Coğrafi Bilgi Sistemleri ile Suşehri (Sivas) Heyelan Duyarlılık Analizi

Yıl 2018, Cilt: 8 Sayı: 1, 96 - 112, 31.01.2018

Gökhan Demir

https://doi.org/10.17714/gumusfenbil.299987

Cited By: 3

Öz

17 Mart 2005 tarihinde meydana gelen can ve mal
kayıplarına yol açan Kuzulu (Koyulhisar) heyelanı Kuzey Anadolu Fay Zonuna
(KAFZ) yakın bir bölgede meydana gelmiştir. KAFZ aktif bir fay zonudur ve
bölgedeki heyelanları tetiktediği düşünülmektedir. Bu etkinin araştırılması ve
heyelan zararlarını en aza indirmek amacıyla; heyelan olayının önceden tahmini
veya olasılığa dayalı yöntemlerle heyelana duyarlı alanların belirlenmesi
gerekmektedir. Bu amaçla ilk olarak inceleme alanına ait Maden Tetkik ve Arama
Genel Müdürlüğü Heyelan envanter verileri, hava fotoğrafları ve arazi
çalışmaları kullanılarak heyelan envanter haritası üretilmiştir. Bu
heyelanların %65’i analizde ve %35’i doğrulamada kullanmak üzere rastgele
olarak iki gruba ayrılmıştır. Arazi çalışmaları sonucu heyelan oluşumunda
etkili olduğu düşünülen, litoloji, topoğrafik yükseklik, yamaç eğim değeri,
yamaç eğim yönü, akarsuya yakınlık, yola yakınlık ve faya yakınlık
parametreleri duyarlılık analizinde kullanılmıştır. Analizde iki değişkenli
istatistiksel yöntem altyapısı esasına dayandırılmış Frekans Oranı yöntemi
kullanılarak, KAFZ’na yakın Sivas ili Suşehri ilçesinin heyelan duyarlılık
haritası oluşturulmuştur.  Duyarlılık
haritası, çok az duyarlıdan çok yüksek duyarlılık sınıfına olmak koşuluyla beş
değişik bölgeye ayırt edilmiştir.  Duyarlılık
haritasının performansını test etmek ve başarısını değerlendirmek için harita
modelde kullanılmayan heyelan lokasyonları ile karşılaştırılmış ve Eğri
Altındaki Alan (EAA)  değeri 0.672 olarak
belirlenmiştir. Bu sonuç ile heyelan duyarlılık değerlendirmesinin
kullanılabilir olduğu görülmüştür. Üretilen harita ile bölgede heyelan olayının
meydana gelme olasılığının yüksek olduğu arazilerde yapılacak planlamalarda
heyelan olasılığı da dikkate alınarak uygulanacak mühendislik önlemleri ile can
ve mal kaybının olmaması sağlanabilir.

Anahtar Kelimeler

Frekans oranı, Heyelan Duyarlılık, CBS (Coğrafi Bilgi Sistemleri), Kuzey Anadolu Fayı

Landslide Susceptibility Analysis by using GIS for Suşehri (Sivas)

Öz

The Kuzulu (Koyulhisar) landslide occurred near the North Anatolian
Fault Zone (NAFZ) on 17 March 2005 resulted loss of life and property. NAFZ is
an active fault and is thought to trigger landslides in the region. In order to
investigate this effect and minimize landslide damage; prediction of landslide
or landslides susceptible areas need to be identified by likelihood methods.
Firstly a inventory map for landslide were produced using inventory map of
General Directory of Mineral Research, field surveys and aerial photographs.
These landslides are randomly divided into two groups that 65% were used in
analysis and 35% used for verification. Lithology, aspect,  slope gradient,  topographical elevation, distance to stream,
roads and faults were decided to used in analysis as contributing factors after
field studies. Landslide susceptibility map (LSM) of the Suşehri province of
Sivas near the NAFZ was created by the Frequency Ratio method. LSM was
separated into five classes from very low to very high. For validation of the
map and evaluate its success, it was compared with the landslide which was not
used in modeling. Consequently the area under curve (AUC) value was determined
as 0.622. AUC value showed that the LSM was useable. With LSM, it is possible
to avoid the loss of life and property by the engineering measures to be
applied considering the possibility of landslide in the plans to be made in the
areas where the possibility of landslide event in the region is high.

