Producing forest fire susceptibility map via multi-criteria decision analysis and frequency ratio methods

ARCA D., Hacisalihoglu M., KUTOĞLU Ş. H.

NATURAL HAZARDS, vol.104, no.1, pp.73-89, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 104 Issue: 1
  • Publication Date: 2020
  • Doi Number: 10.1007/s11069-020-04158-7
  • Journal Name: NATURAL HAZARDS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, PASCAL, Aerospace Database, Agricultural & Environmental Science Database, Aquatic Science & Fisheries Abstracts (ASFA), CAB Abstracts, Communication Abstracts, Environment Index, Geobase, INSPEC, Metadex, PAIS International, Pollution Abstracts, Sociological abstracts, Veterinary Science Database, DIALNET, Civil Engineering Abstracts
  • Page Numbers: pp.73-89
  • Keywords: Multi-criteria decision analysis, Frequency ratio method, GIS, Forest fire susceptibility map, Karabuk, WEIGHTED LINEAR COMBINATION, GIS, EXTENSION, OWA
  • Dokuz Eylül University Affiliated: Yes


Located in the Mediterranean basin, one of the world's leading places in terms of forest fires, Turkey is one of the countries where forest fires are experienced very often due to both natural and socio-economic conditions. The objective of this study is to conduct a forest fire susceptibility analysis within the boundaries of Karabuk Forestry Directorate. This analysis was conducted considering the factors affecting the forest fire risk (elevation, slope, aspect, distance to road lines, distance to settlement, land surface temperature and stand type). The factors used in the study were analyzed using geographic information systems (GIS) techniques and analytic hierarchy process method and frequency ratio method. The forest fire susceptibility map produced was classified in 5 categories including very low, low, moderate, high and very fire susceptibility. In order to see how much the forest fire susceptibility map produced corresponds to reality, the forest fire susceptibility maps and the forest fire inventory map were highly compared, and a 73.92% correspondence was detected according to the multi-criteria decision analysis method, while a 76.42% correspondence was detected in the frequency ratio method. As a result, it was concluded that high- and very high-sensitive areas were dominant in the study area, and the site had a high forest fire potential. Ultimately, this study indicated that GIS could be used as a tool to help make effective decisions during forest fire planning.