A Case Study of Generating Landslide Susceptibility Map using Digital Terrain Model Parameters from Airborne LiDAR-Data, Vegetation Cover and Land Use in Canada Hill, Miri, Sarawak
Landslide Susceptibility Mapping using GIS software and remote sensing data have been conducted in several location involving geological and geomorphological sensitive at Canada Hill, Miri. The previous researchers have conducted quantitative analyses using different statistical methods with differe...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
Universiti Malaysia Sarawak (UNIMAS)
2019
|
| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/26159/3/Edward%20Anak%20Muol%20fr.pdf http://ir.unimas.my/id/eprint/26159/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Landslide Susceptibility Mapping using GIS software and remote sensing data have been conducted in several location involving geological and geomorphological sensitive at Canada Hill, Miri. The previous researchers have conducted quantitative analyses using different statistical methods with different parameters in the same study area. The mapping of landslides using high-resolution Airborne LiDAR data is a valuable effort. All of this play important role, in the analysis and development of landslide susceptibility map. High-resolution Airborne LiDAR data has the ability to penetrate thick forest cover and produce Digital Terrain Model. Using Digital Terrain Model, the landslide parameter can be generated and extracted. The main objective of this study was to produce landslide susceptibility map using the Probability Frequency Ratio Model method. This study involved the delineating of causative factors from Digital Terrain Model generated by Airborne LiDAR data as well as the data collected from the field. In addition to topographical factors, the geological factors and the hydrological factors, and the anthropogenic factors were included into the mapping process. This study was different from the previous studies in the same area in terms of various analytical approaches and samples used. The results of the landslide susceptibility map were verified via randomly selected landslides samples using two different methods. The landslide susceptibility map produced is more refined and is able to predict more effectively compared to the existing map. The landslide susceptibility map produced in this study could be used for land use planning and management by decision makers and land use planners |
|---|