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The remote sensing recognition and extraction of waste dump in mining area using multi-source and multi-temporal remote sensing data

机译:利用多源多时相遥感数据对矿区废料场进行遥感识别与提取

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The long-term emissions and accumulation of tailings can occupy cultivated land and lead to environmental pollution. In the paper Jining Yanzhou mining of Shandong as an example, analyzed the spectral characteristics of tailings and typical surface features of their surroundings. And year-2006 Quickbird data as a reference combined with the ground survey points to identify the large-scale waste dumps using remote sensing, and based on which for multi-temporal CBERS-2 data to classify, and analyzed each temporal data, and analyzed the main interfering factors that affect the classification accuracy. Finally, take the intersection of multi-temporal data and extract accurate waste dump area. The result shows tailings extraction in remote sensing recognition using multi-source and multi-temporal data can do more accurate extraction and the results further for tailings management provide the basis for the investigation.
机译:尾矿的长期排放和积累会占用耕地并导致环境污染。以山东济宁Yan州矿为例,分析了尾矿的光谱特征及其周围典型地表特征。并以2006年的Quickbird数据为参考,结合地面调查点,利用遥感识别大型垃圾场,并以此为基础对多时态CBERS-2数据进行分类,分析和分析各时态数据,并进行分析影响分类准确性的主要干扰因素。最后,获取多时间数据的交集,以提取准确的废物场面积。结果表明,利用多源,多时相数据进行遥感识别中的尾矿提取可以更准确地进行提取,为进一步进行尾矿管理提供了依据。

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