Improved topographic radiation correction method

Abstract

The invention discloses an improved topographic radiation correction method. In a mountain remote sensing image, multiple times of reflection between the ground surface and the atmosphere are neglected, solar radiation received by the ground surface is summarized into a sum of direct solar radiation received by the ground surface, sky scattered radiation and near topographic reflection radiation, and the proposed model expression contains a topographic masking coefficient, and topographic radiation in topographic masking regions such as a mountain umbra and a falling shadow is considered; as influences of sky (diffused) scattered radiation and environment (topography) radiation are considered, radiation brightness information of the topographic masking regions can be well expressed, and radiation brightness values of a shady slope and a sunny slop are closer to real conditions. In addition, a k value obtained through linear fitting is more real and effective; and due to influences of research region topographic conditions and vegetation distribution characteristics, through introducing an average ground surface reflectance value around a target pixel to serve as an adjusting factor eliminating surrounding topographic each diffused effects, topographic masking region pixel radiation brightness value correction effects are improved.

Description

technical field [0001] The invention relates to the field of geographic science, in particular to an improved topographic radiation correction method. Background technique [0002] Terrain radiation correction refers to transforming the radiance value (or reflectance) of all pixels to a reference plane (usually a horizontal plane) through a physical model or an empirical or semi-empirical model, thereby eliminating the radiance caused by terrain effects. The change of the value can restore the real radiance value (or real reflectance) of the ground object under the horizontal condition. As an important step in radiometric correction of remote sensing images in mountainous areas, terrain radiation correction is the premise of quantitative remote sensing research. [0003] At present, scholars at home and abroad have done a lot of research work on the terrain radiation correction method, and a series of terrain radiation correction models proposed are becoming more and more m...

AI Technical Summary

Problems solved by technology

[0014] The disadvantage of the Minnaert model is that, first of all, the Minnaert model is based on the non-Lambertian body reflection theory, based on a purely empirical model, without a physical model basis, and its model is relatively random

Secondly, the Minnaert model does not consider the influence of the surrounding terrain reflection radiation on the radiance value of the shady slope pixel

A single k value plays a key role in the entire formula, however, the k value is a constant, suitable for areas with small slope changes, and in areas with large terrain fluctuations, the correction accuracy needs to be further improved by improving the model

Furthermore, the disadvantage of the Minnaert correction algorithm becomes apparent when forward or backscattering is introduced

[0015] In summary, the Minnaert model is based on the assumption of a non-Lambertian body, which solves the problem of overcorrection of shady slope pixels to a certain extent, but it ignores the isotropic diffuse radiation of the sky and the reflected radiation of the surrounding terrain, so there is a large change in terrain fluctuations. area, the correction accuracy is not good

In addition, in the process of solving the k value, the isotropic scattering of the sky and the reflected light of the environment are also ignored.

In the visible light band, the diffuse light of the sky accounts for a large proportion of the total incident irradiance (especially in the shady slope pixels), which causes the linear relationship between the dependent variable and the independent variable in the regression analysis to weaken, which will inevitably affect the accuracy of the k value. Thus affecting the final correction effect

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