Chapter 7
Comparative GIS-Based Assessment
of Landslide Susceptibility of Chepe
River Corridor, Gandaki River Basin,
Nepal
Kripa Shrestha, Udhab Raj Khadka, and Mandira Singh Shrestha
Abstract Loss of life and property due to human induced and natural landslides
are common in Himalayan region of Nepal. Intense precipitation over a short period
of time, unplanned road construction, degradation of forests, and change in land
use are expected to increase the number and intensity of landslides in the already
fragile mountainous tracts of the country. The landslide susceptibility assessment
using GIS and remote sensing tools identifying hazard/susceptibility, vulnerability
and risk are very useful for disaster risk reduction and management. In this chapter,
Statistical Index Model and Logistic Regression Model were compared for performance through Geographical Information System (GIS), to derive landslide Susceptibility map of the Chepe River corridor. Eleven factors (slope, aspect, geology,
distance to road, land use, rainfall, elevation, relief, drainage density, plan curvature, and profile curvature) were considered as possible key factors for the landslide
susceptibility assessment. To validate the models, Receiver Operating Characteristic
(ROC) was used. The result shows the Logistic Regression Model has 82% prediction accuracy, whereas Statistical Index Model has 63% prediction accuracy. Based
upon the accuracy assessment, the logistic regression model seems to have better
applicability in the Chepe River corridor in comparison to statistical index method
using same eleven triggering factors.
Keywords Landslide · Susceptibility assessment · GIS · Chepe River · Nepal
K. Shrestha (B) · M. Singh Shrestha
International Centre for Integrated Mountain Development (ICIMOD), Khumaltar, Lalitpur, Nepal
e-mail: k.kripashrestha@gmail.com; kripa.shrestha@icimod.org
M. Singh Shrestha
e-mail: mandira.shrestha@icimod.org
U. R. Khadka · M. Singh Shrestha
Central Department of Environmental Science (CDES), Tribhuvan University, Kirtipur, Nepal
© Springer Nature Switzerland AG 2021
R. Djalante et al. (eds.), Integrated Research on Disaster Risks, Disaster Risk Reduction,
https://doi.org/10.1007/978-3-030-55563-4_7
111
Comparative GIS-Based Assessment
of Landslide Susceptibility of Chepe
River Corridor, Gandaki River Basin,
Nepal
Kripa Shrestha, Udhab Raj Khadka, and Mandira Singh Shrestha
Abstract Loss of life and property due to human induced and natural landslides
are common in Himalayan region of Nepal. Intense precipitation over a short period
of time, unplanned road construction, degradation of forests, and change in land
use are expected to increase the number and intensity of landslides in the already
fragile mountainous tracts of the country. The landslide susceptibility assessment
using GIS and remote sensing tools identifying hazard/susceptibility, vulnerability
and risk are very useful for disaster risk reduction and management. In this chapter,
Statistical Index Model and Logistic Regression Model were compared for performance through Geographical Information System (GIS), to derive landslide Susceptibility map of the Chepe River corridor. Eleven factors (slope, aspect, geology,
distance to road, land use, rainfall, elevation, relief, drainage density, plan curvature, and profile curvature) were considered as possible key factors for the landslide
susceptibility assessment. To validate the models, Receiver Operating Characteristic
(ROC) was used. The result shows the Logistic Regression Model has 82% prediction accuracy, whereas Statistical Index Model has 63% prediction accuracy. Based
upon the accuracy assessment, the logistic regression model seems to have better
applicability in the Chepe River corridor in comparison to statistical index method
using same eleven triggering factors.
Keywords Landslide · Susceptibility assessment · GIS · Chepe River · Nepal
K. Shrestha (B) · M. Singh Shrestha
International Centre for Integrated Mountain Development (ICIMOD), Khumaltar, Lalitpur, Nepal
e-mail: k.kripashrestha@gmail.com; kripa.shrestha@icimod.org
M. Singh Shrestha
e-mail: mandira.shrestha@icimod.org
U. R. Khadka · M. Singh Shrestha
Central Department of Environmental Science (CDES), Tribhuvan University, Kirtipur, Nepal
© Springer Nature Switzerland AG 2021
R. Djalante et al. (eds.), Integrated Research on Disaster Risks, Disaster Risk Reduction,
https://doi.org/10.1007/978-3-030-55563-4_7
111