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Remote Sens. 2017, 9(1), 26; doi:10.3390/rs9010026

A New Contextual Parameterization of Evaporative Fraction to Reduce the Reliance of the TsVI Triangle Method on the Dry Edge

Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
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Academic Editors: Soe Myint, Richard Müller and Prasad S. Thenkabail
Received: 29 September 2016 / Revised: 13 December 2016 / Accepted: 17 December 2016 / Published: 4 January 2017
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Abstract

In this study, a new parameterization scheme of evaporative fraction (EF) was developed from the contextual information of remotely sensed radiative surface temperature ( T s ) and vegetation index (VI). In the traditional T s V I triangle methods, the Priestley-Taylor parameter of each pixel was interpolated for each VI interval; in our proposed new parameterization scheme (NPS), it was performed for each isopiestic line of soil surface moisture. Specifically, of mixed pixels was determined as the weighted-average value of bare soil and full-cover vegetation . The maximum T s of bare soil ( T s m a x ) is the sole parameter needed as the constraint of the dry edge. This has not only bypassed the task involved in the determination of the maximum T s of fully vegetated surface ( T c m a x ), but also made it possible to reduce the reliance of the T s V I triangle methods on the determination of the dry edge. Ground-based measurements taken during 21 days in 2004 were used to validate the EF retrievals. Results show that the accuracy achieved by the NPS is comparable to that achieved by the traditional T s V I triangle methods. Therefore, the simplicity of the proposed new parameterization scheme does not compromise its accuracy in monitoring EF. View Full-Text
Keywords: evaporative fraction; TsVI triangle method; TVX method; MODIS evaporative fraction; TsVI triangle method; TVX method; MODIS
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MDPI and ACS Style

Zhu, W.; Lv, A.; Jia, S.; Yan, J. A New Contextual Parameterization of Evaporative Fraction to Reduce the Reliance of the TsVI Triangle Method on the Dry Edge. Remote Sens. 2017, 9, 26.

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