摘要
岩溶山区公路的工程地质条件极为脆弱,容易造成沿线边坡整体或局部滑坡,为保障岩溶山区公路的运营安全,对公路沿线易滑边坡进行定位监测分析是十分有必要的。选取云南九乡典型岩溶山区公路的一个易滑边坡作为实验监测对象,针对传统"点"式监测方法存在的不足,采用地面三维激光扫描(Terrestrial Laser Scanning,TLS)技术对该边坡实施了野外现场扫描并获得该易滑边坡现状的3D点云数据;基于I-Site Studio三维点云数据处理平台,开展了对该公路易滑边坡扫描获得的3D点云数据进行了配准、滤波去噪和空洞修复等预处理,以及精细化建模和三维场景构建等试验研究。整理得出了利用地面TLS技术进行岩溶山区公路易滑边坡3D点云数据采集、预处理和3D场景模拟分析等完整技术应用过程,并对TLS技术用于该实验区边坡监测的测量精度进行了评价。研究结果表明,相对于传统"点"式监测方法,地面TLS技术在岩溶山区公路沿线易滑边坡监测中能够获取更加丰富的空间三维数据,并构建出精细化的三维场景模型。
The geological condition of highway engineer in karst mountain area is very vulnerable.It is easy for landslides development along the whole or part of the slope.Therefore,it is very necessary to locate and monitor the potentially unstable slopes along the highway in order to ensure the operational safety in the mountainous area.This study selected an unstable roadside slope in a typical karst mountain area in Jiuxiang,Yunnan Province as the monitoring object.Aiming at the shortcomings of the traditional"point"monitoring method,this paper adopted the surface Terrestrial Laser Scanning(TLS)technology to carry out field scanning on the slope and got the 3D point cloud data of the slope surface.On the basis of the I-Site Studio 3D point cloud data processing platform,the authors preprocessed the 3D point cloud data obtained from the slope scanning,including the registration of point cloud data,filtering and denoising,and cavity repair.Besides,the experiment and research on fine modeling and 3D scene construction were carried out.This research established a comprehensive technology application process including the use of surface TLS technology to collect 3D point cloud data,3D data preprocessing and 3D scenario construction in the mountainous area.In addition,the accuracy of the TLS technology used in the slope monitoring of the experimental area was evaluated.The research results show that,compared with the traditional"point"monitoring method,the surface TLS technology can get more abundant spatial 3D data in slopes monitoring along the highway in the karst mountainous area,and build a refined 3D scene model.
作者
朱赞
甘淑
袁希平
高莎
ZHU Zan;GAN Shu;YUAN Xiping;GAO Sha(Faculty of Land Resources Engineering,Kunming Engineering University of Science and Technology,Kunming 650093,China;Surveying and Mapping Geo-Informatics Technolo Plateau Mountains of Yunnan Higher Education.Kun ming 650093,China)
出处
《防灾减灾工程学报》
CSCD
北大核心
2019年第6期972-979,共8页
Journal of Disaster Prevention and Mitigation Engineering
基金
国家自然科学基金项目(41561083)
云南省自然科学基金项目(2015FA016)资助
