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Assessment of landslide susceptibility in the Himalayan state of Tripura, India, using a Multi-Model Approach

Debasis Das , Y. V. Krishnaiah * , Kausik Panja , Manika Mallick , Moumita Hati , Deepa Rai and Atoshi Chakma

1 Department of Geography and Disaster Management, Tripura University (A Central University), Suryamaninagar, Agartala, India

Corresponding author Email: yvkrishna09@gmail.com

Landslides are the down slope mass movement of soil, rocks, and debris due to a natural or human activities resulting in widespread hazard events in India. The most affected areas comprise 15 percent of its landmass which includes Tripura and eleven Himalayan states and parts of the Western and Eastern Ghats in India. In Tripura, landslides cause road blockage and destruction of settlements, bringing economic and life losses in every year. Thus, this research is focused on identifying landslide susceptible zones and the significant causative factors behind landslides. Assessment of Landslide Susceptibility (LS) identifies fifteen major causative factors under five broad groups; topographic, geotechnical, hydrological, environmental, and anthropogenic. With application of Analytical Hierarchical Process (AHP), Frequency Ratio (FR), and Random Forest (RF)-based models were performed to extract landslide susceptible zonation map for Tripura. This study reveals that the successive hill ranges formed by young sedimentary lithologic formations associated with deforestation, heavy rainfall during monsoon, and anthropogenic activities (road constructions and jhumming) are the responsible geo-conditions for triggering landslides. In this study, while the AHP and FR model show only 1.95% and 11.46% confined along the hilltop of Jampui, Sakhan, and Longtarai, the RF model designated Tripura’s 30% land area as high and very high landslide susceptible zones (LSZ), predominantly over hills, foothills, and low laying undulating land (tillas). For the accuracy assessment, the ROC curve is used, which shows that RF model appears to be the maximum accurate (0.810) one, followed by FR (0.806) and AHP (0.744).

Analytical Hierarchical Process; Frequency Ratio, Himalayan state, Landslide Susceptibility Modeling, Random Forest, Tripura

Copy the following to cite this article:

Das D, Krishnaiah Y. V, Panja K, Mallick M, Hati M, Rai D, Chakma A. Assessment of landslide susceptibility in the Himalayan state of Tripura, India, using a Multi-Model Approach

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Das D, Krishnaiah Y. V, Panja K, Mallick M, Hati M, Rai D, Chakma A. Assessment of landslide susceptibility in the Himalayan state of Tripura, India, using a Multi-Model Approach

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