A Multi-Criteria Forest Fire Danger Assessment System on GIS Using Literature-Based Model and Analytical Hierarchy Process Model for Mediterranean Coast of Manavgat, Türkiye

Basit Öğe Kaydı
dc.authoridUNSAL, EMRE/0000-0001-6042-0742
dc.contributor.authorErsoy, Izzet
dc.contributor.authorUnsal, Emre
dc.contributor.authorGursoy, Onder
dc.date.accessioned2025-05-04T16:45:40Z
dc.date.available2025-05-04T16:45:40Z
dc.date.issued2025
dc.departmentSivas Cumhuriyet Üniversitesi
dc.description.abstractForest fires pose significant environmental and economic risks, particularly in fire-prone regions like the Mediterranean coast of T & uuml;rkiye. This study presents a comprehensive Forest Fire Danger Assessment System (FoFiDAS), by integrating Geographic Information Systems (GIS), a literature-based model, the Analytical Hierarchy Process (AHP), and machine learning (ML) to improve forest fire danger classification. Both models integrate 13 key parameters identified through the literature. A comparison of these models revealed 53% overlap in fire danger classifications. While the AHP model, based on expert-weighted assessment, provided a more structured and localized classification, the literature-based model relied on broader scientific data but lacked adaptability. Pearson correlation analysis demonstrated a strong correlation between fire danger classifications and historical fire occurrences, with correlation scores of 0.927 (AHP) and 0.939 (literature-based). Further ROC analysis confirmed the predictive performance of both models, yielding AUC values of 0.91 and 0.9121 for the literature-based and AHP models, respectively. Five ML algorithms were used to validate classification performances, with Artificial Neural Network (ANN) achieving the highest accuracy (86.5%). The accuracy of the ANN algorithm exceeded 0.93 for each danger class, and the F1-Score was above 0.85. FoFiDAS offers a reliable tool for fire danger assessment, supporting early intervention and decision making.
dc.identifier.doi10.3390/su17051971
dc.identifier.issn2071-1050
dc.identifier.issue5
dc.identifier.scopus2-s2.0-86000572018
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.3390/su17051971
dc.identifier.urihttps://hdl.handle.net/20.500.12418/35176
dc.identifier.volume17
dc.identifier.wosWOS:001443509400001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherMDPI
dc.relation.ispartofSustainability
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20250504
dc.subjectforest fire
dc.subjectfire danger analysis
dc.subjectfire danger mapping
dc.subjectgeographical information system
dc.subjectmachine learning
dc.subjectanalytical hierarchy process
dc.subjectAHP-GIS integration
dc.titleA Multi-Criteria Forest Fire Danger Assessment System on GIS Using Literature-Based Model and Analytical Hierarchy Process Model for Mediterranean Coast of Manavgat, Türkiye
dc.typeArticle

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu