote Sensing for a Sustainable Future, I E E E, LINCOLN, NE, pp. 1423-1425.
DELIRA, GR, BATCHILY, K, HONGTAO, J & HUETE, AR 1992, 'OPTICAL AND SEASONAL-VARIATIONS ALONG THE UNITED-STATES-MEXICO BORDER - AN ANALYSIS WITH LANDSAT TM IMAGERY', IGARSS '94 - 1994 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM VOLUMES 1-4, International Geoscience and Remote Sensing Symposium on Surface and Atmospheric Remote Sensing - Technologies, Data Analysis and Interpretation (IGARSS 94), IEEE, CALIF INST TECH, PASADENA, CA, pp. 1044-1045.
EPIPHANIO, JCN, HUETE, AR & LIU, HQ 1992, 'INFLUENCE OF SUN-VIEW GEOMETRIES ON THE RELATIONSHIPS AMONG VEGETATION INDEXES, LAI, AND ABSORBED PAR', IGARSS '94 - 1994 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM VOLUMES 1-4, International Geoscience and Remote Sensing Symposium on Surface and Atmospheric Remote Sensing - Technologies, Data Analysis and Interpretation (IGARSS 94), IEEE, CALIF INST TECH, PASADENA, CA, pp. 1455-1457.
HUETE, AR, LIU, H, DELIRA, GR, BATCHILY, K & ESCADAFAL, R 1992, 'A SOIL COLOR INDEX TO ADJUST FOR SOIL AND LITTER NOISE IN VEGETATION INDEX IMAGERY OF ARID REGIONS', IGARSS '94 - 1994 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM VOLUMES 1-4, International Geoscience and Remote Sensing Symposium on Surface and Atmospheric Remote Sensing - Technologies, Data Analysis and Interpretation (IGARSS 94), IEEE, CALIF INST TECH, PASADENA, CA, pp. 1042-1043.
HUETE, AR, LIU, HY & LIU, HQ 1992, 'DIRECTIONAL VEGETATION INDEX INTERACTIONS IN ASAS IMAGERY', IGARSS '94 - 1994 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM VOLUMES 1-4, International Geoscience and Remote Sensing Symposium on Surface and Atmospheric Remote Sensing - Technologies, Data Analysis and Interpretation (IGARSS 94), IEEE, CALIF INST TECH, PASADENA, CA, pp. 1813-1815.
LIU, HQ & HUETE, A 1992, 'A SYSTEMS BASED MODIFICATION OF THE NDVI TO MINIMIZE SOIL AND ATMOSPHERIC NOISE', IGARSS '94 - 1994 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM VOLUMES 1-4, International Geoscience and Remote Sensing Symposium on Surface and Atmospheric Remote Sensing - Technologies, Data Analysis and Interpretation (IGARSS 94), IEEE, CALIF INST TECH, PASADENA, CA, pp. 128-130.
VANLEEUWEN, WJD, HUETE, AR & WALTHALL, CL 1992, 'BIOPHYSICAL INTERPRETATION OF A SPECTRAL MIXTURE MODEL-BASED ON A RADIATIVE-TRANSFER MODEL AND OBSERVATIONAL DATA', IGARSS '94 - 1994 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM VOLUMES 1-4, International Geoscience and Remote Sensing Symposium on Surface and Atmospheric Remote Sensing - Technologies, Data Analysis and Interpretation (IGARSS 94), IEEE, CALIF INST TECH, PASADENA, CA, pp. 1458-1460.
Moran, MS, Weltz, MA, Vidal, A, Goodrich, DC, Amer, SA, Ammon, DS, Batchily, K, Blanford, J, Clarke, TR, Eastman, L, Fox, D, Gellman, D, Hodshon-Yates, M, Hendy, H, Huete, AR, Keefer, T, Kiesel, K, Lane, L, Rahman, AF, Sorooshian, S, Troufleau, D & Washburn, J 1993, 'Evaluating energy balance of semiarid rangeland from combined optical-microwave remote sensing', Conference Proceedings - Topical Symposium on Combined Optical-Microwave Earth and Atmosphere Sensing, COMEAS 1993, pp. 82-85.View/Download from: Publisher's site
POST, DF, BRYANT, RB, BATCHILY, AK, HUETE, AR, LEVINE, SJ, MAYS, MD & ESCADAFAL, R 1990, 'CORRELATIONS BETWEEN FIELD AND LABORATORY MEASUREMENTS OF SOIL COLOR', SOIL COLOR, SYMP ON SOIL COLOR, SOIL SCIENCE SOC AMER, SAN ANTONIO, TX, pp. 35-49.
