Study of Extraction method Project of forestry slope position information based on hyperspectral remote sensing technology With Sustainability Requirements

Abstract

Abstract In order to solve the project problems of low accuracy of extraction of forestry information, small extraction area and incomplete extraction results in traditional methods, a forestry slope position information extraction method based on hyperspectral remote sensing technology was proposed here to select the study area and analyse its geographic profile. The data used in the study was Digital Elevation Model (DEM) raster data with a resolution of 25m, and the gradient information of the slope position was vaguely expressed. We calculated the fuzzy membership degree of the position to be inferred relative to each typical position in the type of slope position, and then synthesized the fuzzy membership degree of the position to be inferred relative to each typical position to obtain the gradient information of the slope position. Using hyperspectral remote sensing technology to identify forestry slope position, we matched the identified forestry slope position information, and finally extracted forestry slope position information based on statistical analysis technology. The experimental results showed that the forestry information extraction accuracy of the method in this paper is higher, the extraction area is larger and the extraction results are more comprehensive, indicating that our proposed method effectively improves the effect of forestry information extraction.