Geodesics-Based Topographical Feature Extraction From Airborne Lidar Data For Disaster Management

摘要

Hundreds of thousands of lives were lost in the natural disasters such as geological earthquakes, floods, landslides and mud-rock flow in every year. Nowadays, with the rapid development in airborne LiDAR techniques, extraction of the multi-scale topographical features from high-resolution topographic data acquired via airborne LiDAR would lead to fundamentally new understandings of earth essential to mapping flood, landslide and mud-rock flow hazards for decision makers. In this paper, we define topographic features in a multi-scale manner using a center-surround operator on Gaussian-weighted mean curvatures. These multi-scale topographical features would allow improved detecting, understanding and prediction of flood inundation, landslide and mud-rock flow likelihood. For example, experimental results identify that proposed method can be employed for detecting landslide.