Anahtar Kelimeler

GIS, Frequency ratio(FR), Landslide Susceptibility, North Anatolian Fault Zone

Kaynakça

• Akgün A, Kincal C, Pradhan ., 2012. Application of remote sensing data and GIS for landslide risk assessment as an environmental threat to Izmir city (west Turkey), Env mon and ass, 184: 9, 5453-5470.
• Akgün A, Sezer EA, Nefeslioglu HA, Gökçeoğlu C, Pradhan B., 2011. An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm, Comp Geo, 38, 1. 23-34.
• Akgün A., Erkan O., 2016. Landslide susceptibility mapping by geographical information system-based multivariate statistical and deterministic models: in an artificial reservoir area at Northern Turkey, Arab J Geosci, 9: 165, DOI 10.1007/s12517-015-2142-7
• Akgün, A., Dağ, S., Bulut, F., 2008. Landslide susceptibility mapping for a landslide-prone area (Findikli, NE of Turkey) by likelihood–frequency ratio and weighted linear combination models, Environ. Geol. 54, 1127–1143.
• Atkinson PM, Massari R., 2011. Autologistic modelling of susceptibility to landsliding in the central apennines, Italy, Geomorphology.doi:10.1016/j.geomorph.2011.02.001.
• Baykal, F., 1952. Recherchesgeologiques la region de Kelkit-Şiran (Nord-East de L’Anatolie): Rev.Fac.Sc.Üniv.İst., Ser. B.T.17, fas, 4, 325-340.
• Bednarik M, Yilmaz I, Marschalko M., 2012. Landslide hazard and risk assessment: a case study from the Hlohovec-Sared landslide area in south-west Slovakia, Nat Hazards 64(1), 547–575.
• Bergougnan, H., 1975. Presence de troisunitescharrie'es a la borduresuddesPontides dans le Haut-Kelkit. Ages et sensdemises en place: C.R. Ac. Sci., 280, 2199-2201, Paris.
• Bergougnan, H., 1982, Remnants of a Pre-Late Jurassic ocean in northernTurkey: Fragments of Permian - TriassicPaleo-Tethys? Discussion. GeologicalSociety of AmericaBulletin, 93, 929- 932.
• Bijukchhen SM, Kayastha P, Dhital MR., 2013. A comparative evaluation of heuristic and bivariate statistical modelling for landslide susceptibility mappings in Ghurmi–Dhad Khola, east Nepal, Arab J Geosci, 6, 2727–2743.
• Bourenane H., Guettouche M. S., Bouhadad Y., Braham M.,2016. Landslide hazard mapping in the Constantine city, Northeast Algeria using frequency ratio, weighting factor, logistic regression, weights of evidence, and analytical hierarchy process methods, Arab J Geosci, 9: 154, DOI 10.1007/s12517-015-2222-8.
• Brenning, A., 2005. Spatial prediction models for landslide hazards: review, comparison and evaluation, Natural Hazards and Earth System Sciences, 5(6), 853–862.
• Bui DT, Pradhan B, Lofman O, Revhaug I, Dick OB., 2011. Landslide susceptibility mapping at Hoa Binh province (Vietnam) using an adaptive neuro fuzzy inference system and GIS, J.Comp Geosci, 45, 199-211.
• Clerici A, Perego S, Tellini C and 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), EnvGeo, 50, 941-961.
• Dağ, S., 2007, Çayeli (Rize) ve Çevresinin İstatistiksel Yöntemlerle Heyelan Duyarlılık Analizi. Doktora Tezi, Karadeniz Teknik Üniversitesi Fen Bilimleri Enstitüsü. Trabzon, 241s.
• Dağ, S., Bulut, F., 2012. Coğrafi Bilgi Sistemleri Tabanlı Heyelan Duyarlılık Haritalarının Hazırlanmasına Bir Örnek: Çayeli (Rize, KD Türkiye) Jeoloji Mühendisliği Dergisi,36, 1.
• Dağ, S., Bulut, F., Alemdağ, S., Kaya, A., 2011. Heyelan Duyarlılık Haritalarının Üretilmesinde Kullanılan Yöntem ve Parametrelere İlişkin Genel Bir Değerlendirme. Gümüşhane Üniversitesi Fen Bilimleri Enstitüsü Dergisi,1, 2, 151-176.
• Dahal RK, Hasegawa S, Nonomura A, Yamanaka M, Takuro M, Nishino K.,2008. GIS-based weights-ofevidence modelling of rainfall-induced landslides in small catchments for landslide susceptibility mapping, Environ Geol, 54:311-324.
• Dai, F.C., Lee, C.F., Zhang, X.H., 2001. GIS-based geo-environmental evaluation for urban land-use planning: a case study, Engineering Geology, 61, 257–271.
