Vegetation detection method and system for soil environment restoration

Through superpixel block analysis and clustering of remote sensing images, the vegetation coverage factor and artificial cultivation characteristics are quantified, and the problem that the spatial distribution characteristics of vegetation coverage areas are not considered is solved, and the accuracy of soil environmental restoration assessment is improved.

CN120451789AActive Publication Date: 2025-08-08SUZHOU VOCATIONAL INSTITUTE OF INDUSTRIAL TECHNOLOGY
7 Cites 2 Cited by

Patent Information

Application Number
CN202510548102.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-04-28
Publication Date
2025-08-08
Estimated Expiration
2045-04-28

AI Technical Summary

Technical Problem

The spatial distribution characteristics of vegetation-covered areas have not been effectively considered in the prior art, resulting in poor accuracy in soil environmental restoration assessment.

Method used

By acquiring multiple superpixel chunking of remote sensing images, analyzing the color characteristics and position distribution of pixel points, filtering out vegetation coverage chunking, and quantifying vegetation coverage factors and artificial cultivation characteristics using CANNY algorithm and PCA algorithm, combining K-means clustering to identify vegetation coverage clusters and non-vegetation coverage clusters, and calculating soil repair vegetation significance and weighted significance.

Benefits of technology

It improves the accuracy of soil environmental restoration assessment, accurately identify vegetation areas that are of great significance to soil restoration, and reflects the overall effect of soil restoration.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention relates to the technical field of soil image processing, in particular to a vegetation detection method and system for soil environment restoration. According to the method, color features and position distribution features of pixel points are analyzed, a vegetation coverage factor of each superpixel block is obtained, and vegetation coverage blocks are screened out; according to the position distribution of the pixel points in each vegetation coverage block and the chromaticity fluctuation characteristics, the artificial cultivation characteristic degree of each vegetation coverage block is obtained; according to the centroid position and the vegetation coverage factor of each superpixel block, obtaining a vegetation coverage class cluster and a non-vegetation coverage class cluster; and in combination with the relative position between each vegetation coverage block in each non-vegetation coverage class cluster and each vegetation coverage block in the adjacent vegetation coverage class cluster, obtaining the soil remediation vegetation significance of each super-pixel block, and further obtaining the soil remediation weighted significance of each super-pixel block. According to the method, the vegetation characteristics in the soil environment restoration process are accurately analyzed, so that the accuracy of soil environment restoration assessment is improved.
Need to check novelty before this filing date? Find Prior Art