期刊
REMOTE SENSING
卷 6, 期 1, 页码 880-904出版社
MDPI
DOI: 10.3390/rs6010880
关键词
modified satellite-based Priestley-Taylor algorithm; PT-JPL algorithm; terrestrial evapotranspiration; vegetation index; apparent thermal inertia
类别
资金
- Natural Science Fund of China [41201331, 41331173, 41230747, 41101313]
- National High Technology Research and Development Program of China [2013AA121201]
- Fundamental Research Funds for the Central Universities [2013YB34]
- High Resolution Earth Observation Systems of National Science and Technology Major Projects [05-Y30B02-9001-13/15-9]
- National Science and Technology Support Plan During the 12th Five-year Plan Period of China [2012BAC19B03, 2013BAC10B01]
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/m(2) to 87.6 W/m(2), and with the square of correlation coefficient (R-2) 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 R-2 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.
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