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Geospatial Approach for Forest Fire Risk Modeling: a Case Study of Taradevi Range of Shimla Forest Division in Himachal Pradesh, India


     

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Forest fires are calamity that causes damage to the forest economy which is considerably greater than all damages caused by the harmful insects and diseases. Its cause's substantial damage whether caused by natural or anthropogenic factors. Therefore the problem of controlling forest fire is making its important place in issue of economy development. The study area is prone to fire because of the presence of dominant species of pines which are highly susceptible to fires due to the presence of resins. The greatest danger from fire occurs during the month of April to June in higher temperatures periods. Satellite images were interpreted and classified to generate fuel type layer and land use layers. Topographic layers (slope, aspect and altitude) were derived from SRTM data. The thematic and topographic information was analyzed by using ARC/INFO GIS software. Forest fire risk zones were delineated by assigning subjective weights to the classes of all the layers (vegetation type, slope, aspect, elevation and distance from roads, and settlements) according to their sensitivity to fire or their fire-inducing capability. Five categories of forest fire risk ranging from very high to very low were derived on knowledge based information.

Keywords

Forest Fire Risk Model, Geospatial Approach
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Shruti Kanga

Laxmi Kant Sharma

M. S. Nathawat

S. K. Sharma


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  • Geospatial Approach for Forest Fire Risk Modeling: a Case Study of Taradevi Range of Shimla Forest Division in Himachal Pradesh, India

Abstract Views: 368  |  PDF Views: 4

Authors

Abstract


Forest fires are calamity that causes damage to the forest economy which is considerably greater than all damages caused by the harmful insects and diseases. Its cause's substantial damage whether caused by natural or anthropogenic factors. Therefore the problem of controlling forest fire is making its important place in issue of economy development. The study area is prone to fire because of the presence of dominant species of pines which are highly susceptible to fires due to the presence of resins. The greatest danger from fire occurs during the month of April to June in higher temperatures periods. Satellite images were interpreted and classified to generate fuel type layer and land use layers. Topographic layers (slope, aspect and altitude) were derived from SRTM data. The thematic and topographic information was analyzed by using ARC/INFO GIS software. Forest fire risk zones were delineated by assigning subjective weights to the classes of all the layers (vegetation type, slope, aspect, elevation and distance from roads, and settlements) according to their sensitivity to fire or their fire-inducing capability. Five categories of forest fire risk ranging from very high to very low were derived on knowledge based information.

Keywords


Forest Fire Risk Model, Geospatial Approach