Fire-danger modeling and mapping in natural ecosystems of northeastern Iran: application of physiographic, vegetative, climatic and human-made indicators

Saeedeh Eskandari (), Nadia Kamali (), Ahmad Sadeghipour (), Reza Siahmansour () and John P. Tiefenbacher ()
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Saeedeh Eskandari: Research Institute of Forests and Rangelands
Nadia Kamali: Research Institute of Forests and Rangelands
Ahmad Sadeghipour: Semnan University
Reza Siahmansour: Natural Resources Division, Lorestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO)
John P. Tiefenbacher: Texas State University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2024, vol. 120, issue 8, No 42, 8025-8056

Abstract: Abstract Fire frequencies have increased in the natural ecosystems of northeastern Iran because of natural and human factors in the recent years. This study models and maps the danger of fire in natural ecosystems in Northern Khorasan Province in northeastern Iran. First, the hierarchical structure of the main fire-influencing factors (physiographic, climatic, vegetative, and human-made factors) and their sub-factors was determined. The data describing these effective factors were acquired from different sources (satellite images, field survey, etc.) and were converted into the maps in raster format (30 m by 30 m pixel size) in the GIS. A map of past fires in the province was developed from data of the Northern Khorasan Natural Resources Administration and from the fire product of the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor. The weights of each of the factors and sub-factors were determined using FAHP (Fuzzy Analytic Hierarchy Process). A fire-danger map was obtained by overlapping all effective-factor maps in the GIS. The raster values were categorized into five fire-danger classes. The results were validated by comparison to the past fires using OA (Overall Accuracy), and kappa index. Results demonstrated that the human-influence factor, with weight of 0.48, is the most effective variable in fire-danger modeling in the Northern Khorasan Province. The fire-danger map indicated that very high-danger and high-danger areas cover 54.65% of the province, a spatially extensive amount of land having high fire likelihood. In statistical terms, the accuracy of fire danger map was high with OA of 96%, and the kappa index of 0.85, reflects the high accuracy of fire-danger prediction in the study area. The fire danger map of the study area provides a baseline for informed fire management, mitigation, and prevention decisions in the natural ecosystems of Northern Khorasan Province. This map could be very useful for forecasting future fires in northeastern Iran.

Keywords: Fire occurrence; Fire-danger mapping; Fire prediction; Fuzzy AHP; GIS; Natural areas; Iran (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11069-024-06542-z

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