Forest fire risk zonation mapping using remote sensing technology

Sunil Chandra; M. K. Arora

doi:10.1117/12.694228

12 December 2006 Forest fire risk zonation mapping using remote sensing technology

Sunil Chandra, M. K. Arora

Proceedings Volume 6412, Disaster Forewarning Diagnostic Methods and Management; 64120A (2006) https://doi.org/10.1117/12.694228
Event: SPIE Asia-Pacific Remote Sensing, 2006, Goa, India

Abstract

Forest fires cause major losses to forest cover and disturb the ecological balance in our region. Rise in temperature during summer season causing increased dryness, increased activity of human beings in the forest areas, and the type of forest cover in the Garhwal Himalayas are some of the reasons that lead to forest fires. Therefore, generation of forest fire risk maps becomes necessary so that preventive measures can be taken at appropriate time. These risk maps shall indicate the zonation of the areas which are in very high, high, medium and low risk zones with regard to forest fire in the region. In this paper, an attempt has been made to generate the forest fire risk maps based on remote sensing data and other geographical variables responsible for the occurrence of fire. These include altitude, temperature and soil variations. Key thematic data layers pertaining to these variables have been generated using various techniques. A rule-based approach has been used and implemented in GIS environment to estimate fuel load and fuel index leading to the derivation of fire risk zonation index and subsequently to fire risk zonation maps. The fire risk maps thus generated have been validated on the ground for forest types as well as for forest fire risk areas. These maps would help the state forest departments in prioritizing their strategy for combating forest fires particularly during the fire seasons.

Citation Download Citation

Sunil Chandra and M. K. Arora "Forest fire risk zonation mapping using remote sensing technology", Proc. SPIE 6412, Disaster Forewarning Diagnostic Methods and Management, 64120A (12 December 2006); https://doi.org/10.1117/12.694228

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