Multi-temporal Mining Land Use/Cover Change Detection and Driving Factors Analysis
|School||Henan Polytechnic University|
|Course||Surveying and Mapping Engineering|
|Keywords||Mine Land use classification Maximum likelihood classification Decision tree classification Driving Factors|
In this paper, the use of remote sensing images of the mine land use classification as well as driving factors . Six remote sensing image based on the use of ENVI software Luan mining land use / land cover information extraction , Luan mining land use cover change contribute to a faster, more accurate, efficient , and thus land use / cover change analysis , to clear dynamic process , analysis of land use / cover various driving force behind the change , to reveal the mechanism of land use / cover change , so that the purpose of the adjustment of human social and economic activities , prompting land use is more reasonable , is conducive to the long-term development of the mines , land development services . Carried out the following tasks: 1. Maximum likelihood classification and decision tree classification of mine image . On this basis, compare the pros and cons of the two classification methods . Comparison , the maximum contingent method of classification accuracy of 86.57% , the decision tree classification method of classification accuracy of 89.97% , higher accuracy of decision tree classification , the use of decision tree classification method to be classified in Lu'an Coal Mine Mining Land use / cover change map . System on one of mine ( wangzhuang mine ) analysis, including Wangzhuang mine land use status , land-use change in amplitude , land use / cover changes in speed, spatial variation of the transfer matrix , and trend analysis of the mine . Overall, the reduction in mine vegetation area , building area increased , indicating that the mine increased urbanization phenomenon . Combination obtained from Changzhi Municipal Bureau of Statistics 2003-2007 Changzhi City National Economic and Social Development Statistics announced to select relevant indicators factor , principal component analysis in SPSS17.0 software help , the index factor , to obtain the main driver factor, and the main factor driving factors of natural and cultural analysis .