Qi, J, Kerr, Y, Huete, AR, Sorooshian, S & Dedicu, G 1993, 'Retrieval of surface physical parameters with AVHRR and SMMR over Africa', Conference Proceedings - Topical Symposium on Combined Optical-Microwave Earth and Atmosphere Sensing, COMEAS 1993, pp. 96-99.View/Download from: Publisher's site
© 1993 IEEE. It is well established that optical remote sensing can be used to retrieve surface vegetation information provided that the atmosphere is sufficiently clcar and cloud free. Passive microwave remote sensing has been successfully used for extracting information on surface soil moisture provided that information on vegetation characteristics is known. In this study, we merge the two sources of information to characterize the soil and vegetation surface / atmosphere interface. The technique utilizes the information contained in two microwavc frequencies as well as visible and near-infrared wavebands to cxtract both soil moisture and vegetation characteristics. It relates the microwave polarization ratios to vegetation indices derived from optical remote sensors through a theoretical radiative transfer model. The method was applied in a regional scale context, over a diverse range of biomes along a 60°, African transect for the year 1986. The sensors used included the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and the NOAA Advanced Very High Resolution Radiometer (AVHRR). The synergistic use of the two sensors allowed for the retrieval of soil moisture, vegetation cover. In this paper, we will describe the method and results, together with discussions on the potentials and limitations of this synergistic relationship involving the optical and microwave remote sensing.
HUETE, A, CHEHBOUNI, A & QI, JG 1991, 'MULTITEMPORAL COMPOSITING OF SATELLITE DATA FOR IMPROVED GLOBAL CHANGE DETECTION', PROCEEDINGS OF THE 24TH INTERNATIONAL SYMPOSIUM ON REMOTE SENSING OF ENVIRONMENT, VOLS 1 AND 2, 24TH INTERNATIONAL SYMP ON REMOTE SENSING OF ENVIRONMENT, ENVIRONMENTAL RESEARCH INST MICHIGAN, RIO DE JANEIRO, BRAZIL, pp. 993-1006.
HUETE, AR 1992, 'EXTRACTION OF SOIL AND VEGETATION PARAMETERS FROM HIGH-RESOLUTION BIDIRECTIONAL REFLECTANCE SPECTRA', INTERNATIONAL SPACE YEAR : SPACE REMOTE SENSING, VOLS 1 AND 2, 12TH ANNUAL INTERNATIONAL SYMP ON GEOSCIENCE AND REMOTE SENSING ( IGARSS 92 ), I E E E, HOUSTON, TX, pp. 752-754.
QI, J, CHEHBOUNI, A, HUETE, A, KERR, Y & SOROOSHIAN, S 1991, 'SCALING OF VEGETATION INDEXES FOR ENVIRONMENTAL-CHANGE STUDIES', PROCEEDINGS OF THE 24TH INTERNATIONAL SYMPOSIUM ON REMOTE SENSING OF ENVIRONMENT, VOLS 1 AND 2, 24TH INTERNATIONAL SYMP ON REMOTE SENSING OF ENVIRONMENT, ENVIRONMENTAL RESEARCH INST MICHIGAN, RIO DE JANEIRO, BRAZIL, pp. 579-590.
ESCADAFAL, R, HUETE, A & POST, D 1990, 'ESTIMATING SOIL SPECTRAL PROPERTIES (VISIBLE AND NIR) FROM COLOR AND ROUGHNESS FIELD DATA', PROCEEDINGS OF THE TWENTY-THIRD INTERNATIONAL SYMPOSIUM ON REMOTE SENSING OF ENVIRONMENT, VOLS 1 AND 2, 23RD INTERNATIONAL SYMP ON REMOTE SENSING OF ENVIRONMENT, ENVIRONMENTAL RESEARCH INST MICHIGAN, BANGKOK, THAILAND, pp. 1263-1273.
