Doctor of Philosophy, The Ohio State University, 2015, Civil Engineering
Landslides are natural disasters that cause environmental and infrastructure damage worldwide. In order to reduce future risk posed by them, effective detection and monitoring methods are needed. Landslide susceptibility and hazard mapping is a method for identifying areas suspect to landslide activity. This task is typically performed in a manual, semi-automatic or automatic form, or a combination of these, and can be accomplished using different sensors and techniques. As landslide hazards continue to impact our environment and impede the lives of many, it is imperative to improve the tools and methods of effective and reliable detecting of such events.
Recent developments in remote sensing have significantly improved topographic mapping capabilities, resulting in higher spatial resolution and more accurate surface representations. Dense 3D point clouds can be directly obtained by airborne Light Detection and Ranging (LiDAR) or created photogrammetrically, allowing for better exploitation of surface morphology. The potential of extracting spatial features typical to landslides, especially small scale failures, provides a unique opportunity to advance landslide detection, modeling, and prediction process.
This dissertation topic selection was motivated by three primary reasons. First, 3D data structures, including data representation, surface morphology, feature extraction, spatial indexing, and classification, in particular, shape-based grouping, based on LiDAR data
offer a unique opportunity for many 3D modeling applications. Second, massive 3D data, such as point clouds or surfaces obtained by the state-of-the-art remote sensing technologies, have not been fully exploited for landslide detection and monitoring. Third, unprecedented advances in LiDAR technology and availability to the broader mapping community should be explored at the appropriate level to assess the current and future advantages and limitations of LiDAR-based detection and modeling of land (open full item for complete abstract)
Committee: Dorota Grejner-Brzezinska (Advisor); Charles Toth (Advisor); Tien Wu (Committee Member)
Subjects: Civil Engineering