INFLUENCE OF RANGING UNCERTAINTY OF TERRESTRIAL LASER SCANNING ON CHANGE DETECTION IN TOPOGRAPHIC 3D POINT CLOUDS

8 citations as recorded by crossref.

1. PointNet-based modeling of systematic distance deviations for improved TLS accuracy J. Hartmann et al. https://doi.org/10.1515/jag-2023-0097
2. Investigations of the scan characteristics with special focus on multi-target capability for the 2D laser scanner RIEGL miniVUX-2UAV A. Dreier et al. https://doi.org/10.1515/jag-2022-0029
3. A Data‐Driven Solution for Large‐Scale Open‐Pit Mines Excavation Monitoring Based on 3D Point Cloud T. He et al. https://doi.org/10.1049/ipr2.70130
4. Multi-directional change detection between point clouds J. Williams et al. https://doi.org/10.1016/j.isprsjprs.2020.12.002
5. Intensity-based stochastic model of terrestrial laser scanners: Methodological workflow, empirical derivation and practical benefit F. Schill et al. https://doi.org/10.1016/j.ophoto.2024.100079
6. Near real-time change detection tool for photogrammetric flood preparedness M. Kögel & D. Carstensen https://doi.org/10.1007/s10661-024-13597-9
7. Three Dimensional Change Detection Using Point Clouds: A Review A. Kharroubi et al. https://doi.org/10.3390/geomatics2040025
8. 基于合成方差协方差矩阵的激光点云随机特性分析 周. Zhou Tengfei https://doi.org/10.3788/LOP251751