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Journals / Bayburt Üniversitesi Fen Bilimleri Dergisi / 2026 / Cilt: 9 Sayı: 1

Integration of Remote Sensing and 3D Printing for Disaster Evacuation Planning in Campus Areas: The Case of Bayburt University Baberti Campus

Kampüs Alanlarında Afet Tahliye Planlaması İçin Uzaktan Algılama ve 3D Baskı Entegrasyonu: Bayburt Üniversitesi Baberti Yerleşkesi Örneği

Canan Cengiz(BAYBURT UNIVERSITY)0009-0008-0634-680X
Murat Camuzcuoğlu(BAYBURT ÜNİVERSİTESİ)0000-0001-7205-1550
Pages
43–54
Publication Date
2026-06-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In addition, it was concluded that this approach improves evacuation planning and logistical response capacity.

📌 3 Key Takeaways

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Objective & Hypothesis:Earthquakes pose a serious threat to settlements located in regions with high seismic activity.
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Key Findings & Data:The analyses showed that the dormitory buildings located on steep slopes (>20%) along the eastern axis of the campus are exposed to high risk.
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Conclusion & Impact:In addition, it was concluded that this approach improves evacuation planning and logistical response capacity.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Mühendislik Jeolojisi · Uzaktan Algılama · Sismik Risk Analizi

Abstract

Earthquakes pose a serious threat to settlements located in regions with high seismic activity. In this study, the Baberti Campus of Bayburt University, which is under seismic risk due to its proximity to the North Anatolian Fault (NAF), was examined. A method integrating remote sensing (RS) data and three-dimensional printing technologies was proposed to enhance the disaster resilience of the campus area. Within the scope of the study, the geological infrastructure and topographic characteristics of the area were evaluated in terms of disaster management. The analyses showed that the dormitory buildings located on steep slopes (>20%) along the eastern axis of the campus are exposed to high risk. In addition to possible structural damage during seismic shaking, secondary disaster risks such as debris flow and rockfall were also identified for these structures. Disaster scenario analyses were carried out on the produced three-dimensional physical model. These analyses enabled the clear visualization of building density, possible debris dispersion areas, and topographic barriers. Thus, the safest evacuation routes and strategic assembly areas were identified. The findings, supported by the L-type Risk Matrix, indicate that the combined use of spatial data and physical models increases the increases decision-making speed. In addition, it was concluded that this approach improves evacuation planning and logistical response capacity.

Özet

Deprem, sismik aktivitenin yüksek olduğu bölgelerdeki yerleşim alanları için ciddi bir tehdit oluşturmaktadır. Bu çalışmada, Kuzey Anadolu Fay Hattı’na (KAF) yakınlığı nedeniyle sismik risk altında bulunan Bayburt Üniversitesi Baberti Kampüsü ele alınmıştır. Kampüs alanlarının afet dirençliliğini artırmak amacıyla uzaktan algılama (UA) verileri ile üç boyutlu baskı teknolojilerini birleştiren bir yöntem önerilmiştir. Çalışma kapsamında, alanın jeolojik altyapısı ve topografik özellikleri afet yönetimi açısından değerlendirilmiştir. Analizler, yerleşkenin doğu aksında bulunan ve yüksek eğime (>%20) sahip yamaçlardaki yurt binalarının yüksek risk taşıdığını göstermiştir. Bu yapılarda, sismik sarsıntı sırasında oluşabilecek yapısal hasara ek olarak, yamaç akışı ve kaya düşmesi gibi ikincil afet riskleri de belirlenmiştir. Üretilen üç boyutlu fiziksel model üzerinde afet senaryo analizleri gerçekleştirilmiştir. Bu analizler sayesinde bina yoğunluğu, olası enkaz yayılım alanları ve topografik engeller somut biçimde ortaya konmuştur. Böylece en güvenli tahliye rotaları ile stratejik toplanma alanları belirlenmiştir. L-Tipi Risk Matrisi ile desteklenen bulgular, mekânsal verilerin fiziksel modellerle birlikte kullanılmasının karar verme hızını artırdığını göstermektedir. Ayrıca bu yaklaşımın tahliye planlamasını ve lojistik müdahale kapasitesini iyileştirdiği sonucuna ulaşılmıştır.

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Cite This Article

Cengiz, C., Camuzcuoğlu, M. (2026). Integration of Remote Sensing and 3D Printing for Disaster Evacuation Planning in Campus Areas: The Case of Bayburt University Baberti Campus. Bayburt Üniversitesi Fen Bilimleri Dergisi, Cilt: 9 Sayı: 1, 43–54. https://doi.org/10.55117/bufbd.1932202

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