MULTI-CRITERIA STRATEGIC PLANNING WITH TWO DIFFERENT SCALE APPROACHES IN FIRE STATION SITE SELECTION

Year 2026, Volume: 14 Issue: 1, 113 - 136, 01.03.2026

Gamze Akyüz , Şükran Yalpır

https://doi.org/10.36306/konjes.1730637

https://izlik.org/JA23ZS47PX

Abstract

Today, global warming and sudden increase in seasonal temperatures cause forest fires. It is necessary to locate fire stations that can offer effective use in forest fires, since their accessibility is difficult and requires urgent intervention. There are many positional factors that need to be considered in the installation of these stations. In this study, the fire station requirement was evaluated at two different scales. This study aims to determine the optimal locations for fire stations in Antalya Province to improve rapid response and effectiveness in forest fire interventions. In Section 1, a study was carried out based on the province (Antalya), which has priority installation needs in the Mediterranean region of Turkey, where the most intense forest fires are experienced. In Section 2, other positional criteria within the provincial border of Antalya were examined. The criteria used in the application of both scales are different. In addition, map bases were arranged by using Geographic Information Systems (GIS) in the fire station location selection in the study. GIS has been used to define location quickly, safely and in a controlled manner and to integrate maps. Appropriate criteria for the study area were determined and the weighting of the criteria was carried out with the Best-Worst Method (BWM). In Section 3, forest fire intensities were established by hotspot analysis for the period from 2015 to 2021 based on forest fire points. Five alternative regions were detected by overlapping the spatial suitability map obtained as a result of Section 2 with the hotspot analysis map. By Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) analysis of the five alternative regions the construction region was established first.

Keywords

Geographic information system , Best-Worst Management , TOPSIS , Fire station , Mediterranean Region

Ethical Statement

The authors conducted this study in accordance with all ethical standards

Supporting Institution

No funding is available for this research.

