Estimation of high-resolution terrestrial evapotranspiration from Landsat data using a simple Taylor skill fusion method

Estimation of high-resolution terrestrial evapotranspiration (ET) from Landsat data is important in many climatic, hydrologic, and agricultural applications, as it can help bridging the gap between existing coarse-resolution ET products and point-based field measurements. However, there is large unc...

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Bibliographic Details
Published in:Journal of Hydrology
Main Authors: Yunjun, Yao, Shunlin, Liang, Yuhu, Zhang, Jiquan, Chen, Xianglan, Li, Kun, Jia, Xiaotong, Zhang, Fisher, Joshua B., Xuanyu, Wang, Lilin, Zhang, Jia, Xu, Changliang, Shao, Posse Beaulieu, Gabriela, Yingnian, Li, Magliulo, Vincenzo, Varlagin, Andrej, Moors, Eddy J., Boike, Julia, Macfarlane, Craig, Kato, Tomomichi, Buchmann, Nina, Billesbach, D.P., Beringer, Jason, Wolf, Sebastian, Papuga, Shirley A., Wohlfahrt, Georg, Montagnani, Leonardo, Ardö, Jonas, Paul-Limoges, Eugénie, Emmel, Carmen, Hörtnagl, Lukas, Sachs, Torsten, Gruening, Carsten, Gioli, Beniamino, López-Ballesteros, Ana, Steinbrecher, Rainer, Gielen, Bert
Format: Article in Journal/Newspaper
Language:English
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/20.500.12123/1551
https://www.sciencedirect.com/science/article/pii/S0022169417305395
https://doi.org/10.1016/j.jhydrol.2017.08.013
Description
Summary:Estimation of high-resolution terrestrial evapotranspiration (ET) from Landsat data is important in many climatic, hydrologic, and agricultural applications, as it can help bridging the gap between existing coarse-resolution ET products and point-based field measurements. However, there is large uncertainty among existing ET products from Landsat that limit their application. This study presents a simple Taylor skill fusion (STS) method that merges five Landsat-based ET products and directly measured ET from eddy covariance (EC) to improve the global estimation of terrestrial ET. The STS method uses a weighted average of the individual ET products and weights are determined by their Taylor skill scores (S). The validation with site-scale measurements at 206 EC flux towers showed large differences and uncertainties among the five ET products. The merged ET product exhibited the best performance with a decrease in the averaged root-mean-square error (RMSE) by 2–5 W/m2 when compared to the individual products. To evaluate the reliability of the STS method at the regional scale, the weights of the STS method for these five ET products were determined using EC ground-measurements. An example of regional ET mapping demonstrates that the STS-merged ET can effectively integrate the individual Landsat ET products. Our proposed method provides an improved high-resolution ET product for identifying agricultural crop water consumption and providing a diagnostic assessment for global land surface models. Inst. de Clima y Agua Fil: Yunjun, Yao. Beijing Normal University. Faculty of Geographical Science. State Key Laboratory of Remote Sensing Science; China Fil: Shunlin, Liang. Beijing Normal University. Faculty of Geographical Science. State Key Laboratory of Remote Sensing Science; China Fil: Xianglan, Li. Beijing Normal University. College of Global Change and Earth System Science; China Fil: Yuhu, Zhang. Capital Normal University. College of Resource Environment and Tourism; China Fil: Jiquan, Chen. Michigan State University. CGCEO/Geography; Estados Unidos Fil: Kun, Jia. Beijing Normal University. Faculty of Geographical Science. State Key Laboratory of Remote Sensing Science; China Fil: Xiaotong, Zhang. Beijing Normal University. Faculty of Geographical Science. State Key Laboratory of Remote Sensing Science; China Fil: Fisher, Joshua B. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Xuanyu, Wang. Beijing Normal University. Faculty of Geographical Science. State Key Laboratory of Remote Sensing Science; China Fil: Lilin, Zhang. Beijing Normal University. Faculty of Geographical Science. State Key Laboratory of Remote Sensing Science; China Fil: Jia, Xu. Beijing Normal University. Faculty of Geographical Science. State Key Laboratory of Remote Sensing Science; China Fil: Changliang, Shao. Michigan State University. CGCEO/Geography; Estados Unidos Fil: Posse Beaulieu, Gabriela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina Fil: Yingnian, Li. Chinese Academy of Sciences. Northwest Institute of Plateau Biology; China Fil: Magliulo, Vincenzo. Consiglio Nazionale delle Ricerche. Institute of Mediterranean Forest and Agricultural Systems; Italia Fil: Varlagin, Andrej. Russian Academy of Sciences. A.N. Severtsov Institute of Ecology and Evolution; Rusia Fil: Moors, Eddy J. Wageningen University and Research, Wageningen Environmental Research; Holanda Fil: Boike, Julia. Alfred Wegener Institute for Polar and Marine Research; Alemania Fil: Macfarlane, Craig. Commonwealth Scientific and Industrial Research Organisation (CSIRO) Land and Water; Australia Fil: Kato, Tomomichi. Hokkaido University. Research Faculty of Agriculture; Japón Fil: Buchmann, Nina. ETH Zurich. Department of Environmental Systems Science; Suiza Fil: Billesbach, D.P. University of Nebraska. Department of Biological Systems Engineering and School of Natural Resources; Estados Unidos Fil: Beringer, Jason. University of Western Australia. School of Agriculture and Environment; Australia Fil: Wolf, Sebastian. ETH Zurich. Department of Environmental Systems Science; Suiza Fil: Papuga, Shirley A. University of Arizona. School of Natural Resources and the Environment; Estados Unidos Fil: Wohlfahrt, Georg. University of Innsbruck. Institute of Ecology; Austria Fil: Montagnani, Leonardo. Free University of Bolzano. Faculty of Science and Technology; Italia Fil: Ardö, Jonas. Lund University. Physical Geography and Ecosystem Science; Suecia Fil: Paul-Limoges, Eugénie. ETH Zurich. Department of Environmental Systems Science; Suiza Fil: Emmel, Carmen. ETH Zurich. Department of Environmental Systems Science; Suiza Fil: Hörtnagl, Lukas. ETH Zurich. Department of Environmental Systems Science; Suiza Fil: Sachs, Torsten. GFZ German Research Centre for Geosciences, Section Remote Sensing; Alemania Fil: Gruening, Carsten. European Commission, Joint Research Centre; Italia Fil: Gioli, Beniamino. National Research Council. Institute of Biometeorology; Italia Fil: López-Ballesteros, Ana. University of Granada. Faculty of Sciences. Department of Ecology; España Fil: Steinbrecher, Rainer. Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research (IMK-IFU); Alemania Fil: Gielen, Bert. University of Antwerp. Department of Biology. Centre of Excellence PLECO; Bélgica