Publications

Tang, RL; Li, ZL; Liu, M; Jiang, YZ; Peng, Z (2022). A moisture-based triangle approach for estimating surface evaporative fraction with time-series of remotely sensed data. REMOTE SENSING OF ENVIRONMENT, 280, 113212.

Abstract
Evapotranspiration (ET) is a primary process for water and heat transfer between the land and atmosphere. The spatial contextual information-based surface temperature versus vegetation index triangle (temperature-based triangle) is one of the most famous and widely applied methods for regional ET estimation from remotely sensed data. However, the determination of temporally variable satellite scene-specific dry and wet edges in this traditional triangle is often largely biased due to the limited range of variability of surface soil moisture avail-ability and fractional vegetation cover (or the nonexistence of end-member pixels), or must rely on the auxiliary ground-based measurements, leading to a large uncertainty or difficulty in regional evaporative fraction esti-mation. This short communication presents a practically operational moisture-based triangle to address the deficiency of the temperature-based triangle, where temporally universal dry and wet edges in this new triangle are determined by making use of the time-series slope of remotely sensed surface temperature versus vegetation index negative relationship over a small window centering the target pixel. Our validation results show that this new triangle outperformed the temperature-based triangle, reducing the root mean square error from 0.19 to 0.16 and increasing the coefficient of determination from 0.44 to 0.53, when the model-estimated evaporative fractions were validated against ground-based eddy covariance measurements at 34 sites across the globe.

DOI:
10.1016/j.rse.2022.113212

ISSN:
1879-0704