何柯璐,汤伏全,韦书平,李小涛

• 1:西安科技大学测绘科学与技术学院
• 2:自然资源部煤炭资源勘查与综合利用重点实验室
• 3:陕西省一八五煤田地质有限公司

摘要(Abstract)：

针对榆神矿区地形起伏而植被覆盖度较低的条件,采用无人机激光雷达(LiDAR)对采煤沉陷盆地进行地面扫描和建模,按现有的点云滤波和插值算法所构建的沉陷模型精度不足的问题,该文提出基于格网高程排序的类地面点云提取算法,通过改变格网大小和点云提取比例来优化点云滤波效果,改进了地表沉陷模型的精度。在此基础上,选用概率积分法和GaussAmp函数对沉陷模型进行最小二乘拟合,结果表明GaussAmp函数对于试验区地表动态沉陷模型的拟合精度更高。

关键词(KeyWords)： 机载LiDAR;点云滤波;DEM叠加;采煤沉陷;数学建模

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目（51674195）;; 陕西省自然科学基金项目（2016JM5048）

作者(Author): 何柯璐,汤伏全,韦书平,李小涛

DOI: 10.16251/j.cnki.1009-2307.2021.02.019

参考文献(References)：

• [1] 王双明,段中会,马丽,等.西部煤炭绿色开发地质保障技术研究现状与发展趋势[J].煤炭科学技术,2019,47(2):1-6.(WANG Shuangming,DUAN Zhonghui,MA Li,et al.Research status and future trends of geological assurance technology for coal green development in western China[J].Coal Science and Technology,2019,47(2):1-6.)
• [2] 芦家欣,汤伏全,赵军仪,等.黄土矿区开采沉陷与地表损害研究述评[J].西安科技大学学报,2019,39(5):859-866.(LU Jiaxin,TANG Fuquan,ZHAO Junyi,et al.Review of study on mining subsidence and ground surface damage in loess mining area[J].Journal of Xi’an University of Science and Technology,2019,39(5):859-866.)
• [3] 汪云甲.矿区生态扰动监测研究进展与展望[J].测绘学报,2017,46(10):1705-1716.(WANG Yunjia.Research progress and prospect on ecological disturbance monitoring in mining area[J].Acta Geodaetica et Cartographica Sinica,2017,46(10):1705-1716.)
• [4] YAN Weitao,CHEN Junjie,YAN Yueguan.A new model for predicting surface mining subsidence:the improved lognormal function model[J].Geosciences Journal,2019,23:165-174.
• [5] 刘玉成,戴华阳.近水平煤层开采沉陷预计的双曲线剖面函数法[J].中国矿业大学学报,2019,48(3):676-681.(LIU Yucheng,DAI Huayang.Hyperbolic function model for predicting the main section surface deformation curve due to approximate horizontal coal seam underground longwall mining[J].Journal of China University of Mining and Technology,2019,48(3):676-681.)
• [6] 王正忠,孔祥柯,毕玉成,等.依兰矿区古近系软岩地层地表沉陷与覆岩破坏规律研究[J].煤炭科学技术,2018,46(S2):206-209.(WANG Zhengzhong,KONG Xiangke,BI Yucheng,et al.Study on surface subsidence and overburden failure law of Paleogene soft rock in Yilan mining area[J].Coal Science and Technology,2018,46(S2):206-209.)
• [7] 郭山川,侯湖平,张绍良,等.D-InSAR的黄土高原矿区地表形变监测[J].测绘科学,2017,42(6):207-212.(GUO Shanchuan,HOU Huping,ZHANG Shaoliang,et al.Surface deformation monitoring of the mining area in Loess Plateau based on D-InSAR[J].Science of Surveying and Mapping,2017,42(6):207-212.)
• [8] 卢遥,余涛,卢小平.基于高差分析的点云数据提取矿区地表沉陷信息方法[J].测绘通报,2013(3):22-25.(LU Yao,YU Tao,LU Xiaoping.Subsidence information extraction of mine surface with point cloud data based on elevation difference analysis[J].Bulletin of Surveying and Mapping,2013(3):22-25.)
• [9] 薛懋,王霄.论三维激光扫描技术在地质测绘中的应用[J].世界有色金属,2019(10):266,269.(XUE Mao,WANG Xiao.Application of 3D laser scanning technology in geological surveying and mapping[J].World Nonferrous Metals,2019(10):266,269.)
• [10] 李卉,李德仁,黄先锋,等.一种渐进加密三角网LiDAR点云滤波的改进算法[J].测绘科学,2009,34(3):39-40,216.(LI Hui,LI Deren,HUANG Xianfeng,et al.Advanced adaptive TIN filter for LiDAR point clouds data[J].Science of Surveying and Mapping,2009,34(3):39-40,216.)
