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Remote Sens. 2014, 6(1), 880-904; doi:10.3390/rs6010880
Article

Validation and Application of the Modified Satellite-Based Priestley-Taylor Algorithm for Mapping Terrestrial Evapotranspiration

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1 State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, No.19 Xinjiekou Street, Beijing 100875, China 2 Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA 3 Ministry of Environmental Protection, Environmental Satellite Center, East Road of Yongfeng Base, Beijing 100094, China 4 College of Resource Environment and Tourism, Capital Normal University, No.105 North Road, Beijing 100048, China 5 Institute of Remote Sensing and GIS, Peking University, No.5 Yiheyuan Road, Beijing 100871, China 6 School of Earth Sciences and Engineering, Hohai University, No.1 Xikang Road, Nanjing, 210098, China 7 College of Earth Sciences, Chengdu University of Technology, No.1 Erxian Bridge Road, Chengdu 610059, China
* Author to whom correspondence should be addressed.
Received: 24 November 2013 / Revised: 2 January 2014 / Accepted: 3 January 2014 / Published: 17 January 2014
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Abstract

Satellite-based vegetation indices (VIs) and Apparent Thermal Inertia (ATI) derived from temperature change provide valuable information for estimating evapotranspiration (LE) and detecting the onset and severity of drought. The modified satellite-based Priestley-Taylor (MS-PT) algorithm that we developed earlier, coupling both VI and ATI, is validated based on observed data from 40 flux towers distributed across the world on all continents. The validation results illustrate that the daily LE can be estimated with the Root Mean Square Error (RMSE) varying from 10.7 W/m2 to 87.6 W/m2, and with the square of correlation coefficient (R2) from 0.41 to 0.89 (p < 0.01). Compared with the Priestley-Taylor-based LE (PT-JPL) algorithm, the MS-PT algorithm improves the LE estimates at most flux tower sites. Importantly, the MS-PT algorithm is also satisfactory in reproducing the inter-annual variability at flux tower sites with at least five years of data. The R2 between measured and predicted annual LE anomalies is 0.42 (p = 0.02). The MS-PT algorithm is then applied to detect the variations of long-term terrestrial LE over Three-North Shelter Forest Region of China and to monitor global land surface drought. The MS-PT algorithm described here demonstrates the ability to map regional terrestrial LE and identify global soil moisture stress, without requiring precipitation information.
Keywords: modified satellite-based Priestley-Taylor algorithm; PT-JPL algorithm; terrestrial evapotranspiration; vegetation index; apparent thermal inertia modified satellite-based Priestley-Taylor algorithm; PT-JPL algorithm; terrestrial evapotranspiration; vegetation index; apparent thermal inertia
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Yao, Y.; Liang, S.; Zhao, S.; Zhang, Y.; Qin, Q.; Cheng, J.; Jia, K.; Xie, X.; Zhang, N.; Liu, M. Validation and Application of the Modified Satellite-Based Priestley-Taylor Algorithm for Mapping Terrestrial Evapotranspiration. Remote Sens. 2014, 6, 880-904.

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