文章摘要
周智勇,东启亮,韦锐,贺军亮.基于面向对象的露天花岗岩矿山信息提取技术研究[J].矿产勘查,2019,(10):2660-2666
基于面向对象的露天花岗岩矿山信息提取技术研究
Study on object-oriented information extraction technology in open-pit granite mine
投稿时间:2019-07-19  
DOI:
中文关键词: 露天花岗岩矿  面向对象  灰度共生矩阵  信息提取
英文关键词: open-pit granite mine, object-oriented, gray level co-occurrence matrix, information extraction
基金项目:中国地质调查局地质调查项目(编号:DD20190511、DD20190705)联合资助。
作者单位
周智勇 河北省水文工程地质勘查院,石家庄 050021
河北省遥感中心,石家庄 050021 
东启亮 河北省水文工程地质勘查院,石家庄 050021
河北省遥感中心,石家庄 050021 
韦锐 石家庄学院资源与环境科学学院,石家庄 050035 
贺军亮 石家庄学院资源与环境科学学院,石家庄 050035 
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中文摘要:
      矿山环境提取一直是遥感技术在矿山调查监测和治理应用中的重要环节。采用国产高分二号遥感数据,基于面向对象的分类方法,对山东省招远市北部花岗岩矿区独特的光谱特征和纹理特征进行分析,找出合适的特征参数并确定其阈值,从而构建决策树算法实现了研究区露天花岗岩矿山边界的自动提取,提取总体精度达到86.29%,Kappa系数达到0.807。
英文摘要:
      The extraction of mine environment has always been an important part of remote sensing technology in mine monitoring and treatment applications. Based on object-oriented classification method, this study used domestic high-resolution GF-2 remote sensing data to analyze the unique spectral features and texture features of the northern granite mining area in Zhaoyuan City, Shandong Province. Appropriate feature parameters were chosen and the threshold was determined. The decision tree algorithm was constructed to realize the automatic extraction of the open-pit granite mine boundary in the study area. The overall accuracy of the extraction was 86.29%, and the Kappa coefficient reached 0.807.
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