Development of an evapotranspiration index from aqua/MODIS for monitoring surface moisture status

Nishida, Kenlo; Nemani, Ramakrishna R.; Glassy, Joseph M.; Running, S. W.

doi:10.1109/tgrs.2003.811744

Cited by 148 publications

(70 citation statements)

References 14 publications

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“…First, the consistency between model-derived and image-based Tends could lead to improving the parameterization of aerodynamic resistance by remote sensing means. Secondly, the minimum and maximum soil temperatures are the boundary conditions for LST-based soil evaporative efficiency (SEE, being defined as the ratio of actual to potential evaporation) models [62,63]. Improving the accuracy in soil Tends opens the path for monitoring SEE from optical/thermal remote sensing.…”

Section: Discussionmentioning

confidence: 99%

Consistency between In Situ, Model-Derived and High-Resolution-Image-Based Soil Temperature Endmembers: Towards a Robust Data-Based Model for Multi-Resolution Monitoring of Crop Evapotranspiration

et al. 2015

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Due to their image-based nature, "contextual" approaches are very attractive to estimate evapotranspiration (ET) from remotely-sensed land surface temperature (LST) data. Their application is however limited to highly heterogeneous areas where the soil and vegetation temperature endmembers (Tends) can be observed at the thermal sensor resolution. This paper aims to develop a simple theoretical approach to estimate Tends independently from LST images. for the image-based and model-derived Tends, respectively. In light of the above results, Tends should be estimated a priori when contextual models are applied to low resolution images. Moreover, the consistency over highly heterogeneous areas between model-derived and high-resolution image-based Tends provides a meaningful basis for developing mixed modeling observational approaches.

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Section: Discussionmentioning

confidence: 99%

Consistency between In Situ, Model-Derived and High-Resolution-Image-Based Soil Temperature Endmembers: Towards a Robust Data-Based Model for Multi-Resolution Monitoring of Crop Evapotranspiration

et al. 2015

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“…Several methods have been developed to estimate ET from remotesensing data including empirical and statistical methods with remotely sensed vegetation indices [16][17][18], physical models that calculate ET as the residual of SEB using remotely sensed thermal infrared (IR) data [19][20][21][22][23][24][25], and other physical models such as the Penman-Monteith equations [26], the revised Resistance-Surface energy balance and the PenmanMonteith (RS-PM) equations [27][28][29] and Priestley-Taylor equations [30][31][32]. On a global or continental scales, the spatial ET is provided by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility (SAF) on Land Surface Analysis (LSA) and the National Aeronautics and Space Administration (NASA).…”

Section: Journal Of Sensorsmentioning

confidence: 99%

COMS-Based Retrieval of Daily Actual Evapotranspiration over Korea

Park¹,

Jang²,

Kim³

et al. 2017

Journal of Sensors

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Evapotranspiration (ET) from the land surface is an important hydrometeorological factor in the exchange of energy between the atmosphere and land surface. The accurate quantification for management of water resources and understanding of climate change are crucial, requiring continuous temporal and spatial monitoring. The objective of this study is to apply and estimate daily actual ET using semiempirical method, B-method, which is based on surface energy balance over heterogeneous area, Korea. To estimate daily ET, we used geostationary meteorological satellite data (Communication, Ocean and Meteorological Satellite, COMS) and polarorbiting satellite data (Système Pour l'Observation de la Terre, SPOT). Estimated daily ET using only satellite data was relatively accurate and reflects land surface characteristics. It had high periodicity and spatial resolution over a wide area on clear-sky days. The daily ET was overestimated by about 1 mm/day at the two flux tower measurements sites, but the simulated seasonal variation and pattern were in good agreement with flux tower measurements. In the mixed forest, the root-mean-square error (RMSE) was 0.94 mm/day and the bias was 1.05 mm/day, while, in the rice paddy, RMSE was 1.12 mm/day and bias was 1.21 mm/day.

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“…potential evapotranspiration -PET). Algorithms which produce global estimates of ET in this way are detailed in Nishida et al (2003), Leuning et al (2008), Mu et al (2007a), andFisher et al (2008). These models have been used in sub-Saharan Africa to estimate water use efficiency for arid rangelands (Palmer and Yanusa, 2011) and to extrapolate biological nitrogen deposition from wildfires (Chen et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach

Marshall

Funk

et al. 2013

Hydrol. Earth Syst. Sci.

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Abstract. Climate change is expected to have the greatest impact on the world's economically poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled evapotranspiration (ET), a key input in continental-scale hydrologic models. In this study, a remote sensing model of transpiration (the primary component of ET), driven by a time series of vegetation indices, was used to substitute transpiration from the Global Land Data Assimilation System realization of the National Centers for Environmental Prediction, Oregon State University, Air Force, and Hydrology Research Laboratory at National Weather Service Land Surface Model (GNOAH) to improve total ET model estimates for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against GNOAH ET and the remote sensing method using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance were at humid sites with dense vegetation, while performance at semi-arid sites was poor, but better than the models before hybridization. The reduction in errors using the hybrid model can be attributed to the integration of a simple canopy scheme that depends primarily on low bias surface climate reanalysis data and is driven primarily by a time series of vegetation indices.

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Development of an evapotranspiration index from aqua/MODIS for monitoring surface moisture status

Cited by 148 publications

References 14 publications

Consistency between In Situ, Model-Derived and High-Resolution-Image-Based Soil Temperature Endmembers: Towards a Robust Data-Based Model for Multi-Resolution Monitoring of Crop Evapotranspiration

Consistency between In Situ, Model-Derived and High-Resolution-Image-Based Soil Temperature Endmembers: Towards a Robust Data-Based Model for Multi-Resolution Monitoring of Crop Evapotranspiration

COMS-Based Retrieval of Daily Actual Evapotranspiration over Korea

Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach

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