Multi-temporal Mining Land Use/Cover Change Detection And Driving Factors Analysis

This paper mainly uses remote sensing for land use classification of the mine and analyses driving factors. Based on six remote sensing images and ENVI software, the information of land use and cover change were extracted. It helps us to understand accurately and effectively the information of land use and cover change in Luan Mining. Thus we analysis the information of land use and cover change, realize the dynamic process of land use and cover change, analysis a variety of driving forces behind land use and cover change, reveal the mechanism of and use and cover change. So that we can consciously adjust the human social and economic activities, for promoting more reasonable in land use. It is benefit for the long-term development of mine and does well in land development services.This paper is carried out the following work:1. Based on the maximum likelihood classification and decision tree classification to process mine images. The advantages and disadvantages of two classification methods were compared. By comparison, I obtain that the classification accuracy of maximum likelihood classification method is 86.57%, and the classification accuracy of decision tree classification method is 89.97%. The classification accuracy of decision tree classification method is higher, so the author adopt the decision tree classification method to classify LUAN mining area, access to mining land use and cover change map.2. One of mine (WANGZHUANG mine) is systematically analyzed, including land use status, land use change range, land use and cover change in speed, spatial variation of the transfer matrix, and the trend of mine. Combining natural and human factors, analysis the driving factors of WANGZHUANG mine land use and cover change. Overall, the grass coverage area is reduced, and the building area is increased. That indicates urbanization mine increasing.3. From CHANGZHI Statistics Bureau, we obtain CHANGZHI 2003-2007 National Economic and Social Development Statistics, and the related indicators factors form statistics are selected. With the help of SPSS17.0 software, the principal component of indicator factors is analyzed for the main driving factors, and these driving Natural and human-driven factors are analyzed.