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Journal of the Indian Society of Remote Sensing

, Volume 47, Issue 12, pp 2047–2060 | Cite as

A Comparative Analysis of Forest Fire Risk Zone Mapping Methods with Expert Knowledge

  • H. Yathish
  • K. V. Athira
  • K. PreethiEmail author
  • U. Pruthviraj
  • Amba Shetty
Research Article

Abstract

Despite repeated occurrences of forest fire, very less scientific studies have been reported in the Indian context especially in Kudremukh region to mitigate and suppress the fire. The objective of this article was to pool the expert knowledge on forest fire triggering factors from officials working in wildlife division in the Western Ghats of India through a questionnaire and to validate the risk zones obtained from three popular fire risk zone mapping methods namely logistic regression, multi-criteria decision analysis, and weighted overlay. Based on the earlier studies and expert knowledge, fire ignition parameters considered are elevation, slope, and aspect, proximity to roads, water bodies and area of human activities, normalized difference vegetation index (NDVI), land surface temperature (LST), and vegetation type. The regression model was based on previous fire occurrences and the other two based on expert’s opinion. The three models were validated and compared using past fire occurrence events. The logistic regression model gave 88.89% of accuracy and that of multi-criteria decision analysis with 74.6% accuracy, and that of weighted overlay method with an accuracy of 68.24% for the specific study area. The logistic regression model is useful in the presence of historical data, whereas expert knowledge is helpful for mapping risk zones using multi-criteria decision analysis and weighted overlay analysis when historical data are scarce or not available for mapping risk zones. The obtained risk maps can be used for deciding watchtower locations, installation of sensors, cameras, etc. In every forest division, it is recommended to prepare a standard questionnaire form and document their experiences on forest fire in the region under their supervision before they are getting transferred to another location.

Keywords

Fire ignition parameters Forest fire risk zones Logistic regression model Multi-criteria decision analysis Weighted overlay analysis 

Notes

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Copyright information

© Indian Society of Remote Sensing 2019

Authors and Affiliations

  1. 1.National Institute of Technology KarnatakaSurathkalIndia

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