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

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Estimation of high-resolution terrestrial evapotranspiration from Landsat data using a simple Taylor skill fusion method. / Yao, Yunjun; Liang, Shunlin; Li, Xianglan; Zhang, Yuhu; Chen, Jiquan; Jia, Kun; Zhang, Xiaotong; Fisher, Joshua B.; Wang, Xuanyu; Zhang, Lilin; Xu, Jia; Shao, Changliang; Posse, Gabriela; Li, Yingnian; 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.

I: Journal of Hydrology, Vol. 553, 01.10.2017, s. 508-526.

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskrift

Harvard

Yao, Y, Liang, S, Li, X, Zhang, Y, Chen, J, Jia, K, Zhang, X, Fisher, JB, Wang, X, Zhang, L, Xu, J, Shao, C, Posse, G, Li, Y, Magliulo, V, Varlagin, A, Moors, EJ, Boike, J, Macfarlane, C, Kato, T, Buchmann, N, Billesbach, DP, Beringer, J, Wolf, S, Papuga, SA, Wohlfahrt, G, Montagnani, L, Ardö, J, Paul-Limoges, E, Emmel, C, Hörtnagl, L, Sachs, T, Gruening, C, Gioli, B, López-Ballesteros, A, Steinbrecher, R & Gielen, B 2017, 'Estimation of high-resolution terrestrial evapotranspiration from Landsat data using a simple Taylor skill fusion method', Journal of Hydrology, vol. 553, s. 508-526. https://doi.org/10.1016/j.jhydrol.2017.08.013

APA

CBE

Yao Y, Liang S, Li X, Zhang Y, Chen J, Jia K, Zhang X, Fisher JB, Wang X, Zhang L, Xu J, Shao C, Posse G, Li Y, Magliulo V, Varlagin A, Moors EJ, Boike J, Macfarlane C, Kato T, Buchmann N, Billesbach DP, Beringer J, Wolf S, Papuga SA, Wohlfahrt G, Montagnani L, Ardö J, Paul-Limoges E, Emmel C, Hörtnagl L, Sachs T, Gruening C, Gioli B, López-Ballesteros A, Steinbrecher R, Gielen B. 2017. Estimation of high-resolution terrestrial evapotranspiration from Landsat data using a simple Taylor skill fusion method. Journal of Hydrology. 553:508-526. https://doi.org/10.1016/j.jhydrol.2017.08.013

MLA

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Author

Yao, Yunjun ; Liang, Shunlin ; Li, Xianglan ; Zhang, Yuhu ; Chen, Jiquan ; Jia, Kun ; Zhang, Xiaotong ; Fisher, Joshua B. ; Wang, Xuanyu ; Zhang, Lilin ; Xu, Jia ; Shao, Changliang ; Posse, Gabriela ; Li, Yingnian ; 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. / Estimation of high-resolution terrestrial evapotranspiration from Landsat data using a simple Taylor skill fusion method. I: Journal of Hydrology. 2017 ; Vol. 553. s. 508-526.

RIS

TY - JOUR

T1 - Estimation of high-resolution terrestrial evapotranspiration from Landsat data using a simple Taylor skill fusion method

AU - Yao, Yunjun

AU - Liang, Shunlin

AU - Li, Xianglan

AU - Zhang, Yuhu

AU - Chen, Jiquan

AU - Jia, Kun

AU - Zhang, Xiaotong

AU - Fisher, Joshua B.

AU - Wang, Xuanyu

AU - Zhang, Lilin

AU - Xu, Jia

AU - Shao, Changliang

AU - Posse, Gabriela

AU - Li, Yingnian

AU - Magliulo, Vincenzo

AU - Varlagin, Andrej

AU - Moors, Eddy J.

AU - Boike, Julia

AU - Macfarlane, Craig

AU - Kato, Tomomichi

AU - Buchmann, Nina

AU - Billesbach, D. P.

AU - Beringer, Jason

AU - Wolf, Sebastian

AU - Papuga, Shirley A.

AU - Wohlfahrt, Georg

AU - Montagnani, Leonardo

AU - Ardö, Jonas

AU - Paul-Limoges, Eugénie

AU - Emmel, Carmen

AU - Hörtnagl, Lukas

AU - Sachs, Torsten

AU - Gruening, Carsten

AU - Gioli, Beniamino

AU - López-Ballesteros, Ana

AU - Steinbrecher, Rainer

AU - Gielen, Bert

PY - 2017/10/1

Y1 - 2017/10/1

N2 - 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.

AB - 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.

KW - Eddy covariance

KW - Fusion method

KW - High-resolution products

KW - Landsat data

KW - Terrestrial evapotranspiration

U2 - 10.1016/j.jhydrol.2017.08.013

DO - 10.1016/j.jhydrol.2017.08.013

M3 - Article

VL - 553

SP - 508

EP - 526

JO - Journal of Hydrology

JF - Journal of Hydrology

SN - 0022-1694

ER -