Integrated risk mapping for forest fire management using the analytical hierarchy process and ordered weighted average: a case study in southern Turkey


Özcan Z., ÇAĞLAYAN İ., Kabak Ö., KILIÇ GÜL F.

Natural Hazards, 2024 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Publication Date: 2024
  • Doi Number: 10.1007/s11069-024-06810-y
  • 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, Veterinary Science Database, DIALNET, Civil Engineering Abstracts
  • Keywords: AHP, Forest fire, GIS, MCDM, OWA, Risk mapping
  • Yıldız Technical University Affiliated: Yes

Abstract

Forest fires pose a critical problem for natural environments and human settlements, necessitating effective risk management approaches. This study focuses on forest fire risk (FFR) mapping in the Antalya Forest, southern Turkey, by analyzing different criteria. Extensive literature research identifies nearly twenty criteria, which we re-evaluate based on expert opinions and study area characteristics, leading to the selection of four main criteria and fourteen sub-criteria. We process the data using Geographic Information System (GIS) software and calculate weights using the Analytical Hierarchy Process (AHP) and Ordered Weighted Average (OWA) techniques. The main criteria are topographic, meteorological, land use, and forest structure. In the AHP sub-criteria, precipitation, tree species, distance to settlement areas, and elevation receive high values. We classify the resultant FFR maps into five risk classes using both the Jenks Natural Breaks method and equal interval classification. We evaluate the accuracy of our maps using Receiver Operating Characteristic (ROC) analysis and Area Under Curve (AUC) values, based on historical forest fire data. The equal interval classification shows decreased alignment with historical fire data, especially for the AHP method, which performs significantly worse. Both OWA and AHP methods show better performance with Jenks classification compared to equal interval classification, indicating that Jenks Natural Breaks more effectively captures natural groupings in the data, making it a more suitable choice for risk mapping. Applying AHP and OWA in FFR mapping benefits regional forest management and highlights the universal applicability of these methodologies for broader environmental hazard assessments under changing climates.