高级检索
张俊阳,王 昆,赵同彬,等. 矿区地表沉陷与裂缝无人机遥感观测研究现状及发展[J]. 煤炭科学技术,xxxx,xx(x): x−xx. DOI: 10.12438/cst.2023-0438
引用本文: 张俊阳,王 昆,赵同彬,等. 矿区地表沉陷与裂缝无人机遥感观测研究现状及发展[J]. 煤炭科学技术,xxxx,xx(x): x−xx. DOI: 10.12438/cst.2023-0438
ZHANG Junyang,WANG Kun,ZHAO Tongbin,et al. Status and development of UAV remote sensing technology in mining surface subsidence and fracture measuring[J]. Coal Science and Technology,xxxx,xx(x): x−xx. DOI: 10.12438/cst.2023-0438
Citation: ZHANG Junyang,WANG Kun,ZHAO Tongbin,et al. Status and development of UAV remote sensing technology in mining surface subsidence and fracture measuring[J]. Coal Science and Technology,xxxx,xx(x): x−xx. DOI: 10.12438/cst.2023-0438

矿区地表沉陷与裂缝无人机遥感观测研究现状及发展

Status and development of UAV remote sensing technology in mining surface subsidence and fracture measuring

  • 摘要: 地下煤炭资源开发利用引发矿区地表沉陷与裂缝,不利于矿区生态环境保护和能源矿产持续稳定供应,对于矿区地表沉陷与裂缝的全面高效观测可提升采动地表损害认知水准、科学防治次生灾害。当前主流观测方法如地面测点人工施测、卫星遥感等存在人工作业强度高、造价昂贵、采集数据效率低等问题,卫星InSAR受波长限制难以获取大尺度变形。无人机遥感技术作为一种新兴地理信息获取方法,具备机动灵活、高效、可重复、全面覆盖等优势,在矿区地表沉陷与裂缝观测领域备受瞩目。系统梳理该领域国内外文献,分析前沿进展与发展态势,以促进矿山无人机遥感的技术革新与创新应用。首先,简要介绍无人机遥感技术要点及观测矿区地表沉陷与裂缝技术流程,无人机搭载可见光相机、激光雷达、红外热成像相机等传感器,生成数字高程模型(Digital Elevation Model, DEM)、数字正射影像(Digital Orthophoto Map, DOM)等遥感成果;在地表沉陷观测方面,分别列举文献案例分析沉陷区域地形获取、差分DEM沉陷模型及沉陷参数求取、水平位移观测3个方向的研究进展、技术难点与展望;在地表裂缝观测方面,介绍图像处理法、机器学习法与红外热成像观测识别裂缝的研究进展与问题;最终,从无人机遥感技术沉陷观测优势、裂缝背景噪声、裂缝预测及识别准确率、数据处理速度等方面展望未来发展方向。研究结果表明:① 无人机遥感技术可胜任矿区地表地形获取与沉陷观测,与InSAR等数据融合可提高沉陷参数求取精度;② 图像处理法、机器学习法等处理无人机遥感DOM可实现地表裂缝智能识别,深度学习被研究用于排除环境干扰、提高裂缝识别准确率;③ 地表水平位移与沉陷规律研究、裂缝识别率提高及其分布预测、航测数据的快速与自动化处理、多源遥感数据融合是该领域技术应用与研究的主要发展方向。无人机遥感技术在矿区地表沉陷与裂缝观测领域具有广阔前景,可从技术层面驱动矿山绿色、智能化发展转型。

     

    Abstract: The development and utilization of underground coal resources can cause the mining area surface subsidence and fractures and other hazards, which is not conducive to the protection of ecological environment and the sustainable and stable supply of energy and minerals in mining areas. Comprehensive and efficient measuring of surface subsidence and fractures in mining areas can improve the awareness level of mining damage and scientifically prevent secondary disasters. At present, the mainstream measure methods, such as manual measure of ground observation points and satellite remote sensing, have problems such as high operation intensity and expensive cost, and InSAR is difficult to obtain large-scale deformation due to wavelength limitation. As a new method of geographic information acquisition, Unmanned Aerial Vehicle Remote Sensing (UAVRS) technology has the advantages of flexibility, efficiency, accuracy, repeatability, and comprehensive coverage, and has become a research hotspot in mining area surface subsidence and fractures measuring. Systematic review of domestic and abroad literatures and analysis of frontier progress and development trend are conducive to technological innovation and application in this field. Firstly, the main points of UAVRS and the technical process of measuring surface subsidence and fractures in mining areas are introduced briefly. The UAV is equipped with visible light camera, LiDAR, infrared thermal imaging camera and other sensors, generate remote sensing results such as Digital Elevation Model (DEM) and Digital Orthophoto Map (DOM); Then, in terms of surface subsidence measuring, the research progress, technical difficulties and prospects of terrain acquisition, differential DEM subsidence model, subsidence parameters acquisition and horizontal displacement measuring are analyzed by citing literature cases. In the field of surface fractures measuring, the research progress and problems of image processing, machine learning and infrared thermal imaging are introduced. Finally, the future development direction is forecasted from the advantages of UAVRS technology in subsidence measuring, fractures background noise, fractures prediction and identification accuracy, and data processing speed. Research shows that: (1) UAVRS technology is competent for surface topography acquisition and subsidence measuring in mining areas, and fusion with InSAR data can improve the measuring accuracy of subsidence parameters; (2) Based on DEM acquired by UAVRS, image processing and machine learning methods can realize intelligent recognition of surface fractures, and deep learning is studied to eliminate environmental interference and improve the accuracy of fractures recognition; (3) The research of surface horizontal displacement and subsidence law, the improvement of fracture identification rate and its distribution prediction, the rapid and automatic processing of aerial survey data, and the fusion of multi-source remote sensing data are the main development directions of technology application and research in this field. UAVRS technology has broad prospects in the field of mining surface subsidence and fractures measuring, can drive the transformation of green and intelligent development of mines from the technical level.

     

/

返回文章
返回