References

• G. Asri, Ö. Çorumluoğlu ve E. Özdemir, “CBS destekli orman yangını risk dağılım analizi; Antalya örneği,” 15th Turkish Scientific and Technical Mapping Congress, Ankara, Turkey, 2015, pp. 25-28.
• M. N. Alkan, Entegre Çok Kriterli Karar Verme Yöntemi ve Hedef Programlama ile En Uygun İtfaiye Yeri Seçimi, M.S. thesis, Dept. Ind. Eng., Sakarya Univ., Sakarya, Turkey, 2019. [Online]. Available:https://tez.yok.gov.tr/UlusalTezMerkezi/tezDetay.jsp?id=zXyJPPq0zlWtYCotrlAorg&no=KKm68pVM5aeS4TPVFSatSQ. [Accessed Jun. 26, 2025].
• E. Aktaş, Ö. Özaydın, F. Ülengin, Ş. Önsel Ekici, and B. Ağaran, “İstanbul'da itfaiye istasyonu yerlerinin seçimi için yeni bir model,” Endüstri Müh. Derg., vol. 22, no. 4, pp. 2-12, 2011.
• R. Geçen, “Ağ analizi kullanılarak acil durumlarda itfaiye araçlarının erişebilirlik analizi: Ceyhan (Adana) Örneği, ” Ege Coğrafya Derg., vol. 28, no. 2, pp. 199–211, 2019.
• G. Yılmaz, G. Usta, and K. Torpuş, “Artvin itfaiye müdürlüğü'nün 2008-2017 yılları arasında müdahale ettiği köy yangınları üzerine bir inceleme,” Ulus. Aras. Sos. Araş. Derg., vol. 12, no. 62, 2019, doi: 10.17719/jisr.2019.3801.
• A. Şişman, “Yangın Risk Haritasının Üretilmesi ve İstasyonların Konumlarının Uygun Yer Analizi İle İrdelenmesi,” in Proc. ISITES2015, Valencia, Spain, pp. 488-493, 2015.
• E. N. Nacar and B. Erdebilli, “Tesis yeri seçimine yeni bir bakış: Katmanlı çok kriterli karar verme yöntemi,” Verimlilik Derg., vol. 2021, no. 4, pp. 103-117, Oct. 2021, doi: 10.51551/verimlilik.832480.
• E. Erten, V. Kurgun, and N. Musaoğlu, “Uzaktan algılama ve coğrafi bilgi sistemleri kullanarak orman yangını bilgi sisteminin kurulması,” in Proc. 10th Turkey Scientific and Technical Mapping Conference, Ankara, Turkey, 2005, Mar. 28 – Apr. 1.
• I. Badi, M. L. Jibril, and M. Bakır, “A composite approach for site optimization of fire stations,” J. Intell. Manag. Decis., vol. 1, no. 1, pp. 28-35, 2022, doi: 10.56578/jimd010104.
• P. H. Nyimbili and T. Erden, “İstanbul, Türkiye'deki itfaiye istasyonlarının optimum yer seçimi için CBS tabanlı bulanık çok kriterli yaklaşım, ” Sosyo-Ekon. Planlama Bilim., vol. 71, Sep. 2020, p. 100860, doi:10.1016/j.seps.2020.100860.
• T. Erden, “Coğrafi bilgi sistemleri ile analitik hiyerarşi yöntemi’ne dayalı itfaiye istasyon yer seçimi: İstanbul örneği,” Ph.D. dissertation, Grad. Sch. Sci., Dept. Geod. & Photogr. Eng., Istanbul Tech. Univ., İstanbul, 2009.
• T. Erden and M. Z. Coşkun, “Coğrafi bilgi sistemleri ve analitik çözüm yöntemi yardımıyla itfaiye istasyon yer seçimi,” in Proc. 13th Turkey Scientific and Technical Mapping Conference, Ankara, Turkey, 2011, Apr. 18-22, pp. 301-304.
• H. Amin-Tahmasbi, S. M. MirAkbari, and H. Nasirzadeh, “Optimizing the location of urban uses with combined methods Delphi-BWM-PROMETHEE (case study of Ahvaz fire stations),” Urban Plan. Knowl., vol. 4, no. 3, pp. 89-110, 2020, doi: 10.22124/upk.2020.16186.1438.
• D. Chen and H. Xie, “ [Retracted] Fire safety evaluation for scenic spots: An evidential best‐worst method,” J. Math., vol. 2023, Art. no. 9806305, 2023, doi: 10.1155/2023/9806305.
• G. KhoshAmooz, “A new fuzzy location-based approach for fire station site selection in Tehran,” Appl. Geomatics, vol. 16, no. 4, pp. 987-1001, 2024, doi: 10.21203/rs.3.rs-3917117/v1.
• “2021 Türkiye orman yangınları,” Wikipedia, The Free Encyclopedia, 2021. [Online]. Available: https://tr.wikipedia.org/wiki/2021_T%C3%BCrkiye_orman_yang%C4%B1nlar%C4%B1#cite_note-5. [Accessed Jun. 26, 2025].
• O. N. Sunar ve S. Kurnaz, “Afet yönetimi bağlamında havacılığın orman yangınlarıyla mücadeledeki rolü üzerine bir değerlendirme”, International Journal of Aeronautics and Astronautics, c. 3, sy. 2, pp. 60–70, 2022, doi: 10.55212/ijaa.1143554.
• Ö. Eker and D. M. Abdurrahmanoğlu, “Orman yangınlarıyla mücadele harcamalarının analizi: Kahramanmaraş Orman Bölge Müdürlüğü örneği”, Turk J For Sci, vol. 2, no. 1, pp. 34–48, 2018, doi: 10.32328/turkjforsci.400491.
• A. Küçükosmanoğlu, “Relationship between Turkish pine and forest fires,” J. Fac. For. Istanbul Univ., vol. 40, no. 4, pp. 67–84, 1990, doi: 10.17099/jffiu.78360.
• C. Duran, “Mersin ilindeki orman yangınlarının başlangıç noktalarına göre mekânsal analizi (2001-2013),” Ormanc. Araş. Derg., vol. 1, no. 1A, pp. 38-49, 2014, doi: 10.17568/oad.87328.
• “Orman Yangınları,” Çevresel Göstergeler, 2020. [Online]. Available: https://cevreselgostergeler.csb.gov.tr/orman-yanginlari-i-85850. [Accessed Jun. 26, 2025].
• E. Bilgili, İ. Baysal, B. D. Durmaz, B. Sağlam, and Ö. Küçük, “Türkiye’de 2008 yılında çıkan büyük orman yangınlarının değerlendirilmesi,” in Proc. 3rd National Black Sea Forestry Congress, Artvin, Turkey, 2010, p. 1.
