An End-Member-Based Two-Source Approach for Estimating Land Surface Evapotranspiration From Remote Sensing Data

Evapotranspiration (ET) is one of the key variables in the water and energy exchange between land surface and atmosphere. This paper develops an end-member-based two-source approach for estimating land surface ET (i.e., the ESVEP model) from remote sensing data, considering the differing responses o...

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Veröffentlicht in:IEEE transactions on geoscience and remote sensing Jg. 55; H. 10; S. 5818 - 5832
Hauptverfasser: Tang, Ronglin, Li, Zhao-Liang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.10.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:0196-2892, 1558-0644
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Zusammenfassung:Evapotranspiration (ET) is one of the key variables in the water and energy exchange between land surface and atmosphere. This paper develops an end-member-based two-source approach for estimating land surface ET (i.e., the ESVEP model) from remote sensing data, considering the differing responses of soil water content at the upper surface layer to soil evaporation and at the deeper root zone layer to vegetation transpiration. The ESVEP model first diverges the soil-vegetation system net radiation into soil and vegetation components by considering the transmission of direct and diffuse shortwave radiation separately from the transmission of longwave radiation through the canopy, then calculates the four dry/wet soil/vegetation end-members with the diverged soil and vegetation net radiations, and last separates soil evaporation from vegetation transpiration based on the two-phase ET dynamics and the four end-member temperatures. The model can overall produce reasonably good surface energy fluxes and is no more sensitive to meteorology, vegetation, and remote sensing inputs than other two-source energy balance models and surface temperature versus vegetation index (T_{R} -VI) trapezoid models. A reasonable agreement could be found with a small bias of ±8 W/\text{m}^{2} and a root-mean-square error within 60 W/\text{m}^{2} (comparable to accuracies published in other studies) when both model-estimated sensible heat flux and latent heat flux from MODIS remote sensing data are validated with ground-based large aperture scintillometer measurements.
Bibliographie:ObjectType-Article-1
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ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2017.2715361