Mehmet İnanç ONUR, Majid AGHLMAND, Reza TALAEI

Heyelan Duyarlılık Haritalarının Üretilmesinde Analitik Hiyerarşi Yönteminin Ve Coğrafi Bilgi Sistemlerinin Kullanımı

Depremler ve heyelanlar toplum hayatını derinden etkileyen doğal afetlerin başında gelmektedir. Özellikle dağlık bölgelerde meydanagelen heyelanlar, her yıl can kaybına ve hasara sebep olmaktadır. Son yıllarda heyelana duyarlı bölgelerin belirlenmesi çalışmalarıoldukça yaygınlaşmıştır. Heyelan duyarlılık analizlerinin yapılması hem mühendislik projelerinin planlanmasını kolaylaştıracak hemde meydana gelebilecek zararların azaltılmasını sağlayacaktır. Bu çalışmada, İran'ın Ardabil (Erdebil) bölgesindeki Saqezchi'inheyelan duyarlılık haritaları oluşturulmuştur. Heyelan duyarlılık analizinde arazi kullanımı, yağış miktarı, faylara uzaklık, litoloji,akarsu ağlarına uzaklık, yükselti, eğim, bakı ve yola uzaklık parametreleri kullanılmıştır. Çalışmada heyelan duyarlılık haritasıoluşturulurken Analitik Hiyerarşi Süreci (AHP) yöntemi ve Coğrafi Bilgi Sistemleri (CBS) kullanılmıştır. Oluşturulan duyarlılıkharitaları, “çok yüksek, yüksek, orta, düşük ve çok düşük” duyarlı alanlar olmak üzere 5 grup altında sınıflandırılmıştır.

The Use of Analytical Hierarchy Process and Geographic Information Systems in Production of Landslide Susceptibility Maps

Earthquakes and landslides are among the natural disasters that deeply affect social life. Landslide, especially occurs in mountainous areas, causes loss of life and damages every year. Studies to determine landslide sensitive areas have become quite widespread in recent years. Conducting landslide susceptibility analysis will both facilitate the planning of engineering projects and reduce the loss. In this study, landslide susceptibility maps of Saqezchi in Ardabil (Ardebil) region of Iran are created. In landslide susceptibility analysis; land use, rainfall, distance to faults, lithology, distance to river networks, elevation, slope, aspect and distance to road parameters are used. Analytical Hierarchy Process (AHP) method and Geographic Information Systems (GIS) are used while creating landslide susceptibility map. The created sensitivity maps are classified under 5 groups as “very high, high, medium, low and very low” sensitive areas.

PDF

___

Akgun, A., & Türk, N. (2010). Landslide susceptibility mapping for Ayvalik (Western Turkey) and its vicinity by multicriteria decision analysis. Environmental Earth Sciences, 61(3), 595-611.
Cevik, E., & Topal, T. (2003). GIS-based landslide susceptibility mapping for a problematic segment of the natural gas pipeline, Hendek (Turkey). Environmental geology, 44(8), 949-962.
Clerici, A., Perego, S., Tellini, C., & Vescovi, P. (2006). A GIS-based automated procedure for landslide susceptibility mapping by the conditional analysis method: the Baganza valley case study (Italian Northern Apennines). Environmental Geology, 50(7), 941-961
Corominas, J., van Westen, C., Frattini, P., Cascini, L., Malet, J. P., Fotopoulou, S., ... & Pitilakis, K. (2014). Recommendations for the quantitative analysis of landslide risk. Bulletin of engineering geology and the environment, 73(2), 209-263.
Crozier, M. J. (1986). Landslides: causes, consequences and environment, Croom Helm. London. 252.
Dai, F. C., Lee, C. F., Li, J. X. Z. W., & Xu, Z. W. (2001). Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong. Environmental Geology, 40(3), 381-391.
Feizizadeh, B., & Blaschke, T. (2013). GIS-multicriteria decision analysis for landslide susceptibility mapping: comparing three methods for the Urmia lake basin, Iran. Natural hazards, 65(3), 2105-2128.
Feizizadeh, B., Roodposhti, M. S., Jankowski, P., & Blaschke, T. (2014). A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping. Computers & geosciences, 73, 208-221.
Hashemi Tabatabaei, S. (1998). Landslide hazard zonation in southwest of Ardabil Province Iran. Ministry of Roads and Urban Development, Tehran, Iran, 2.
Ilinca, V., & Gheuca, I. (2011). The Red Lake Landslide (Ucigaşu Mountain, Romania). Carpathian Journal of Earth and Environmental Sciences, 6(1), 263-272.
Lee, S., & Dan, N. T. (2005). Probabilistic landslide susceptibility mapping in the Lai Chau province of Vietnam: focus on the relationship between tectonic fractures and landslides. Environmental Geology, 48(6), 778-787.
Lee, S., & Min, K. (2001). Statistical analysis of landslide susceptibility at Yongin, Korea. Environmental geology, 40(9), 1095-1113.
Mohammady, M., Pourghasemi, H. R., & Pradhan, B. (2012). Landslide susceptibility mapping at Golestan Province, Iran: a comparison between frequency ratio, Dempster–Shafer, and weights-of-evidence models. Journal of Asian Earth Sciences, 61, 221-236.
Nefeslioglu, H. A., Sezer, E., Gokceoglu, C., Bozkir, A. S., & Duman, T. Y. (2010). Assessment of landslide susceptibility by decision trees in the metropolitan area of Istanbul, Turkey. Mathematical Problems in Engineering, 2010
Özşahin, E. (2014). Tekirdağ ilinde coğrafi bilgi sistemleri ve analitik hiyerarşi süreci kullanarak heyelan duyarlilik analizi. HUMANITAS-Uluslararası Sosyal Bilimler Dergisi, 2(3), 167-186.
Saaty, T. L., & Brandy, C. (2009). The encyclicon, volume 2: a dictionary of complex decisions using the analytic network process. Pittsburgh, Pennsylvania: RWS Publications.
Talaei, R. (2014). Landslide susceptibility zonation mapping using logistic regression and its validation in Hashtchin Region, northwest of Iran. Journal of the Geological Society of India, 84(1), 68-86.
Talaei, R. (2018). A Combined Model for Landslide Susceptibility, Hazard and Risk Assessment. AUT Journal of Civil Engineering, 2(1), 11-28.
Talaei, R., Ghayoumian, J., Akbarzadeh, E. A., & Shariat Jafari, M. (2004). Study on Effective Factor Causing Landslide in South West of Khalkhal Region.
Uromeihy, A., & Mahdavifar, M. R. (2000). Landslide hazard zonation of the Khorshrostam area, Iran. Bulletin of Engineering Geology and the Environment, 58(3), 207-213.
Van Westen, C. J., Seijmonsbergen, A. C., & Mantovani, F. (1999). Comparing landslide hazard maps. Natural hazards, 20(2-3), 137-158.
Wang, C., Esaki, T., Xie, M., & Qiu, C. (2006). Landslide and debris-flow hazard analysis and prediction using GIS in Minamata– Hougawachi area, Japan. Environmental Geology, 51(1), 91-102.
Yesilnacar, E., & Topal, T. (2005). Landslide susceptibility mapping: a comparison of logistic regression and neural networks methods in a medium scale study, Hendek region (Turkey). Engineering Geology, 79(3-4), 251-266.
Yilmaz, Işık. "A case study from Koyulhisar (Sivas-Turkey) for landslide susceptibility mapping by artificial neural networks." Bulletin of Engineering Geology and the Environment 68, no. 3 (2009): 297-306.
Zahedi, F. (1986). The analytic hierarchy process—a survey of the method and its applic.