Landslide susceptibility mapping of a hilly region through a semi-quantitative technique

ABSTRACT

Characterization of landslide susceptibility carries great importance in hilly regions as it is one of the frequently occurring natural hazards which comes with huge destruction of life as well as property. Identification of such landslide susceptible zones is usually decided based on the necessity and available resources. It is considered a valuable input for planning developmental activities by policymakers. The current study focuses on Pabbar Catchment, located in the state of Himachal Pradesh in India and prepares a Landslide Susceptibility Map (LSM) at a catchment scale using Analytical Hierarchy Approach (AHP). Eleven geo-morphological attributes of the catchment called causative factors were used in thematic form while creating the LSM. Being a semi-quantitative method, AHP performed satisfactorily to produce a realistic distribution of landslide susceptibility with a prediction accuracy of 0.768 under the Area Under Curve (AUC) technique. Approximately 72% of the geographical area from the catchment falls under the ‘high’ landslide susceptible zone. Unavailability of LSM at this scale is addressed through this study that may be useful to regional planners for future land use planning.

KEYWORDS:

• Landslides
• AHP
• LSM
• causative factors
• AUC
• semi-quantitative

Acknowledgement

The authors are thankful to the Department of Science and Technology, Government of India for all their support for conducting this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article.

Additional information

Funding

This work was supported by Department of Science and Technology, Ministry of Science and Technology, India (NRDMS/LS/34418/2020).

Notes on contributors

Janaki Ballav Swain

Dr. Janaki Ballav Swain is an Assistant Professor in the School of Civil Engineering, at Lovely Professional University, Punjab, India. His research interests include Natural Hazards Investigation, Remote Sensing and GIS and Geohydrological analysis.

Ningthoujam James Singh

Mr. Ningthoujam James Singh is a research scholar in the School of Civil Engineering, at Lovely Professional University, Punjab, India. His study focuses on Landslide Hazard Examination.

Lovi Raj Gupta

Dr. Lovi Raj Gupta is a Professor in the Faculty of Science and Technology Division at Lovely Professional University, Punjab, India. Machine Learning and Deep Learning themes are his areas of Interest.