ASSESSING TEMPORAL BEHAVIOR IN LIDAR POINT CLOUDS OF URBAN ENVIRONMENTS

9 citations as recorded by crossref.

1. Research note: cost-efficient estimates of Pinus radiata wood volumes using multitemporal LiDAR data S. Peters et al. 10.1080/00049158.2021.1997459
2. Integrity and Collaboration in Dynamic Sensor Networks S. Schön et al. 10.3390/s18072400
3. Gap completion in point cloud scene occluded by vehicles using SGC-Net Y. Feng et al. 10.1016/j.isprsjprs.2024.07.009
4. Three Dimensional Change Detection Using Point Clouds: A Review A. Kharroubi et al. 10.3390/geomatics2040025
5. Classification and Change Detection in Mobile Mapping LiDAR Point Clouds M. Voelsen et al. 10.1007/s41064-021-00148-x
6. Spatio-Temporal Research Data Infrastructure in the Context of Autonomous Driving C. Fischer et al. 10.3390/ijgi9110626
7. The strip adjustment of mobile LiDAR point clouds using iterative closest point (ICP) algorithm R. Kuçak et al. 10.1007/s12517-022-10303-2
8. Semantics-aided 3D change detection on construction sites using UAV-based photogrammetric point clouds R. Huang et al. 10.1016/j.autcon.2021.104057
9. Change detection of urban objects using 3D point clouds: A review U. Stilla & Y. Xu 10.1016/j.isprsjprs.2023.01.010