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Forest fire spatial modelling using ordered weighted averaging multi-criteria evaluation

Author

Listed:
  • Hassan Faramarzi

    (Department of Natural Resources, Tarbiat Modares University, Tehran, Iran)

  • Seyd Mohsen Hosseini

    (Department of Natural Resources, Tarbiat Modares University, Tehran, Iran)

  • Hamid Reza Pourghasemi

    (Department of Natural Resources and Environment Engineering, College of Agriculture, Shiraz University, Shiraz, Iran)

  • Mahdi Farnaghi

    (Department of Geo-Information Processing (GIP), Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, the Netherlands)

Abstract

Forest fires are a major environmental issue because they are increasing as a consequence of climate change and global warming. The present study was aimed to model forest fire hazard using the ordered weighted averaging (OWA) multi-criteria evaluation algorithm and to determine the role of human, climatic, and environmental factors in forest fire occurrence within the Golestan National Park (GNP), Iran. The database used for the present study was created according to daily classification of climate changes, environmental basic maps, and human-made influential forest fire factors. In the study area, the forest fires were registered using GPS. Expert opinions were applied through the analytic hierarchy process (AHP) to determine the importance of effective factors. Fuzzy membership functions were used to standardize the thematic layers. The fire risk maps were prepared using different OWA scenarios for man-made, climatic, and environment factors. The findings revealed that roads (weight = 0.288), rainfalls (weight = 0.288), and aspects (weight = 0.255) are the major factors that contribute to the occurrence of forest fire in the study area. The forest fire maps prepared from different scenarios were validated using the relative operating characteristic (ROC) curve. Values of forest fire maps acquired from scenarios of human, environment, climate factors and their combination were 0.87, 0.731, 0.773 and 0.819, respectively.

Suggested Citation

  • Hassan Faramarzi & Seyd Mohsen Hosseini & Hamid Reza Pourghasemi & Mahdi Farnaghi, 2021. "Forest fire spatial modelling using ordered weighted averaging multi-criteria evaluation," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 67(2), pages 87-100.
    • Handle: RePEc:caa:jnljfs:v:67:y:2021:i:2:id:50-2020-jfs
    DOI: 10.17221/50/2020-JFS
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    References listed on IDEAS

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    1. Cantarello, Elena & Newton, Adrian C. & Hill, Ross A. & Tejedor-Garavito, Natalia & Williams-Linera, Guadalupe & López-Barrera, Fabiola & Manson, Robert H. & Golicher, Duncan J., 2011. "Simulating the potential for ecological restoration of dryland forests in Mexico under different disturbance regimes," Ecological Modelling, Elsevier, vol. 222(5), pages 1112-1128.
    2. Claus Rinner & Jacek Malczewski, 2002. "Web-enabled spatial decision analysis using Ordered Weighted Averaging (OWA)," Journal of Geographical Systems, Springer, vol. 4(4), pages 385-403, December.
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