Cloud shadow recognition method supported by priori data

Abstract

The invention relates to a cloud shadow identification method supported by priori data, in particular to a cloud shadow automatic detection method based on a real surface, and the specific process isshown as figure 1. Firstly, utilizing MOD09 A1 data to construct a real surface reflectance data set of a visible light near infrared band one scene every month; then, based on a 6S radiation transmission model; assuming that the ground pixels are uniform and have a Lambert surface; simulating the surface reflectance under the conditions of different atmospheric modes, aerosol types, observation geometries and aerosol optical thicknesses under the condition of a near infrared band of visible light under a sunny condition; according to the change condition of the apparent reflectance, constructing a lookup table of the apparent reflectance change based on the parameters, and nonlinearly fitting a minimum value of the apparent reflectance change by using a least square method according to lookup table data to obtain a cloud shadow detection algorithm of the to-be-detected sensor.

Description

technical field [0001] The invention relates to a cloud shadow recognition method supported by prior data, which is an automatic cloud shadow detection method based on the real surface and is applicable to various sensors. Background technique [0002] About 55% of the continent’s surface is covered by clouds. Due to the influence of factors such as weather, sensor observation angle, and solar zenith angle, most remote sensing images will have clouds and cloud shadows when they are acquired, making the surface information on remote sensing images It becomes blurred or even lost, and it is difficult to accurately obtain the spectral information of ground objects in the cloud shadow area, which brings difficulties to target recognition, classification, and information extraction, and seriously affects the interpretation effect and further application of remote sensing images. Therefore, using fast and effective The automatic identification of cloud shadows is the first problem...

AI Technical Summary

Problems solved by technology

At the same time, the problem of mixed pixels in the cloud shadow area is more serious, which makes cloud shadow identification more difficult. According to the spectral information of cloud shadow and underlying surface objects, it cannot effectively distinguish cloud shadow and dark surface area, and the fixed threshold method is easy to identify cloud shadow. Misjudgment of the dark surface

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