无人机遥感与卫星遥感在采煤地表裂缝识别中的对比  被引量:36

Contrast application of unmanned aerial vehicle remote sensing and satellite remote sensing technology relating to ground surface cracks recognition in coal mining area

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作  者:侯恩科[1] 张杰 谢晓深 徐友宁[2] HOU Enke;ZHANG Jie;XIE Xiaoshen;XU Youning(College of Geology and Environment,Xi’an University of Science and Technology,Xi’an 710054,Shaanxi,China;Xi’an Center of China Geological Survey,Xi’an 710054,Shaanxi,China)

机构地区:[1]西安科技大学地质与环境学院,陕西西安710054 [2]中国地质调查局西安地质调查中心,陕西西安710054

出  处:《地质通报》2019年第2期443-448,共6页Geological Bulletin of China

基  金:中国地质调查局项目<秦岭及宁东矿产资源集中开采区地质环境调查>(编号:DD20160336);国家自然科学基金项目<煤层顶板突水机理及突水危险性分区预测研究>(批准号:41472234)

摘  要:采煤诱发地表裂缝是地面塌陷最直观的表现形式之一,也是造成煤矿区环境恶化的主要因素。准确掌握地表裂缝的展布规律是煤矿区地面塌陷治理的基础。以宁夏金凤煤矿011805工作面为研究对象,对比分析卫星遥感影像与无人机遥感影像在地表裂缝调查、解译识别中的优缺点,总结工作面地表裂缝发育规律。研究表明,无人机航拍影像中裂缝整体视觉清晰,可充分反映出宽度大于5cm的地表裂缝的形态、长度、位置等发育特征,且解译出的地表裂缝发育规律更接近实际;无人机遥感不仅提高了煤矿区地表裂缝调查的精度和可靠性,也为地表裂缝各项研究提供了丰富的基础数据。The surface cracks induced by coal mining constitute one of the most intuitive manifestations of ground collapse and also the main factor causing the environmental deterioration in the coal mine.Thus accurately grasping the distribution law of surface cracks is the basis for the treatment of ground subsidence in the coal mine.In this paper,satellite remote sensing and unmanned aerial vehicle remote sensing technology were used to investigate the distribution of surface cracks of the 011805 working face which was selected as the research area.Research shows that in the aerial images of UAVs,the overall vision of ground cracks is clear,which can fully reflect the development characteristics including the shape,length,and location of ground cracks with a width greater than 5cm.and the interpretation results of the ground cracks are closest to reality.UAV remote sensing not only improves the accuracy and reliability of the surface crack investigation in the coal mining area but also provides abundant basic data for the study of the surface cracks.

关 键 词:地表裂缝 卫星遥感 无人机遥感 采煤塌陷 

分 类 号:TP79[自动化与计算机技术—检测技术与自动化装置]

 

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