4.7 Article

Forest fire susceptibility mapping via multi-criteria decision analysis techniques for Mugla, Turkey: A comparative analysis of VIKOR and TOPSIS

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FOREST ECOLOGY AND MANAGEMENT
卷 480, 期 -, 页码 -

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ELSEVIER
DOI: 10.1016/j.foreco.2020.118644

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Forest fire susceptibility mapping; Multi criteria decision analysis; AHP; TOPSIS; VIKOR

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Turkey faces a high forest fire potential along the Aegean and Mediterranean coasts, necessitating the use of scientific methods to determine susceptibility zones to protect ecosystems, habitats, and human lives.
Turkey has a high forest fire potential along the Aegean and Mediterranean coasts, related to climate and extremely sensitive forests. In Turkey over 10,000-ha forest area has been destroyed every year and inevitable damage has been revealed. Forest fires not only destroy forest areas, but also cause damage to ecosystems, habitats and especially human lives. Because Mugla province has 90% of total pine honey production in the world and a high potential forest fire occurrence rate, sustainability of ecosystems, productivity and economic income require determining forest fire susceptibility zones. Generating forest fire susceptibility zones is a complex study which requires considering environmental, forestry, topographic, economic, and meteorological parameters within a decision support platform. At this point, Geographical Information System (GIS) aided Multi-Criteria Decision Analysis (MCDA) techniques can provide sufficient and effective solutions for fire susceptibility mapping due to the comparable and scalable structure of the criteria that are used to determine the susceptibility map when deciding. In this study, the weight of each criterion is calculated via the Analytical Hierarchy Process (AHP). Then, TOPSIS and VIKOR methods were used to generate forest fire susceptibility maps in Mugla province. The results indicated that 1659.44 ha (13%) and 3952.14 ha (31%) of the study area were assigned as highly prone to forest fire according to the TOPSIS and VIKOR calculations respectively, and an 81% correlation coefficient was calculated between methods. The reliabilities of the maps were verified with 1454 forest fire locations. Considering the respective 89.54%, 86.94% and 88.99% accuracy rate of VIKOR, TOPSIS and AHP susceptibility maps, all the methods could be used in forest fire susceptibility map generation which has comprehensive decision making process.

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