Unveiling Short-Term Dynamic of Urban Areas with Airborne LiDAR Data for Change Detection

摘要: Remote Sensing and Computer Vision, Universitaet Karlsruhe, Englerstr. 7, 76131, Germany Currently, as modern airborne small-footprint laser scanners (airborne LiDAR) are increasingly employed for various urban applications, e.g. building reconstruction, 3d city modeling planning. Change detection areas using LiDAR technique, which mainly served damaged assessment after unforeseen disasters, ecology monitoring, etc, has been also entered into the scope of research. In contrast to common change tasks where observed events span a long time range, short-term dynamic refer those frequently happen within small temporal scale not easy reliable be detected by long-period observations. The dynamical have become represent one most important elements changes plays key role in many applications. this paper, we will propose approaches detecting view detection. To test verify our approaches, multi-aspect data short revisiting interval one-path data, both acquired over densely built-up areas, applied respectively. For deal with anomaly happing between every two flights. Then, it distinguished view-induced variants real ones due acquisition setting scanning. A spatial-context based height differencing method is introduced describe find changed regions on co-registered gridded surface. moving objects appearing traffic major issue. scanning mechanism leads motion artifacts instantaneously vehicles. Our idea make use effect classify status obtained results experiments simulated showed us feasibility promising proposed approaches. Finally, paper concluded present troubles future works.