A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed DataReport as inadecuate




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1

Institute of Geographic Sciences and Natural Resources Research, Beijing 100101, China

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LSIIT, Bld Sebastien Brant, BP10413, 67412 Illkirch, France

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Graduate University of Chinese Academy of Sciences, Beijing, 100049, China

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ICESS, University of California, Santa Barbara, CA 93106, USA

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Institute of Agricultural Resources and Regional Planning, Beijing 100081, China

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Beijing Normal University, Beijing 100875, China

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Shanxi University, Taiyuan 030006, China





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Author to whom correspondence should be addressed.



Abstract An overview of the commonly applied evapotranspiration ET models using remotely sensed data is given to provide insight into the estimation of ET on a regional scale from satellite data. Generally, these models vary greatly in inputs, main assumptions and accuracy of results, etc. Besides the generally used remotely sensed multi-spectral data from visible to thermal infrared bands, most remotely sensed ET models, from simplified equations models to the more complex physically based two-source energy balance models, must rely to a certain degree on ground-based auxiliary measurements in order to derive the turbulent heat fluxes on a regional scale. We discuss the main inputs, assumptions, theories, advantages and drawbacks of each model. Moreover, approaches to the extrapolation of instantaneous ET to the daily values are also briefly presented. In the final part, both associated problems and future trends regarding these remotely sensed ET models were analyzed to objectively show the limitations and promising aspects of the estimation of regional ET based on remotely sensed data and ground-based measurements. View Full-Text

Keywords: remote sensing; evapotranspiration; methodology; review; temporal scaling remote sensing; evapotranspiration; methodology; review; temporal scaling





Author: Zhao-Liang Li 1, 2,* , Ronglin Tang 1, 2, 3, Zhengming Wan 4, Yuyun Bi 2, 5, Chenghu Zhou 1, Bohui Tang 1, Guangjian Yan 6 and Xiaoyu Zhang 7

Source: http://mdpi.com/



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