Forest type recognition method based on high-score remote sensing images

Abstract

The invention relates to a forest type identification method based on high-score remote sensing images, which comprises the following steps: preprocessing the high-score remote sensing images to obtain panchromatic spectral images and multi-spectral images; performing gray scale extraction from panchromatic spectral image and vegetation index extraction from multi-spectral image; according to theforest resources survey data, analyzing the dominant tree species, and obtaining the gray value and vegetation index value of the dominant tree species. According to the classification standard of woodland, the research is divided into woodland and non-woodland. According to the correlation between grey value and vegetation index value, the recognition function models of related forest types are established respectively. The correlation function model is tested and evaluated; the correlation function model is applied to forest type recognition. The gray scale and vegetation index can be obtained by using the texture features of the high-score No. 2 image, which can identify the forest types, reasonably reduce the field investigation work of forest resources, and save the cost and resources.

Description

technical field [0001] The invention relates to a method for identifying forest types based on high-resolution remote sensing images. Background technique [0002] Forest type identification is an important part of forest resources management and monitoring. Traditional forest type identification methods are relatively backward, relying on a large number of manual field identification, which not only has a lot of work intensity, poor timeliness, inaccurate monitoring results, errors and timeliness, but also consumes a lot of manpower, material resources and Financial resources, and did not meet the expected requirements. As time changes, the state of forest resources will show dynamic changes, and traditional methods cannot accurately grasp the changes of forest types. [0003] With the successful launch of my country's domestic high-resolution series of remote sensing satellites, high-resolution remote sensing images have been widely used in earth observation. The textur...

AI Technical Summary

Problems solved by technology

Traditional forest type identification methods are relatively backward, relying on a large number of manual field identification, which not only has a lot of work intensity, poor timeliness, inaccurate monitoring results, errors and timeliness, but also consumes a lot of manpower, material resources and financial resources, and did not meet the expected requirements

As time changes, the state of forest resources will show dynamic changes, and traditional methods cannot accurately grasp the changes in forest types

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