The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVI-4/W5-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W5-2021, 33–38, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W5-2021-33-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W5-2021, 33–38, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W5-2021-33-2021

  23 Dec 2021

23 Dec 2021

DEVELOPING VALIDATION OF FOREST FIRE RISK MAPS BASED ON HISTORICAL FIRE INCIDENCES

A. E. Akay and A. Erdoğan A. E. Akay and A. Erdoğan
  • Bursa Technical University, Faculty of Forestry, 16310 Yıldırım, Bursa, Turkey

Keywords: Forest Fires, Fire Risk Maps, Map validation, GIS, MCDA, AHP

Abstract. Large forest lands are damaged every year due to wild fires in Turkey. Prompt detection and rapid intervention is the key factors of firefighting activities. To be well prepared for the wildfires, it is crucial to determine the fire sensitive areas and then to locate fire extinguishing structures such as fire lookout towers and the firefighting headquarters by consideration these areas. The accuracy of the fire risk maps plays important role in the effectiveness of the fire management strategies and decisions. In this paper, the accuracy of a fire risk map, which was developed by GIS techniques integrated with Multi-Criteria Decision Analysis (MCDA), was evaluated based on the previous fire incidence in the study area. Analytic Hierarchy Process (AHP) method was used to generate fire risk map based on topographic features and forest vegetation structures. Then, total of 19 forest fires recorded in the study area in last 50 years were evaluated to validate the risk map. It was found that 23.81% of the area was subject to extreme risk, while 25.81% was of high risk. The results indicated that about 42.10% of the fire events fell into the forested areas with extreme fire risk, while 31,58% were in the high fire risk. Thus, the fire risk map developed by using the GIS-based MCDA can be an effective way for accurate estimation of the fire sensitive areas.