广东大宝山矿区植被污染信息的遥感识别方法研究

Study on recognition of vegetation contamination by remote sensing in Dabaoshan mine of Guangdong

为了探索遥感技术识别矿山植被污染信息的有效方法,基于ASTER和QuickBird 2种数据源,采用植被指数法和植被绿度法2种方法,对广东大宝山矿区的植被污染信息进行了识别研究。通过不同数据源、不同识别方法的对比分析,为遥感技术识别矿山植被污染信息的推广应用提供了工作思路和科学依据。

In order to explore an effective remote sensing method to mine vegetation contamination recognition,the authors recognized mine vegetation contamination of Dabaoshan mine in Guangdong Province,used the two methods of vegetation index and vegetation greenness,based on ASTER and QuickBird data. Through contrast analysis of different data sources,different recognition methods,the authors could provide a scientific basis and good working thought for the recognition of mine vegetation contamination using remote sensing technology.