高奎英，都伟冰，陈建华,等. OT技术联合无人机LiDAR在矿区地表沉陷监测中的应用研究[J].河南理工大学学报(自然科学版), doi:10.16186/j.cnki.1673-9787.2023110010.

GAO K Y, DU W B,CHEN J H,et al. Application research of OT technology combined with UAV LiDAR in surface subsidence monitoring of mining area [J].Journal of Henan Polytechnic University( Natural Science),doi:10.16186/j.cnki.1673-9787. 2023110010.

OT技术联合无人机LiDAR在矿区地表沉陷监测中的应用研究(网络首发)

高奎英¹，都伟冰²，陈建华¹，杨彬²，张合兵²，徐朝¹，冯志忠¹，张文志²

(1.国能神东煤炭集团大柳塔煤矿，陕西 神木 719315; 2.河南理工大学 测绘与国土信息工程学院，河南 焦作 454000)

摘要: 目的 为充分发挥不同尺度遥感监测在识别高强度煤炭开采地表形变上的应用价值，方法 利用卫星影像偏移量追踪技术和无人机激光雷达技术分别获取矿区尺度和工作面尺度的典型沉陷区及其参数，并结合地面观测站数据论证这两种不同尺度遥感监测的差异性。结果 以神东矿区两景合成孔径雷达影像为例，利用偏移量追踪技术得到研究时段内矿区多处于地表沉陷中心，沉陷值为−3.8～0 m。无人机激光雷达技术有效识别出工作面尺度上的沉陷范围和量级，二次和三次采动区的地表沉陷量高于一次采动区的，有井下煤柱存在的区域沉陷量较小，沉陷量为−1.17～0 m。对比分析工作面两处典型区域无人机激光雷达差分数据与卫星偏移量追踪结果的差别，沉陷量较小的区域，偏移量追踪技术精度较高，沉陷量较大的区域，无人机激光雷达技术精度较高，两者得到下沉系数分别为 0.61 和 0.72，说明无人机激光雷达获取的下沉系数更接近地面实测下沉系数。结论 研究结果可为大范围和高效开采沉陷监测提供参考。

关键词: 高强度开采；偏移量追踪；无人机激光雷达；开采沉陷

中图分类号：TD353　

doi:10.16186/j.cnki.1673-9787. 2023110010

基金项目: ：国家自然科学基金资助项目（U22A20620，U22A20620/003，U21A20108）；河南省科技攻关项目（222102320306）；中国神华能源股份有限公司神东煤炭分公司委托项目（技术研究院 HT （2023）16 号）

收稿日期：：2023-11-07

修回日期：2024-02-04

网络首发日期：2024-03-07

Application research of OT technology combined with UAV LiDAR in surface subsidence monitoring of mining area(Online)

GAO Kuiying1，DU Weibing2，CHEN Jianhua1，YANG Bin2，ZHANG Hebing2，XU Zhao1，FENG Zhizhong1，ZHANG Wenzhi2

（1.Daliuta Coal Mine，China Energy Shengdong Coal Group Co.，Ltd.，Shenmu 719315，Shaanxi，China；2.School of Surveying and Land Information Engineering，Henan Polytechnic University，Jiaozuo 454000，Henan，China）

Abstract: Objective In order to give full play to the application value of different scale remote sensing monitoring methods in identifying surface deformation in high-intensity coal mining，Methods satellite image offset tracking and UAV LiDAR （Light Detection and Ranging） technology are used to obtain two typical subsidence areas and their parameters of the working face.The differences of these two remote sensing monitoring methods at different scales are demonstrated by combining the ground observation station data. Results Taking the two-scene SAR images of Shendong mining area as an example，the main value of surface subsidence in the mining area is −3.8~0 m by using the offset tracking technology.The UAV LiDAR technology can effectively identify the subsidence range and magnitude on the scale of the working face.The surface subsidence in the secondary and tertiary mining areas is higher than that in the primary mining areas，and the subsidence in the areas with underground coal pillars is small，and the subsidence is concentrated in −1.17~0 m.In the area with small subsidence，the offset tracking technology has higher accuracy，while in the area with large subsidence，the UAV LiDAR technology has higher accuracy，and the subsidence coefficients obtained by the two are 0.61 and 0.72，respectively.The subsidence coefficient obtained by the UAV LiDAR is closer to the subsidence coefficient measured on the ground. Conclusion This finding could provide reference for large-scale and efficient mining subsidence monitoring.

Key words：high-intensity coal mining；offset tracking；UAV LiDAR；mining subsidence

CLC: TD353