Estimation of Terrestrial Latent Heat Flux Based on Chinese GaoFen-1
Remote Sensing Data
Abstract
Accurate estimation of terrestrial latent heat flux (LE) at high spatial
resolution is of great vital importance for energy balance and water
resource management, especially for agricultural production at field
scale. However, there are relatively few LE products based on Chinese
GaoFen-1 (GF-1) remote sensing data. In this study, we used GF-1
satellite data with a 16 m spatial resolution over the part regions of
Ethiopia, Laos and Pakistan, and generated the LE products using
Modified Satellite-based Priestley-Taylor model. LE products based on
GF-1 data were aggregated to a 1 km spatial resolution to be validated
by Global LAnd Surface Satellite (GLASS) LE products with the same
spatial resolution as reference values. The validation results
demonstrated that the 16 m GF and 1 km GLASS LE products of the three
countries all presented good spatial consistency, and the coefficient of
determination of LE estimates based on GF-1 data against GLASS LE
products were all greater than 0.6, indicating that the accuracy of LE
products based on GF-1 data was high. LE estimation based on GF-1 data
is of great significance for energy balance and water resource precision
management.