Nonlinear regression technique to assess the landslide susceptibility of the Kalapahar hill, Guwahati, Assam State (India)

In the past few decades, the increasing frequency of landslides has become a concern for Guwahati city (capital of the State of Assam), especially around the low lying hills. In particular, the Kalapahar hill is one of the major landslide-prone areas of Guwahati, due to its peculiar geomorphological aspects.. The area is characterized by steep slopes underlying loose unconsolidated soil, which lead to frequent slope failure, especially during the monsoon season. Moreover, the intense urbanization of the hills has led to slope instability, making these areas more vulnerable. This paper provides a preliminary study on landslide susceptibility assessment, representing a first step towards landslide risk reduction. In particular, a semi-parametric nonlinear regression method, namely the GAM (Generalized Additive Model), was applied for landslide susceptibility mapping.