Comparison between Post-Fire Analysis and Pre-Fire Risk Assessment According to Various Geospatial Data

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dc.authoridOzcan, Orkan/0000-0002-7485-6157
dc.authoridGUNGOROGLU, CUMHUR/0000-0003-3932-3205
dc.authoridMUSAOGLU, NEBIYE/0000-0002-8022-8755
dc.contributor.authorGungoroglu, Cumhur
dc.contributor.authorIsmailoglu, Irem
dc.contributor.authorKapukaya, Bekir
dc.contributor.authorOzcan, Orkan
dc.contributor.authorYanalak, Mustafa
dc.contributor.authorMusaoglu, Nebiye
dc.date.accessioned2024-09-29T16:08:15Z
dc.date.available2024-09-29T16:08:15Z
dc.date.issued2024
dc.departmentKarabük Üniversitesien_US
dc.description.abstractWildfires in forest ecosystems exert substantial ecological, economic, and social impacts. The effectiveness of fire management hinges on precise pre-fire risk assessments to inform mitigation efforts. This study aimed to investigate the relationship between predictions from pre-fire risk assessments and outcomes observed through post-fire burn severity analyses. In this study, forest fire risk was assessed through the Fuzzy Analytical Hierarchy Process (FAHP), in which fire-oriented factors were used as input. The degree of burn was determined by the Random Forest method using 11,519 training points and 400 test points on Sentinel-2 satellite images under three different classes. According to the results obtained from 266 selected test points located within the forest, all primary factors put forth increased high burn severity. Climate, in particular, emerged as the most significant factor, accounting for 52% of the overall impact. However, in cases of high fire severity, climate proved to be the most effective risk factor, accounting for 67%. This was followed by topography with 50% accuracy at a high fire intensity. In the risk assessment based on the FAHP method, climate was assigned the highest weight value among the other factors (32.2%), followed by topography (27%). To evaluate the results more comprehensively, both visually and statistically, two regions with different stand canopy characteristics were selected within the study area. While high burn severity had the highest accuracy in the Case 1 area, moderate burn severity had the highest in the Case 2 area. During the days of the fire, the direction of spreading was obtained from the MODIS images. In this way, the fire severity was also interpreted depending on the direction of fire progression. Through an analysis of various case studies and literature, this research underlines both the inherent strengths and limitations of predicting forest fire behavior-based pre-fire risk assessments. Furthermore, it emphasizes the necessity of continuous improvement to increase the success of forest fire management.en_US
dc.description.sponsorshipIstanbul Technical University (ITU) Scientific Projects Office (BAP)en_US
dc.description.sponsorshipNo Statement Availableen_US
dc.identifier.doi10.3390/su16041569
dc.identifier.issn2071-1050
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85185967005en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.3390/su16041569
dc.identifier.urihttps://hdl.handle.net/20.500.14619/7435
dc.identifier.volume16en_US
dc.identifier.wosWOS:001172362600001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherMdpien_US
dc.relation.ispartofSustainabilityen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectforest fireen_US
dc.subjectremote sensingen_US
dc.subjectrisk assessmenten_US
dc.subjectManavgaten_US
dc.subjectfuzzy analytic hierarchy process (FAHP)en_US
dc.titleComparison between Post-Fire Analysis and Pre-Fire Risk Assessment According to Various Geospatial Dataen_US
dc.typeArticleen_US

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