• Das, I., Sahoo, S., Van Westen, C., Stein, A. and Hack, R., 2010. Landslide susceptibility assessment using logistic regression and its comparison with a rock mass classification system, along a road section in the northern Himalayas (India), Geomorphology, 114, 4, 627–637.
• Demir G, Aytekin M, Akgün A, İkizler SB, Tatar O., 2013. A comparison of landslide susceptibility mapping of the eastern part of the North Anatolian Fault Zone (Turkey) by likelihood-frequency ratio and analytic hierarchy process methods, Nat Haz, 65, 1481–1506.
• Demir G, Aytekin M, Akgün A., 2015. Landslide susceptibility mapping by frequency ratio and logistic regression methods: an example from Niksar–Resadiye (Tokat, Turkey), Arab J Geosci, DOI 10.1007/s12517-014-1332-z.
• Demir, G., 2011. Kuzey Anadolu Fayı Üzerinde Niksar-Suşehri Arasındaki Alanın Cbs Tabanlı
• Devkota KC, Regmi AD, Pourghasemi HR, Yoshida K, Pradhan B, Ryu IC, Dhital MR, Althuwaynee OF., 2013. Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling-Narayanghat road section in Nepal Himalaya, Nat Hazards, 65:135–165.
• Dewitte O, Chung C, Cornet Y, Daoudi M, Demoulin A., 2010. Combining spatial data in landslide reactivation susceptibility mapping: a likelihood ratio-based approach in W Belgium, Geomorphology, 122, 153–166.
• Ercanoglu M, Kasmer O, Temiz N., 2008. Adaptation and comparison of expert opinion to analytical hierarchy process for landslide susceptibility mapping, Bull Eng Geol Environ, 67:565–578.
• Erener A., Mutlu A., Düzgün H.Ş.,, 2016. A comparative study for landslide susceptibility mapping using GIS-based multi-criteria decision analysis (MCDA), logistic regression (LR) and association rule mining (ARM), Engineering Geology, 203, 45–55.
• Ghosh S, Carranza EJM., 2010. Spatial analysis of mutual fault/fracture and slope controls on rocksliding in Darjeeling Himalaya, India, Geomorphology, 122:1–24.
• Gorsevski PV, Jankowski P., 2010. An optimized solution of multi-criteria evaluation analysis of landslide susceptibility using fuzzy sets and Kalman fitler, Comput Geosci, 36:1005–1020.
• Gökçeoğlu C, Sönmez H, Nefeslioğlu HA, Duman TY and Can T., 2005. The 17 March 2005 Kuzulu landslide (Sivas, Turkey) and landslide susceptibility map of its near vicinity, Eng Geol 81, 65-83.
• Gökçeoğlu C., Nefeslioğlu A.H., Türer D., Akgün A., Ayaş Z., Temimhan M., 2014. Determination Of Coastal Border Line: An Integrated Approach For A Part Of Antalya Coast (Turkey), Arab J Geosci, 1-10.
• Gurocak, Z., Alemdag, S., Bostanci, H.T., ve Gokceoglu, C., 2017. Discontinuity controlled slope failure zoning for a granitoidcomplex: A fuzzy approach.Rock Mechanics and Engineering, Volume 5: Surfaceand Underground Projects, CRC Press Taylor & Francis Group, eBook ISBN: 978-1-317-48188-1, Pages 1–25.
• Gürsoy, H., 1995, The main tectonic structures of the Kelkit (Gümüşhane) region and their relationship with the regional tectonic structures, Edited by A. Erler, T. Ercan, E. Bingöl, S Örçen, Proceedings of the International Symposium of the Geology of the Black SeaRegion, p. 292-299, 7-11 September 1992, Ankara
• Kavzoğlu T, Sahin EK, Çölkesen I., 2013. Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression, Landslides, doi:10.1007/s10346- 013-0391-7.
• Lee S, Pradhan B., 2007. Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models, Landslides, 4:33–41.
• Lee S., 2005. Application of Logistic Regression Model and Its Validation for Landslide Susceptibility Mapping Using GIS and Remote Sensing Data, Int. J. Remote Sensing 26, 1477-1491.
• Lee, S., TuDan, N., 2005. Probabilistic landslide susceptibility mapping in the Lai Chau province of Vietnam: focus on the relationship bet- ween tectonic fractures and landslides, Environmental Geology, 48, 778–787.
• Nandi A, Shakoor A., 2009. A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses, Eng Geol, 110:11–20.
• Nebert, K., 1961. Kelkit çayı ve Kızılırmak giriş sahalarının jeolojik yapısı, M.T.A. Enst. Yay. Ankara.
