基于遥感与核密度分析方法相结合的尾矿库分布研究

Study on the distribution of tailings pond based on the combination of remote sensing and kernel density analysis

我国尾矿库数量巨大,分布杂乱无章,及时掌握尾矿库的数量及分布情况对预防尾矿库事故和开展尾矿库应急工作具有重大意义。传统的调查方法主要以地面调查为主,难以做到对尾矿库的快速监测。文章以承德市为研究区,利用高分一号遥感图像对研究区内的尾矿库进行解译,并将尾矿库按照不同类型分类;同时结合研究区内的居民点数据利用核密度分析法对不同类型尾矿库的风险性评价。实验结果表明,承德市内共解译出尾矿库834座,通过对不同类型尾矿库的风险性评价,为相关部门对高风险地区的尾矿库监测和管理提供了科学依据。

The number of tailings pond in China is huge and the distribution is chaotic.Grasping the quantity and distribution of tailings pond in time is of great significance for preventing accidents and carrying out emergency work on tailings pond.The traditional survey methods are mainly ground-based survey,so it is difficult to achieve rapid monitoring of tailings pond.Taking Chengde City as the research area,the GF-1 remote sensing image is used to interpret the tailings pond in the research area and classify the tailings pond according to the different types.Meanwhile,the risk assessment of different types of tailingspond is carried out by nuclear density analysis method combined with residential data in the study area.The experimental results show that a total of 834 tailings pond have been interpreted in Chengde.The risk assessment of different types of tailings pond has provided scientific basis for the relevant departments to monitor and manage tailings ponds in the high-risk areas.