Terrain classification based on adaptive weights with airborne LiDAR data for mining area  

作　　者：LI Hui-ying1, WANG Zhi2, SUN Ya-feng1, LI Wen-hui1 1. College of Computer Science and Technology, Jilin University, Changchun 130012, China 2. College of Resources and Civil Engineering, Northeastern University, Shenyang 110004, China 

出　　处：《中国有色金属学会会刊：英文版》2011年第S3期648-653,共6页Transactions of Nonferrous Metals Society of China

基　　金：Project(2011CB707102)supported by the National Basic Research Program of China;Projects(41001302,40901220)supported by the National Natural Science Foundation of China;Project(200903190)supported by the Fundamental Research Funds for the Central Universities,China;Project(20090450305)supported by the China Postdoctoral Science Foundation;Project(122025)supported by the Fok Ying Tong Education Foundation,China

摘　　要：The fast high-efficiency inspection for mining subsidence of mine area is a reliable way for forecasting accident and evaluating losing expense. In order to monitor mining subsidence of exploitation mine efficiently, LiDAR data were used and a novel strip division method was brought forward based on separating-treatment theory, which divided the mass of discrete three-dimensional point cloud data into a series of parallel strips and reduced the dimension in each strip. Polynomial fitting algorithm based on the adaptive weights, which located in the range of the strip, was used for classification complex terrain data of mine-area. The results show that LiDAR datamation can be greatly reduced. In the mean time, the time spending for calculation is shortened, and computational complexity is simplified. Therefore, high-efficiency terrain classification of LiDAR point cloud method can be great beneficial to monitoring environment of mine area.The fast high-efficiency inspection for mining subsidence of mine area is a reliable way for forecasting accident and evaluating losing expense. In order to monitor mining subsidence of exploitation mine efficiently, LiDAR data were used and a novel strip division method was brought forward based on separating-treatment theory, which divided the mass of discrete three-dimensional point cloud data into a series of parallel strips and reduced the dimension in each strip. Polynomial fitting algorithm based on the adaptive weights, which located in the range of the strip, was used for classification complex terrain data of mine-area. The results show that LiDAR datamation can be greatly reduced. In the mean time, the time spending for calculation is shortened, and computational complexity is simplified. Therefore, high-efficiency terrain classification of LiDAR point cloud method can be great beneficial to monitoring environment of mine area.

关 键 词：mining SUBSIDENCE AIRBORNE LIDAR STRIP DIVISION adaptive WEIGHTS 

分 类 号：TN958.98[电子电信—信号与信息处理] P208[电子电信—信息与通信工程]