HUETE, AR & ESCADAFAL, R 1990, 'ASSESSMENT OF SOIL-VEGETATION-SENESCED MATERIALS WITH SPECTRAL MIXTURE MODELING - PRELIMINARY-ANALYSIS', REMOTE SENSING SCIENCE FOR THE NINETIES, VOLS 1-3, 10TH ANNUAL INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM : REMOTE SENSING SCIENCE FOR THE NINETIES, I E E E, UNIV MARYLAND, COLLEGE PARK, MD, pp. 1621-1624.
Huete, AR & Jackson, RD 1985, 'TASSELED CAP: SIZE, SHAPE AND ORIENTATION CHANGES DUE TO SOIL BACKGROUND.', International Symposium - Machine Processing of Remotely Sensed Data, pp. 329-337.
The empirical domain of the Tasseled Cap Graphic Model was examined in the soil brightness-plant greenness plane. Individual, soil-specific tasseled caps were derived for four different soil types with similar plant canopy conditions in order to analyze soil background influences on greenness results. The size, shape and orientation of these tasseled caps were strongly dependent on soil type, and greenness results for identical plant canopy conditions were not reproducible across tasseled caps. Greenness was comparable only when individual tasseled caps were scaled to similar sizes.
Thomas, L, Wyndham, J, Huete, A, Woods, A, Tran, N, Runck, M, Nguyen, H, Wilkinson, S, Biloria, N & Dwyer, S University of Technology Sydney 2020, Fairwater Living Laboratory Milestone 2 Report, pp. 1-89, Sydney Australia.
The overarching aim of the Fairwater Living Laboratory project is to ascertain whether Fairwater, a new housing development by Frasers Property in Blacktown, Sydney NSW delivers predicted sustainability, resilience, wellbeing and commerciality benefits. When completed Fairwater will include up to 850 homes. This report to funding body sets out research outcomes for Year 1 of the three year study for House Performance, Network Demand and Impact Study and Urban Heat Island.
The Hort Innovation Green Cities project "Measuring Australia's Green Space Asset" (MUGS) undertook a global review of urban green space (UGS) measurement research and engaged with Australian stakeholders to gauge current practice. The overall aim of the project was to foster best-practice UGS planning and management by juxtaposing the scientific state of the art with the contextualised needs expressed by potential Australian end users. The synthesis of findings informed a 'blueprint' which sketches the contours of a possible nationally consistent UGS decision-support framework. The framework is illustrated with a worked example from Australia (rapid assessment of urban green space assets using satellite imagery).
Didan, K, Solano, R, Jacobson, A & Huete, A NASA report 2010, MODIS Vegetation Indices (MOD13) C5 User's Guide, pp. 1-42, Arizona, USA.
TOne of the primary interests of the Earth Observing System (EOS) program is to study the role of terrestrial vegetation in large-scale global processes with the goal of understanding how the Earth functions as a system. This requires an understanding of the global distribution of vegetation types as well as their biophysical and structural properties and spatial/temporal variations. Vegetation Indices (VI) are robust, empirical measures of vegetation activity at the land surface. They are designed to enhance the vegetation re?ected signal from measured spectral responses by combining two (or more) wavebands, often in the red (0.6 - 0.7 m) and NIR wavelengths (0.7-1.1 m) region
Huete, A & Ma, X 2016, 'Rising extreme weather warns of ecosystem collapse: study', The Conversation.
The world's climate is already changing. Extreme weather events (floods, droughts, and heatwaves) are increasing as global temperatures rise. While we are starting to learn how these changes will affect people and individual species, we don't yet know how ecosystems are likely to change.
Research published in Nature, using 14 years of NASA satellite data, shows eastern Australia's drylands are among the most sensitive ecosystems to these extreme events, alongside tropical rainforests and mountains. Central Australia's desert ecosystems are also vulnerable, but for different reasons.