NDVI shadow influence removal method based on remote sensing multispectral images

Abstract

The invention relates to an NDVI shadow influence removing method based on remote sensing multispectral images. The method utilizes vegetation NDVI of a bright area in a multi-spectral remote sensingimage to modify vegetation NDVI of a shadow area, so as to remove the influence of the shadow on NDVI in the image. Compared with conventional methods, the method does not need multi-source data and complex processing process, and only relies on the information of remote sensing image itself. The method can remove the influence of shadow on NDVI index quickly and effectively, and improve its accuracy and accuracy. The method of the invention is efficient and effective in calculation, can quickly correct the influence of the universal shadow of the remote sensing image on the NDVI, provides a reliable data source for the application of the follow-up remote sensing inversion and remote sensing monitoring, and effectively improves the reliability of the NDVI in a series of applications such as environmental monitoring, vegetation growth monitoring, crop yield estimation, and the like.

Description

technical field [0001] The invention relates to the technical field of remote sensing vegetation index NDVI inversion, in particular to a method for removing NDVI shadow effects based on remote sensing multispectral images. Background technique [0002] The normalized difference vegetation index (NDVI) is currently the most widely used vegetation index in the field of remote sensing. It uses the typical characteristics of the plant spectrum (that is, the reflectance of vegetation in the visible light band is much smaller than that in the near-infrared band), and can effectively reflect the Vegetation information and vegetation vitality have become important technical means for multispectral remote sensing to retrieve biophysical and biochemical parameters such as chlorophyll content, vegetation coverage, leaf area index, biomass, net primary productivity (NPP) and photosynthetically active radiation absorption. NDVI occupies a very important position in the vegetation index,...

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is: in view of the problems of serious sacrifice of vegetation information, difficulty in obtaining multi-source data, complex heterogeneous data assimilation process, and neglect of real ground objects in existing methods, the present invention proposes a method based on remote sensing multispectral The NDVI shadow effect removal method of the image is based on the fact that most of the energy obtained by the vegetation in the shadow area in the image comes from the real physical process of solar scattering (sky light scattering) radiation, and only relies on the information of the image itself. Based on the NDVI of the bright area, the The NDVI of the shadow area is corrected to remove the shadow effect

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