Application of remote sensing and GIS in landslide detection
Journal
27th Asian Conference on Remote Sensing
Pages
1165-1170
Date Issued
2006
Author(s)
Yang, Y.-A.
Abstract
Because of the precipitous terrain and short rapid rivers in Taiwan, the landslides usually happen after heavy rains and the resulting floods. Landslides are natural hazards that often cause series property damages and even life losses. This makes the landslide monitoring and mitigation techniques an important study issue for the related professional disciplines in Taiwan. Wtih the development of remote sensing technology, both the spatial and spectral resolution of satellite images become more mature for objection identification and detection. In this paper, the landslide areas are detected using the pre- and post-images by the decision trees classifier. Firstly, the thresholding method according to the variety of Normalized Difference Vegetation Index (NDVI) is used to remove the vegetation areas. Then, a supervised classifier is used to distinguish the river zones from the bare lands and identify different types of landslides. Finally, based on the spatial analysis of digital terrain model (DTM) using GIS technology, more information about the landslide areas can be integrated according to the geometric characteristics of the terrain such, as the slope, aspect and watershed analysis. The detected landslide information could be utilized as a reference for the mitigation of the future landslide hazards.
Subjects
Decision trees; Digital terrain models; Landslide detection; Vegetation index
SDGs
Other Subjects
Bare lands; Digital terrain model; Geometric characteristics; GIS technology; Heavy rains; Landslide detection; Landslide hazard; Landslide monitoring; Mitigation techniques; Natural hazard; Normalized difference vegetation index; Property damage; Remote sensing and GIS; Remote sensing technology; Satellite images; Spatial analysis; Supervised classifiers; Thresholding methods; Vegetation index; Watershed analysis; Decision trees; Forestry; Hazards; Landforms; Remote sensing; Landslides
Publisher
journal article
Type
journal article