Research Article

Artificial Intelligence Assisted Decision Support System for Forest Fire Crisis Management in Turkey

Volume: 8 Number: 2 December 26, 2025

Artificial Intelligence Assisted Decision Support System for Forest Fire Crisis Management in Turkey

Abstract

Natural disasters, particularly forest fires, significantly impact societies by causing loss of life and property. Effective crisis management, encompassing disaster response and subsequent mitigation efforts, is critically important. This paper, drawing upon an Artificial Intelligence (AI) based Decision Support System (DSS) developed for natural disasters in Turkey, focuses specifically on forest fire management. The system utilizes historical fire data and machine learning (ML) techniques to predict the impacts of fires, enhance decision-making processes, and provide timely, accurate information to decision-makers. Data on forest fires in Turkey, primarily from the satellite-based NASA FIRMS dataset and atmospheric analysis from ECMWF ERA5, were analyzed and interpreted. Preprocessing steps, including data cleaning and feature extraction, were applied. An XGBoost classification model was developed and evaluated for fire risk prediction, demonstrating high performance in identifying fire-prone regions and their potential intensity. The developed AI-based system determines provincial risk scores, aiming for effective resource allocation for natural disasters. Performance metrics such as accuracy, precision, and F1 score were calculated, and the model's performance was examined. The system culminates in a user-friendly prototype, the Turkey Disaster Management System (TDMS), offering risk-based resource allocation simulations and AI-supported reporting for proactive fire management.

Keywords

References

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Details

Primary Language

English

Subjects

Artificial Intelligence (Other)

Journal Section

Research Article

Early Pub Date

December 16, 2025

Publication Date

December 26, 2025

Submission Date

September 23, 2025

Acceptance Date

December 3, 2025

Published in Issue

Year 2025 Volume: 8 Number: 2

APA
Yaraş, İ. E., & Onan, A. (2025). Artificial Intelligence Assisted Decision Support System for Forest Fire Crisis Management in Turkey. Scientific Journal of Mehmet Akif Ersoy University, 8(2), 95-113. https://doi.org/10.70030/sjmakeu.1789925
AMA
1.Yaraş İE, Onan A. Artificial Intelligence Assisted Decision Support System for Forest Fire Crisis Management in Turkey. Techno-Science. 2025;8(2):95-113. doi:10.70030/sjmakeu.1789925
Chicago
Yaraş, İbrahim Emre, and Aytuğ Onan. 2025. “Artificial Intelligence Assisted Decision Support System for Forest Fire Crisis Management in Turkey”. Scientific Journal of Mehmet Akif Ersoy University 8 (2): 95-113. https://doi.org/10.70030/sjmakeu.1789925.
EndNote
Yaraş İE, Onan A (December 1, 2025) Artificial Intelligence Assisted Decision Support System for Forest Fire Crisis Management in Turkey. Scientific Journal of Mehmet Akif Ersoy University 8 2 95–113.
IEEE
[1]İ. E. Yaraş and A. Onan, “Artificial Intelligence Assisted Decision Support System for Forest Fire Crisis Management in Turkey”, Techno-Science, vol. 8, no. 2, pp. 95–113, Dec. 2025, doi: 10.70030/sjmakeu.1789925.
ISNAD
Yaraş, İbrahim Emre - Onan, Aytuğ. “Artificial Intelligence Assisted Decision Support System for Forest Fire Crisis Management in Turkey”. Scientific Journal of Mehmet Akif Ersoy University 8/2 (December 1, 2025): 95-113. https://doi.org/10.70030/sjmakeu.1789925.
JAMA
1.Yaraş İE, Onan A. Artificial Intelligence Assisted Decision Support System for Forest Fire Crisis Management in Turkey. Techno-Science. 2025;8:95–113.
MLA
Yaraş, İbrahim Emre, and Aytuğ Onan. “Artificial Intelligence Assisted Decision Support System for Forest Fire Crisis Management in Turkey”. Scientific Journal of Mehmet Akif Ersoy University, vol. 8, no. 2, Dec. 2025, pp. 95-113, doi:10.70030/sjmakeu.1789925.
Vancouver
1.İbrahim Emre Yaraş, Aytuğ Onan. Artificial Intelligence Assisted Decision Support System for Forest Fire Crisis Management in Turkey. Techno-Science. 2025 Dec. 1;8(2):95-113. doi:10.70030/sjmakeu.1789925