Landslide Morphology Analysis Model Based on LiDAR and Topographic Dataset Comparison.

The natural trend of megacities is to expand from their centers to outlying areas in order to accommodate rapid population growth. Urban areas situated near steep, mountainous terrain or water sources may suffer from landslides, which are one of the most common natural disasters. This paper outlines a new approach in which airborne laser altimetry is used to automatically identify and model landslide occurrences within the acquired data. Dense and accurate light detection and ranging (LiDAR) topographic observations are modeled and compared to an existing digital elevation model (DEM) of the area acquired at an earlier stage. The standard direct superimposition comparison mechanism, which ignores the datasets' inherent interrelations, usually results in an incorrect modeling outcome. A new modeling concept is proposed that initially monitors the inherent global incongruities by georeferencing the two datasets. These incongruities are then utilized in a novel geospatial matching procedure that makes it possible to achieve a precise and correct local modeling mechanism. The hierarchical comparison concept presented accurate results in automatic identification of landslide phenomena, making it possible to precisely assess their morphology. [ABSTRACT FROM AUTHOR]