Evapotranspiration remote sensing inversion method and system based on combination of GF-4 and MODIS

Abstract

The invention provides an evapotranspiration remote sensing inversion method and system based on combination of GF-4 and MODIS. The method includes: acquiring GF-4 data and MODIS data of a target area, and obtaining surface key parameters on the basis of the GF-4 data and the MODIS data; based on the surface key parameters, obtaining the heat flux exchange data between uniform surface and atmosphere by using the surface energy balance model SEBAL; based on the heat flux exchange data, carrying put decomposition by using an energy balance model TSEB, and obtaining the heat flux exchange data ofvegetation canopy and soil; performing calculation according to the data of canopy heat flux exchange and soil heat flux exchange, and obtaining instantaneous evapotranspiration; carrying out time-daily scale conversion on the instantaneous evapotranspiration, and obtaining daily evapotranspiration in the target area. In combination with the GF-4 data and the MODIS data, the high-precision ET results can be obtained by fusing the multi-source sensor data with different spatial resolution.

Description

technical field [0001] The invention relates to the technical field of evapotranspiration inversion, in particular to an evapotranspiration remote sensing inversion method and system based on the combination of GF-4 and MODIS. Background technique [0002] Evapotranspiration (evapotranspiration, ET) is an important part of the water cycle in the earth-atmosphere system, and it is also the most difficult to estimate in the surface energy cycle, water cycle and carbon cycle. In arid and semi-arid areas, evapotranspiration accounts for more than 80% of the total water consumption in farmland ecosystems. Therefore, quantitative calculation of evapotranspiration is of great significance for implementing agricultural hydrological cycle simulations and guiding agricultural water management. Especially in irrigation areas with complex and fragmented planting structures, it has a greater effect. [0003] The development of remote sensing technology has made it possible to estimate r...

AI Technical Summary

Problems solved by technology

With the rapid development of earth observation technology, more and more remote sensing data sources are available, and the existing embodiments are still generally limited to the inversion of ET based on a single sensor data

However, affected by uncertain factors such as clouds, rain, fog / haze, different sensor parameters and spatial resolutions, revisit cycles, and complex land surfaces during image acquisition, a single sensor can obtain less data during the entire growth period of crops. The spatio-temporal continuity is poor, resulting in a large gap between the regional adaptability of its ET inversion results and the commercialization of precision agricultural monitoring

Images