Remote estimation of terrestrial evapotranspiration without using meteorological data
作者： Di Long , Songhao Shang , Yuting Yang
DOI: 10.1002/GRL.50450
关键词: Estimation 、 Satellite data 、 Evapotranspiration 、 Satellite remote sensing 、 Primary production 、 Environmental science 、 Eddy covariance 、 Meteorology
摘要: [1] We developed a new method to estimate terrestrial evapotranspiration (ET) from satellite data without using meteorological inputs. By analyzing observations 20 eddy covariance tower sites across continental North America, we found strong relationship between monthly gross primary production (GPP) and ET (R2 = 0.72–0.97), implying the potential of remotely sensed GPP invert ET. We therefore adopted Temperature-Greenness model which calculates 16 day MODIS EVI LST products then calculate by dividing with ecosystem water use efficiency (the ratio ET). The proposed estimated very well comparison tower-based measurements (R2 = 0.84, p < 0.001, n = 1290) provided better estimates than product. This suggests that routine estimation remote sensing fine-resolution fields is possible can be useful for studying carbon cycles.
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