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Modeling forest fire risk in the northeast of Iran using remote sensing and GIS techniques

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  • Hamed Adab
  • Kasturi Kanniah
  • Karim Solaimani

Abstract

Fire in forested areas can be regarded as an environmental disaster which is triggered by either natural forces or anthropogenic activities. Fires are one of the major hazards in forested and grassland areas in the north of Iran. Control of fire is difficult, but it is feasible to map fire risk by geospatial technologies and thereby minimize the frequency of fire occurrences and damages caused by fire. The fire risk models provide a suitable concept to understand characterization of fire risk. Some models are map based, and they combine effectively different forest fire–causing variables with remote sensing data in a GIS environment for identifying and mapping forest fire risk. In this study, Structural Fire Index, Fire Risk Index, and a new index called Hybrid Fire Index were used to delineate fire risk in northeastern Iran that is subjected to frequent forest fire. Vegetation moisture, slope, aspect, elevation, distance from roads, and vicinity to settlements were used as the factors influencing accidental fire starts. These indices were set up by assigning subjective weight values to the classes of the layers based on their sensitivity ratio to fire. Hot spots data derived from MODIS satellite sensor were used to validate the indices. Assessment of the indices with receiver operating characteristic (ROC) curves shows that 76.7 % accuracy of the HFI outperformed the other two indices. According to the Hybrid Fire Index, 57.5 % of the study area is located under high-risk zone, 33 % in medium-risk zone, and the remaining 9.5 % area is located in low-risk zone. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • Hamed Adab & Kasturi Kanniah & Karim Solaimani, 2013. "Modeling forest fire risk in the northeast of Iran using remote sensing and GIS techniques," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(3), pages 1723-1743, February.
  • Handle: RePEc:spr:nathaz:v:65:y:2013:i:3:p:1723-1743
    DOI: 10.1007/s11069-012-0450-8
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    1. Abolfazl Jaafari & Omid Rahmati & Eric K. Zenner & Davood Mafi-Gholami, 2022. "Anthropogenic activities amplify wildfire occurrence in the Zagros eco-region of western Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(1), pages 457-473, October.
    2. José Manuel Zúñiga-Vásquez & Marín Pompa-García, 2019. "The occurrence of forest fires in Mexico presents an altitudinal tendency: a geospatial analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 96(1), pages 213-224, March.
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    4. Hamed Adab & Kasturi Devi Kanniah & Karim Solaimani, 2021. "Remote sensing-based operational modeling of fuel ignitability in Hyrcanian mixed forest, Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(1), pages 253-283, August.
    5. Osama Ashraf Mohammed & Sasan Vafaei & Mehdi Mirzaei Kurdalivand & Sabri Rasooli & Chaolong Yao & Tongxin Hu, 2022. "A Comparative Study of Forest Fire Mapping Using GIS-Based Data Mining Approaches in Western Iran," Sustainability, MDPI, vol. 14(20), pages 1-13, October.
    6. Ghafar Salavati & Ebrahim Saniei & Ebrahim Ghaderpour & Quazi K. Hassan, 2022. "Wildfire Risk Forecasting Using Weights of Evidence and Statistical Index Models," Sustainability, MDPI, vol. 14(7), pages 1-15, March.
    7. Dingli Liu & Zhisheng Xu & Chuangang Fan, 2019. "Predictive analysis of fire frequency based on daily temperatures," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 97(3), pages 1175-1189, July.
    8. Shruti Sachdeva & Tarunpreet Bhatia & A. K. Verma, 2018. "GIS-based evolutionary optimized Gradient Boosted Decision Trees for forest fire susceptibility mapping," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 92(3), pages 1399-1418, July.
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    14. Naderpour, Mohsen & Rizeei, Hossein Mojaddadi & Khakzad, Nima & Pradhan, Biswajeet, 2019. "Forest fire induced Natech risk assessment: A survey of geospatial technologies," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    15. Saeedeh Eskandari & Mahdis Amiri & Nitheshnirmal Sãdhasivam & Hamid Reza Pourghasemi, 2020. "Comparison of new individual and hybrid machine learning algorithms for modeling and mapping fire hazard: a supplementary analysis of fire hazard in different counties of Golestan Province in Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 104(1), pages 305-327, October.
    16. Reshma T. Vilasan & Vijay S. Kapse, 2022. "Evaluation of the prediction capability of AHP and F-AHP methods in flood susceptibility mapping of Ernakulam district (India)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(2), pages 1767-1793, June.
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    19. Roghayeh Jahdi & Michele Salis & Fermin J. Alcasena & Mahdi Arabi & Bachisio Arca & Pierpaolo Duce, 2020. "Evaluating landscape-scale wildfire exposure in northwestern Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 101(3), pages 911-932, April.

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