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金属矿山 ›› 2012, Vol. 41 ›› Issue (10): 90-92+96.

• 地质与测量 • 上一篇    下一篇

无人机影像提取矿区地裂缝信息技术研究

魏长婧1,2,3,汪云甲1,2,3,王坚1,2,3,赵慧1,2,3   

  1. 1.中国矿业大学(徐州)环境与测绘学院;2.江苏省资源环境信息工程重点实验室;3.国土环境与灾害监测国家测绘局重点实验室
  • 出版日期:2012-10-15 发布日期:2012-11-08
  • 基金资助:

    * 国家自然科学基金项目(编号:50774080;40971275),中国矿业大学青年基金项目(编号:OP090212),江苏高校优势学科建设工程项目(编号:PAPD)。

The Technical Research of Extracting Ground Fissure Information in Mining Area with the UAV Image

Wei Changjing1,2,3,Wang Yunjia1,2,3,Wang Jian1,2,3,Zhao Hui1,2,3   

  1. 1.School of Environment Science and Spatial Informatics,China University of Mining and Technology,Xuzhou;2.Jiangsu Key Laboratory of Resources and Environmental Information Engineering;3.Key laboratory for Resources Environment and Disaster Monitoring of SBSM
  • Online:2012-10-15 Published:2012-11-08

摘要: 针对矿区地裂缝信息提取问题展开研究,采用无人机影像和TM影像为数据源,通过提取研究区的纹理特征、线性特征、分形维数、NDVI值以及光谱特征,利用ERDAS软件建立知识模型,成功提取出矿区地裂缝信息分布图,并对提取结果进行精度验证,证明该方法具有较高的精度。

关键词: 无人机, 矿区, 地裂缝, 知识模型, 自动提取

Abstract: The research is conducted with the problem of extracting ground fissure information in mining area. The UAV and TM images are used as data sources. Through the extraction of texture feature,linear characteristics,fractal dimension,the NDVI values and spectral features,and using the ERDAS software,a knowledge model is built,and the distribution graphs about ground fissure information is successfully extracted. It proves that the method has higher precision after precision verification on the extraction results.

Key words: UAV, Mining area, Ground fissure, Knowledge model, Automatic extraction