• [11] CUI Tingting,JI Shunping,SHAN Jie,et al.Line-based registration of panoramic images and LiDAR point clouds for mobile mapping[J].Sensor,2017,17(1):70.
• [12] SITHOLE G,VOSSELMAN G.Experimental comparison of filter algorithms for bare-Earth extraction from airborne laser scanning point clouds[J].ISPRS Journal of Photogrammetry & Remote Sensing,2004,59(1/2):85-101.
• [13] 贾艳昌,谢谟文,刘汉东.基于栅格柱体单元的开采沉陷算法[J].煤炭学报,2015,40(12):2794-2800.(JIA Yanchang,XIE Mowen,LIU Handong.Subsidence prediction of goaf based on grid column units[J].Journal of Coal Industry,2015,40(12):2794-2800.)
• [14] 高超,徐乃忠,刘贵.特厚煤层综放开采地表沉陷预计模型算法改进[J].煤炭学报,2018,43(4):939-944.(GAO Chao,XU Naizhong,LIU Gui.Improvement on prediction model algorithm for surface subsidence of extra thick seam using fully-mechanized top coal caving method[J].Journal of Coal Industry,2018,43(4):939-944.)
• [15] HUI Z Y,HU Y J,YAO Z Y,et al.An improved morphological algorithm for filtering airborne LiDAR point cloud based on multi-level Kriging interpolation[J].Remote Sensing,2016:8(1):35.
• [16] HUANG Xiaoping,CAO Rujun,CAO Yanyan.A density-based clustering method for the segmentation of individual buildings from filtered airborne LiDAR point clouds[J].Journal of the Indian Society of Remote Sensing,2019,47(6):907-921.
• [17] MAN Qixia,DONG Pinliang.Extraction of urban objects in cloud shadows on the basis of fusion of airborne LiDAR and hyperspectral data[J].Remote Sensing,2019,11(6):713.
• [18] 邓喀中,谭志祥,姜岩,等.变形监测及沉陷工程学[M].徐州:中国矿业大学出版社,2014:183-184.(DENG Kazhong,TAN Zhixiang,JIANG Yan,et al.Deformation monitoring and subsidence engineering[M].Xuzhou:China University of Mining and Technology Press,2014:183-184.)
• [19] TANG Fuquan,LU Jiaxin,LI Pengfei.A prediction model for mining subsidence in loess-covered mountainous areas of western China[J].Current Science,2019,116(12):2036.
• [20] 周大伟,吴侃,刁鑫鹏,等.测量误差对概率积分法参数精度影响[J].辽宁工程技术大学学报(自然科学版),2013,32(3):316-320.(ZHOU Dawei,WU Kan,DIAO Xinpeng,et al.Analysis of influence of measurement error on probability-integral parameters[J].Journal of Liaoning University of Engineering and Technology(Natural Science Edition),2013,32(3):316-320.)
• [21] FAN Hongdong,GU Wei,QIN Yong,et al.A model for extracting largedeformation mining subsidence using D-InSAR technique and probability integral method[J].Transactions of Nonferrous Metals Society of China,2014,24(4):1242-1247.
• [22] 薄怀志,宋炳忠,李川建,等.概率积分法沉陷预计与参数反演优化算法及实现[J].山东国土资源,2018,34(4):73-77,83.(BO Huaizhi,SONG Bingzhong,LI Chuanjian,et al.Method and implementation of subsidence prediction based on the probability integral method and inversion of optimal parameters[J].Shandong Land and Resources,2018,34(4):73-77,83.)
• [23] 姜岳,R MISA,李鹏宇,等.矿山开采沉陷理论发展历程综述[J].金属矿山,2019(10):1-7.(JIANG Yue,MISA R,LI Pengyu,et al.Summary and development of mining subsidence theory[J].Metal Mines,2019(10):1-7.)