• Nefeslioglu H, Duman TY, Durmaz S., 2008b. Landslide susceptibility mapping for a part of tectonic Kelkit Valley (Eastern Black Sea region of turkey), Geomorphology, 94(3–4):401–418.
• Nefeslioglu H, Gokceoglu C, Sonmez H., 2008a. An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps, Eng Geol, 97(3/4):171–191.
• Nourani V, Pradhan B, Ghaffari H, Sharifi S S., 2014. Landslide susceptibility mapping at Zonouz Plain, Iran using genetic programming and comparison with frequency ratio, logistic regression, and artificial neural network models, Nat Hazards, 71:523–547 DOI 10.1007/s11069-013-0932-3.
• Oh HJ, Lee S, Chotikasathien W, Kim CH, Kwon JH., 2009. Predictive landslide susceptibility mapping using spatial information in the Pechabun area of Thailand, Environ Geol, 57:641–651.
• Oh H-J, Pradhan B., 2011. Application of a neuro-fuzzymodel to landslide-susceptibility mapping for shallow landslides in a tropical hilly area, Comp.Geosc., 37(9):1264-1276.
• Ozdemir A., 2009. Landslide susceptibility mapping of vicinity of Yaka Landslide (Gelendost, Turkey) using conditional probability approach in GIS, Environ Geol, 57:1675–1686.
• Pistocchi, A., Luzi, L., Napolitano, P., 2002. The use of predictive modeling techniques for optimal exploitation of spatial databases: a case study in landslide hazard mapping with expert system-like methods, Environmental Geology, 41, 765–775.
• Polat, A. (2011). Kuzey Anadolu Fay Zonu’nun Suşehri Havzası’ndaki Bölümünün Neotektonik ve Paleosismolojik Özellikleri. C.Ü. Fen Bilimleri Enstitüsü, Doktora Tezi, 256 s.
• Pourghasemi HR, Goli Jirandeh A, Pradhan B, Xu C, Gokceoglu C., 2013. Landslide susceptibility mapping using support vector machine and GIS, J Earth Syst Sci, 122(2):349–369.
• Pourghasemi HR, Pradhan B, Gokceoglu C, Deylami Moezzi K., 2012. A comparative assessment of prediction capabilities of Dempster-Shafer and Weights-of-evidence models in landslide susceptibility mapping using GIS, Geomat Natl Hazards Risk, doi:10.1080/19475705.2012.662915.
• Pourghasemi HR, Pradhan B, Gokceoglu C, Mohammadi M, Moradi HR., 2012. Application of weights-of evidence and certainty factor models and their comparison in landslide susceptibility mapping at Haraz watershed, Iran, Arab J Geosci., doi:10.1007/s12517-012-0532-7.
• Pradhan B and Youssef AM., 2010. Manifestation of remote sensing data and GIS on landslide hazard analysis using spatial-based statistical models, Arab J Geosci, 3:319–326.
• Pradhan B, Singh RP, Buchroithner MF., 2006. Estimation of stress and its use in evaluation of landslide prone regions using remote sensing data, Adv Space Res, 37:698–709.
• Pradhan B., 2010a. Landslide susceptibility mapping of a catchment area using frequency ratio, fuzzy logic and multivariate logistic regression approaches, J Ind Soc Rem Sens, 38(2):301–320.
• Pradhan B., 2010b. Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia, Advncs Space Res, 45(10):1244–1256.
• Pradhan B., 2011. Manifestation of an advanced fuzzy logic model coupled with Geo-information techniques to landslide susceptibility mapping and their comparison with logistic regression modeling, Environmental and Ecological Statistics, 18: 3. 471-493.
• Pradhan B., 2013. A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS, Computers & Geosciences, 51, 350-365.
• Regmi AD, Yoshida K, Pradhan B, Pourghasemi HR, Khumamoto T, Akgun A., 2013. Application of frequency ratio, statistical index and weights-of-evidence models, and their comparison in landslide susceptibility mapping in Central Nepal Himalaya, Arab J Geosci, doi:10.1007/s12517-012-0807-z.
• Saha AK, Gupta RP, Sarkar I, Arora MK, Csaplovics E., 2005a. An approach for GIS—based statistical landslide susceptibility zonation-with a case study in the Himalayas, Landslides , 2:61–69.
