GIS based Landslides Susceptibility Mapping using Probabilistic Certainty Factor for Hazard Zonation in Mandakini Valley
Seema Joshi1, J.K. Garg2, Amarjeet Kaur3

1Seema Joshi*, Esri India Technologies Ltd, University School of Environment Management, Guru Gobind Singh Indraprastha University, New Delhi, India.
2J.K. Garg, University School of Environment Management, Guru Gobind Singh Indraprastha University, New Delhi, India.
3Amarjeet Kaur, University School of Environment Management, Guru Gobind Singh Indraprastha University, New Delhi, India.
Manuscript received on February 12, 2020. | Revised Manuscript received on February 21, 2020. | Manuscript published on March 30, 2020. | PP: 398-404 | Volume-8 Issue-6, March 2020. | Retrieval Number: F7288038620/2020©BEIESP | DOI: 10.35940/ijrte.F7288.038620

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Abstract: Landslides are highly threatening a phenomenon which is very common in hilly region and mountainous regions. These landslides trigger major risks leading to heavy losses in terms of life and property. Many studies were conducted globally to determine Landslide vulnerability of different locations. In order to assess vulnerability, there were few studies around Landslides Susceptibility mapping also whose main objective is to identify high-risk vulnerable areas, there by applying measure to reduce the damage caused, if it were to happen in near future. In literature, there are many methods available for predictive susceptibility mapping of landslides. However, identification of any of the prevalent method for a specific area require utmost care and prudence because land sliding is a result of complex geo-environmental spatial factors. Mandakini valley is highly ruggedized terrain with intensive rains during monsoon season. As a result, Landslides are very common in the Mandakini River valley and its catchment area. These landslides cause severe damage to human settlements and infrastructure present in this area. In this study, we have used certainty factor method in order to generate landslide susceptibility map for the catchment area of Mandakini river. Certainty factor approach is a bi-variate probabilistic method which uses Geo-environmental parameters like elevation, slope, aspect, rainfall distance away from river, soil characteristics etc. to generate landslide susceptibility map. A Script was developed in ArcPy – a python package to design tools for generating susceptibility map. These tools can run both at desktop level and at server level and generate results in an integrated way. Esri ArcMap 10.7 is used in order to generate required data layers and thematic maps. Overall, this paper leverages GIS technology and its tools to performs Landslide Susceptibility Mapping using Probabilistic Certainty Factor and generate Hazard Zonation of Mandakini Valley using an automated script for generating Landslide Susceptibility Mapping and Hazard Risk Zonation. It was found that out of 696, total 136 villages are under high risk of landsides, total 329 villages are under moderate risks and around 231 villages are under low risk zonation impacting lives of approx. 216166 people. Also, it is worth mentioning that a GIS based script was developed to automate generation of Landslide Susceptibility Maps which can be used where the same geological and topographical feature prevails.
Keywords: GIS, Landslides, Susceptibility, mapping, Certainty factor (CF)
Scope of the Article: Remote Sensing, GIS and GPS.