• R. Geçen and İ. Ölmez, “Antakya'da (Hatay) itfaiyelerin acil durumlarda erişebilirliği,” Ulus. Sos. Araş. Derg./ J. Int. Soc. Res., vol. 11, no. 60, 2018, doi: 10.17719/jisr.2018.2786.
• P. Chaudhary, S. K. Chhetri, K. M. Joshi, B. M. Shrestha, and P. Kayastha, "Application of an analytic hierarchy process (AHP) in the GIS interface for suitable fire site selection: A case study from Kathmandu Metropolitan City, Nepal," Socio-Econ. Plan. Sci., vol. 53, pp. 60-71, 2016, doi: 10.1016/j.seps.2015.10.001.
• A. A. Mehrizi and T. K. Karimabadi, “Location of fire station in Bam city using fuzzy analytic hierarchy process,” in Proc. 9th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS), Bam, Iran, Mar. 2–4, 2022, pp. 1–6, doi: 10.1109/CFIS54774.2022.9756473.
• M. Aruldoss, T. M. Lakshmi, and V. P. Venkatesan, “A survey on multi criteria decision making methods and its applications,” Am. J. Inf. Syst., vol. 1, no. 1, pp. 31–43, 2013, doi: 10.12691/ajis-1-1-5.
• E. Aktaş, Ö. Özaydın, B. Bozkaya, F. Ülengin, and Ş. Önsel, “Optimizing fire station locations for the Istanbul metropolitan municipality,” Interfaces, vol. 43, no. 3, pp. 240–255, 2013, dio: 10.1287/inte.1120.0671.
• A. Şen Et Al. , “A GIS Approach to Fire Station Location Selection,” 4th International Symposium on Geo-information for Disaster Management, Gi4DM 2011 , Antalya, Turkey, 2011.
• B. Han, M. Hu, J. Zheng, and T. Tang, “Site selection of fire stations in large cities based on actual spatiotemporal demands: A case study of Nanjing City,” ISPRS Int. J. Geo-Inf., vol. 10, no. 8, p. 542, 2021, doi: 10.3390/ijgi10080542.
• A. E. Okutan and G. Çavuş, “Deprem sonrası ortaya çıkabilecek orman yangınları; peyzaj mimarlığı alanında alınabilecek pasif önlemler,” Duzce Univ. For. Fac. Ormanc. Derg., vol. 8, no. 1, pp. 19–33, 2012.
• D. Cengiz, “Çok kriterli karar verme yöntemleri üzerine karşılaştırmalı analiz,” M.S. thesis, Dept. Stat., Grad. Sch. Sci., Yıldız Tech. Univ., Istanbul, Turkey, 2012. [Online]. Available: https://tez.yok.gov.tr/UlusalTezMerkezi/tezDetay.jsp?id=ShCBR0ziLyZjWw9RG7JmVQ&no=tUzPse5bM3qunDwLrxqWdQ [Accessed Jun. 26, 2025]. J. Rezaei, “Best-worst multi-criteria decision-making method,” Omega, vol. 53, pp. 49–57, 2015, doi: 10.1016/j.omega.2014.11.009.
• M. W. Herman and W. W. Koczkodaj, “A Monte Carlo study of parwise comparison,” Inf. Process. Lett., vol. 57, no. 1, pp. 25–29, 1996.
• X. Mi, M. Tang, H. Liao, W. Shen, and B. Lev, “The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what’s next?,” Omega, vol. 87, pp. 205–225, 2019, doi: 10.1016/j.omega.2019.01.009.
• H. Gupta, “Assessing organizations performance on the basis of GHRM practices using BWM and fuzzy TOPSIS,” J. Environ. Manag., vol. 226, pp. 201–216, 2018, doi: 10.1016/j.jenvman.2018.08.005.
• P. Sirisawat and T. Kiatcharoenpol, “Fuzzy AHP-TOPSIS approaches to prioritizing solutions for reverse logistics barriers,” Comput. Ind. Eng., vol. 117, pp. 303–318, 2018, doi: 10.1016/j.cie.2018.01.015.
• B. C. Ervural, S. Zaim, O. F. Demirel, Z. Aydin, and D. Delen, “An ANP and fuzzy TOPSIS-based SWOT analysis for Turkey’s energy planning,” Renew. Sustain. Energy Rev., vol. 82, pp. 1538–1550, 2018, doi: 10.1016/j.rser.2017.06.095.
• H. Han and S. Trimi, “A fuzzy TOPSIS method for performance evaluation of reverse logistics in social commerce platforms,” Expert Syst. Appl., vol. 103, pp. 133–145, 2018, doi: 10.1016/j.eswa.2018.03.003.
• X. Sang, X. Liu, and J. Qin, “An analytical solution to fuzzy TOPSIS and its application in personnel selection for knowledge-intensive enterprise,” Appl. Soft Comput., vol. 30, pp. 190–204, 2015, doi: 10.1016/j.asoc.2015.01.002.
• A. Yıldız and Y. Demir, “Bulanık TOPSIS yöntemiyle Türkiye’nin yerli otomobili için en uygun fabrika yerinin seçimi,” Bus. Manag. Stud.: Int. J., vol. 7, no. 4, pp. 1427–1445, 2019, doi: 10.15295/bmij.v7i4.1210.
• P. F. Kuo, X. Zeng, and D. Lord, “Guidelines for choosing hot-spot analysis tools based on data characteristics, network restrictions, and time distributions,” in Proc. 91st Annu. Meet. Transp. Res. Board, Nov. 2011, pp. 22–26.
• M. Gür and Ö. Bilen, “Türkiye’de Şiddet Suçlarından Hüküm Giyenlerin Mekansal Dağılımını Etkileyen Faktörler,” in Violence and Social Traumas, Ankara, Turkey: HEGEM Publications, 2018, pp. 200–211.
• F. Tian, J. Lei, X. Zheng, and Y. Yin, "Integrating space syntax and location-allocation model for fire station location planning in a China mega city," Fire, vol. 6, no. 2, p. 64, 2023, doi: 10.3390/fire6020064.
• A. Ç. Aydınoğlu, S. Şişman, and İ. Ergül, “Sezgisel Ağ Tabanlı Konum Tahsis Analiz Algoritmaları ile Tesis Yeri Optimizasyonu: İtfaiye Tesisleri Yer Seçimi Örneği,” Journal of Transportation and Operations Management (JTOM), vol. 6, no. 1, pp. 955–976, 2022.