Remote sensing inversion method and system for surface evapotranspiration

Abstract

The invention discloses a remote sensing inversion method for surface evapotranspiration. The inversion method comprises the steps of acquiring meteorological data and remote sensing data of the surface; according to the meteorological data and the remote sensing data, calculating the soil temperature and vegetation temperature with the relative soil moisture being 0 and the soil temperature and vegetation temperature with the relative soil moisture being 1 respectively; calculating a soil dry edge temperature, a soil humidity limiting factor, a vegetation humidity limiting factor and a vegetation temperature limiting factor; and according to the soil humidity limiting factor, the vegetation humidity limiting factor and the temperature limiting factor, calculating the surface evaporation capacity by using a Priestley-Taylor formula. According to the method, the soil temperature and vegetation temperature with the relative soil moisture being 0 and the soil temperature and vegetation temperature with the relative soil moisture being 1 are introduced to calculate the limiting factors, the moisture change of the soil surface layer and the vegetation root area on the day scale can be reflected, and the accuracy of remote sensing inversion of surface evapotranspiration is improved by adopting an inversion method of surface evapotranspiration on the day scale.

Description

technical field [0001] The invention relates to the technical field of surface evapotranspiration calculation, in particular to a remote sensing inversion method and system for surface evapotranspiration. Background technique [0002] Surface evapotranspiration is an important part of surface energy balance and water cycle, and it is also an important indicator of vegetation growth and crop yield. Accurately estimating surface evapotranspiration on a regional or global scale is of great significance for global climate change research, water resource planning and management, agricultural water conservation, and crop yield estimation. However, evapotranspiration has strong spatial variability. Remote sensing technology has the characteristics of fast speed, high temporal and spatial resolution, and is suitable for long-term observation of large areas. effective means. [0003] Due to the instantaneous transit characteristics of remote sensing satellites, the surface evapotra...

AI Technical Summary

Problems solved by technology

However, the diurnal scale extension method is based on remote sensing inversion of instantaneous evapotranspiration, and the accuracy and applicability of different remote sensing inversion methods are different

Therefore, there are two uncertainties in most of the daily-scale surface evapotranspiration estimation results: (1) the uncertainty of the remote sensing inversion model; (2) the uncertainty of the diurnal scale extension method

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