• Saha AK, Gupta RP, Sarkar I, Arora MK, Csaplovics E., 2005b. GIS-based landslide hazard zonation in the Bhagirathi (Ganga) Valley, Int J Remote Sens, 23(2):357–369.
• Shahabi H, Khezri S, Ahmad B B, Hashim M., 2014. Landslide susceptibility mapping at central Zab basin, Iran: A comparison between analytical hierarchy process, frequency ratio and logistic regression models, Catena, 115, 55–70.
• Son J., Suh J., Park H.D., 2016. GIS-based landslide susceptibility assessment in Seoul, South Korea, applying the radius of influence to frequency ratio analysis, Environ Earth Sci, 75:310, DOI 10.1007/s12665-015-5149-1.
• Sterlacchini S, Ballabio C, Blahut J, Masetti M, Sorichetta A., 2011. Spatial agreement of predicted patterns in landslide susceptibility maps, Geomorphology, 125:51–61.
• Şengör, A.M.C,, Görür N, Şaroğlu, F. (1985). Strike slip faulting and related basin formation in zones of tectonic escape: Turkey as a case study. In Strike-slip Deformation, Basin Formation, and Sedimentation, Soc. Econ. Paleontol. Miner. Spec. Publ. 37 (in honor of J.C. Crowell), ed. KT Biddle, N Christie-Blick, pp. 227–64
• Şengör, A.M.C. (1979). The North Anatolian Transform Fault: it sage, offsetand tectonic significance. J. Geol. Soc. London, 136:269–82.
• Tatar, O., Gürsoy, H., Altunel, E., Akyüz, H.S., Topal, T., Şahin, M., Kavak, K.Ş., Çakır, Z.,Koçbulut, F., Sezen, T.F., Mesci, B.L., Dikmen, Ü., Türk, T., Poyraz, F., Hastaoğlu, K.Ö.,Zabcı, C., Karabacak, V., Akın, M., Akpınar, Z., Polat, A., Gürsoy, Ö., Demir, G., Ayazlı, İ.E., Yalçıner, Ç, Yavaşoğlu, H., Karaman, H. ve Erden, T. (2009). Aktif Fay Zonları ve Doğal Afetler: Kuzey Anadolu Fay Zonu Üzerinde Kelkit Vadisi Boyunca Yer Alan Yerleşim Alanlarının Doğal Afet Risk Analizi ve Afet Bilgi Sisteminin Oluşturulması, Cilt 1 (Neotektonik, Paleosismoloji, GPS, Heyelan Duyarlılık ve Radar Interferometri), DPT Proje No 2006K-120220, 868 s
• Tatar, O., Türk, T., Gürsoy, H., Hastaoğlu, K., Ayazlı, E., Poyraz, E., Gürsoy, Ö., Zabcı, C., Demir, G., Dikmen, Ü., Akın, M., Mesci, L., Koçbulut, F., Kavak, K.Ş., Sezen T.F. ve Polat, A., 2007. Kelkit vadisi afet bilgi sistemi (kabis) altyapisinin oluşturulmasi, Ulusal coğrafi bilgi sistemleri kongresi, K.T.Ü, Trabzon, s.102.
• Tien Bui D, Pradhan B, Lofman O, Revhaug I, Dick OB., 2012. Spatial prediction of landslide hazards in Hoa Binh province (Vietnam) : a comparative assessment of the efficacy of evidential belief functions and fuzzy logic models, Catena, 96, 28-40.
• Van Den Eeckhaut M, Marre A, Poesen J., 2010. Comparison of two landslide susceptibility assessments in the Champagne–Ardenne region (France), Geomorphology, 115:141–155.
• Van Den Eeckhaut M, Reichenbach P, Guzzetti F, Rossi M, Poesen J., 2009. Combined landslide inventory and susceptibility assessment based on different mapping units: an example from the Flemish Ardennes, Belgium, Nat Hazard Earth Sys, 9:507–521.
• Van Den Eeckhaut, M., Vanwalleghem, T., Poesen, J., Govers, G., Verstraeten, G., Vandekerckhove, L., 2006. Prediction of landslide susceptibility using rare events logistic regression: A case-study in the Flemish Ardennes (Belgium), Geomorphology, 76, 392–410.
• Van Westen CJ, Rengers N, Soeters R., 2003. Use of geomorphological information in indirect landslide susceptibility assessment, Nat Hazards, 30:399–419.
• Van Westen, C.J., 1993. Remote Sensing and Geographic Information Systems for Geological Hazard Mitigation, ITC-Journal, 4, 393-399.
• Wang L. J., Guo M., Sawada K., Lin J., Zhang J., 2016. A comparative study of landslide susceptibility maps using logistic regression, frequency ratio, decision tree, weights of evidence and artificial neural network, Geosciences Journal, Vol. 20, No. 1, p. 117-136, DOI 10.1007/s12303-015-0026-1.
• Wang, L.-J., Sawada, K., Moriguchi, S., 2013. Landslide susceptibility analysis with logistic regression model based on FCM sampling strategy.” , Comput. Geosci. 57, 81–92.
• