A Remote Sensing Inversion Method for Farmland Soil Moisture

Abstract

The invention discloses a remote sensing retrieval method for moisture of farmland soil. The method is based on an energy-balance equation and TVDI, and provides a quantitative dry and wet edges determination method and an improved TVQI model-temperature vegetation quantitative index (TVQI). The method is characterized in that A) forming a vegetation index-ground temperature characteristic space based on a remote sensing image observation value, according to the surface energy-balance equation, obtaining a quantitative dry edge, wherein the quantitative dry edge is determined by two points of Tds and Tdv; B) obtaining the quantitative wet edge, wherein the quantitative wet edge is determined by two points of Tws and Twv; and C) according to the TVQ1 model, calculating a soil moisture estimate value. The method overcomes restriction of vegetation cover types in calculation of VI-Ts characteristic space, and remote sensing retrieval precision of soil moisture can be increased.

Description

Technical field [0001] The invention relates to a remote sensing inversion method of farmland soil moisture, in particular to a remote sensing inversion method of farmland soil moisture based on an improved temperature vegetation drought index. Background technique [0002] Water is an important part of the earth system and plays a comprehensive role in various physical geographic research areas. Soil moisture in farmland is of great significance to crop growth and crop yield. The method of using remote sensing to monitor surface soil moisture has the advantages of wide range, high efficiency, and continuous time. At present, soil moisture remote sensing monitoring methods based on visible light-near infrared and thermal infrared bands mainly include vegetation index method, land surface temperature method, and characteristic space method. The vegetation index method indirectly reflects the water supply status of the soil through the response of vegetation in the sensitive band....

AI Technical Summary

Problems solved by technology

[0012] The Temperature Vegetation Dryness Index (TVDI) based on the Vegetation Index-Surface Temperature (VI-Ts) feature space is widely used in soil moisture monitoring, but there are two shortcomings: (1) High requirements on the type of land cover

Theoretically, the TVDI feature space should include three vegetation coverage conditions: bare soil, partial vegetation coverage, and full vegetation coverage, which makes it difficult to estimate areas with simple coverage types. In essence, it is only the edge existing in the feature space, rather than the theoretical dry and wet edge, so it causes great uncertainty; (2) TVDI is the relative value of soil moisture, which needs to be corrected to the estimated value of soil moisture after observation

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