4.3 Article

Landslide Susceptibility Mapping Using Landslide Numerical Risk Factor Model and Landslide Inventory Prepared Through OBIA in Chenab Valley, Jammu and Kashmir (India)

Journal

JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING
Volume 48, Issue 3, Pages 431-449

Publisher

SPRINGER
DOI: 10.1007/s12524-019-01092-5

Keywords

LNRF; Remote sensing; GIS; Landslide

Ask authors/readers for more resources

A landslide is the movement of rock, debris or earth down along the slope under the gravity. It may cause to loss of people's life and their private and public properties. Landslide is a common hazard in steep slope areas, especially during the rainy season. A study of landslide helps urban planners, engineers and local communities to reduce losses caused by existing and future landslides by means of prevention, mitigation and avoidance. Therefore, the prime aim of this paper is to produce acceptable landslide hazard map for Chenab valley, Jammu and Kashmir. Semiautomatic extraction of the landslide is a suitable method that has been used in this paper to extract the location and extent of the landslides. IRS LISS-IV and CartoDEM have been used for object-based image analysis to extract and prepare a landslide inventory map. About 84 landslide potential sites have been identified by the semiautomatic extraction approach. Landslide numerical risk factor model is derived by using thirteen thematic layers with landslide inventory to prepare the landslide hazard map. The result showed that 21% area of the Chenab valley is falling under the very high hazard zone category of the landslide. The final result of the investigation will definitely be useful in the decision-making procedure at the time of emergency and will be used to prepare a preparedness plan for high-risk areas of Chenab valley. The ROC curve method is used for accuracy assessment that signifies the acceptable result for landslide susceptibility zonation of Chenab valley with 0.956 AUC value.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.3
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available