Current Science

Arnab Laha ¹, Nagarajan Balasubramanian ², Rajiv Sinha ³

Affiliations
1 Department of Earth Sciences, Indian Institute of Technology Kanpur, Kanpur 208 016, India; Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur 208 016, India, IN
2 Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur 208 016, India, IN
3 Department of Earth Sciences, Indian Institute of Technology Kanpur, Kanpur 208 016, India, IN

Abstract

Forest fire is one of the primary and recurring problems in Sikkim, India impacting the ecological heritage of the region. The article presents a fire risk model based on the identification of the major factors that contribute to forest fire, namely, vegetation type, vegetation density, land surface temperature, elevation, slope, aspect, and distance from settlements, rivers and roads, and then integrating them using a multi-criteria decision-making technique in a GIS framework. We document that more than 50% of the area of all the districts except North Sikkim falls into high to moderate risk zones. The model shows that 61% of fire information for resource management system data for the last 16 years coincide with the mapped high-risk zone of the state. Areas with low slope and with moderate vegetation density fall into very high risk, whereas areas with high slope and with high vegetation density correspond to moderate risk zones. Further, aspect and density of human intervention differentiate the very high and high-risk zones of the region. This model has provided a robust geographical representation of fire ignition probability and identification of high-risk areas at different regions for the entire state of Sikkim

Keywords

Analytic hierarchy process, forest fire risk, multi-criteria decision-making technique, remote sensing, risk map.

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