Detection and Volume Estimation of Mining Subsidence Based on Multi-temporal LiDAR Data
A new technique for quickly assessing extensive areas ofmining subsidence that uses digital elevation models (DEMs)extracted from LiDAR (Airborne light detection and ranging,LiDAR) is presented in this paper. The proposed techniqueobserves the elevation changes by using multi-temporal DEMs.One-meter-resolution DEMs from LiDAR data are applied todetection the mining subsidence in Hebi coal mine area, China. Weassess the DEMs produced by the proposed method and theirmining subsidence application. Differential DEMs were producedto identify vertical ground displacements over the period. Elevationchanges in excess of 15 cm can be detected. We find three mainresults. 1) The elevation difference error increases with the highcoverage of vegetation. 2) The proposed technique well delineatedthe large-scale mining subsidence. The total rate of successful areadetection was over 90%. 3) The mining subsidence volume could beroughly estimated in units of 10 3 m 3. The developed technique wellsupports damage assessments of mining subsidence because thelocation, depth, and volume can be quantitatively determined byLiDAR.
Haiyang Yu Xiaoping Lu Gang Cheng Xiaosan Ge
Key Laboratory of Mine Spatial Information TechnologiesHenan Polytechnic University,Henan Bureau of Surveying & Mapping,State Bureau of Surveying & Mapping Henan Polytechnic University Jiaozuo, China
国际会议
The 19th International Conference on Geoinformatics(第19届国际地理信息科学与技术大会 19 Geoinformatics)
上海
英文
1-6
2011-06-01（万方平台首次上网日期，不代表论文的发表时间）