Vegetation Change Detection Based on TM and SPOT Images Spectrum Fusion in the Typical Area of Xishuangbanna Area
There are many tropical forest resources in Xishuangbanna area; it is a very important status in China. But because a large number of rubber plantations are expanding as far as possible and the areas of urban construction land are increasing, the areas of tropical forest are decreasing rapidly, which lead to serious fragmentation. In the paper, we choose the typical area of Xishuangbanna area as the research area to study the vegetation change trajectory using ETM and SPOT images acquired on different time. On the base of data pretreatment, two aspects researches were carried out. On the one hand, spectral information and NDVI information of each type of vegetation were analyzed to classify the ETM and SPOT images using the method of decision tree respectively. By classification post-processing, we could get the ways of the vegetation type conversion. On the other hand, ETM and SPOT PAN Images were integrated by the PCA to acquire the information of vegetation change including vegetation gain or loss. Finally, comprehensive information on two aspects of the vegetation changes was analyzed to acquire the vegetation change trajectory from 2000 to 2007 in the Xishuangbannan area. The result showed vegetation conversions that changed from one type to another type were frequent. A larger proportion of other type vegetation was transformed to rubber plantations.
Weiguo Pan, Jianxing Ren and Yongguang Li
Y. F. Li and G. H. Liu, "Vegetation Change Detection Based on TM and SPOT Images Spectrum Fusion in the Typical Area of Xishuangbanna Area", Advanced Materials Research, Vols. 347-353, pp. 2393-2399, 2012