Small Landslide Susceptibility and Hazard Assessment Based on Airborne Lidar Data
Landslides are natural disasters that cause environmental and infrastructure damage worldwide. To prevent future risk posed by such events, effective methods to detect and map their hazards are needed. Traditional landslide susceptibility mapping techniques, based on field inspection,
aerial photograph interpretation, and contour map analysis are often subjective, tedious, difficult to implement, and may not have the spatial resolution and temporal frequency necessary to map small slides, which is the focus of this investigation. We present a methodology that is based on
a Support Vector Machine (SVM) that utilizes a lidar-derived Digital Elevation Model (DEM) to quantify and map the topographic signatures of landslides. The algorithm employs several geomorphological features to calibrate the model and delineate between landslide and stable terrain. To evaluate
the performance of the proposed algorithm, a road corridor in Zanesville, Ohio, was used for testing. The resulting landslide susceptibility map was validated to correctly identify 67 of the 80 mapped landslides in the independently compiled landslide inventory map of the area. These results
suggest that the proposed landslide surface feature extraction method and airborne lidar data can be used as efficient tools for small landslide susceptibility and hazard mapping.
Document Type: Research Article
Publication date: 01 March 2015
- The official journal of the American Society for Photogrammetry and Remote Sensing - the Imaging and Geospatial Information Society (ASPRS). This highly respected publication covers all facets of photogrammetry and remote sensing methods and technologies.
Founded in 1934, the American Society for Photogrammetry and Remote Sensing (ASPRS) is a scientific association serving over 7,000 professional members around the world. Our mission is to advance knowledge and improve understanding of mapping sciences to promote the responsible applications of photogrammetry, remote sensing, geographic information systems (GIS), and supporting technologies. - Editorial Board
- Information for Authors
- Submit a Paper
- Subscribe to this Title
- Membership Information
- Information for Advertisers
- Terms & Conditions
- Ingenta Connect is not responsible for the content or availability of external websites
Receive new issue alert- Access Key
- Free content
- Partial Free content
- New content
- Open access content
- Partial Open access content
- Subscribed content
- Partial Subscribed content
- Free trial content