Coverage Changes In Information Extraction, Based On The Cva Vegetation

Vegetation is one of the important components of the earth ecosystem, Vegetation Coverage, which is used to describe the ground cover situation of vegetation, is one of the important parameters of the earth's ecological climate. The research of vegetation coverage and its change has important significance for accurate understanding the dynamic variation trend of vegetation and its influence on ecological environment.With the development of remote sensing technology, remote sensing has more obvious advantage in the application of surface information acquisition. Under the diversified needs of Dynamic monitoring in vegetation coverage, using image change detection technology acquit the change information of vegetation coverage can comprehensively and quickly provides services to dynamic monitoring for vegetation coverage.In order to improve the extraction accuracy of vegetation coverage change information, this article make several amelioration of the Change Vector Analysis (CVA) and Artificial Neural Network (ANN) method based on the study and analyze the extracting technology of vegetation coverage and it's change information. Firstly, minimum noise fraction transform (MNF) is isolated noise of the images to reduce the impact of noise on the extracting results; and minimal classifying error is used to determine the segmentation threshold of change intensity and correlation coefficient, which are used to determine the change area. After that, the class end-members of ANN training samples are selected by pixel purity index (PPI) and the n-dimensional visualization method to extract the vegetation coverage, and this method can effectively reduce the impact of nonlinear factors; lastly, the data of change area and vegetation coverage are combined to extract the change information of vegetation coverage, and we can obtain a relatively high change information. For this improved methods, Interactive Data Language (IDL) and Arc Engine are used to develop special software in. NET to provide support for extracting change information. On the basis, the author extracts the vegetation coverage change information in northern Beijing between 2002-2009 and analyses its temporal-spatial pattern.