Research And Application For Image Change Detection Of Vegetation Coverage Area By Multitemporal Remote Sensing Images

In recent years,the development of the technology of remote sensing image change detection becomes more mature, it is moving towards the comprehensive application stage,with the application of the technology of remote image change detection continues to improve, it is applications are more and more extensive,it occupies very important role in agriculture and forestry, environments protection, land and other fields.The paper analyses the development and present situation of test method for vegetation coverage area’s change bymultitemporal remote sensing images, introduces the basic knowledge of remoting sensing image change detection systematicly, analyses the test method for vegetation coverage area’s change with multi-temporal satellite image existing, Gamma correction was modified, constructs the learning algorithm of vegetation coverage area’s station work based on the CIE Lab color space, proposes a detection method of vegetation coverage’s change, and both uses the theoretical analysis and experimental verification combined, proves that the method can improve the accuracy of change detection in a certain extent.In this paper, research results and conclusions are as follows:1) To make the color multi-temporal remote sensing images is reduced, the paper Gamma correction process remote sensing image pre-processing stage, the revised calculation method Gamma correction, reducing its output range, to reduce chromatic aberration purposes.2)Build a new CIE Lab color space in vegetation cover regional groupings training learning algorithm, used to detect temporal remote sensing images of vegetation coverage area. Verified by comparing the experimental results, it improves the image of remote sensing of vegetation coverage change detection accuracy.3) The proposed multi-temporal coverage of vegetation change detection methods applied to major national special project "High-resolution Earth Observation business processing platform" system, and achieved good results.