
This work integrates AI algorithms and radiative transfer models to build high-precision quantitative remote sensing inversion methods. It accurately retrieves key physical and chemical parameters of the surface and atmosphere from spectral and radiometric data. Applications include vegetation, soil moisture, and water quality parameter inversion.

Based on multispectral remote sensing image data and integrated with high-precision quantitative remote sensing inversion algorithms, high-precision and refined inversion of vegetation fraction is realized, and the vegetation fraction and dynamic evolution information in the region are accurately obtained. It provides data support for regional ecological environment assessment and vegetation ecological restoration.The figure shows the vegetation coverage inversion results of a certain region.
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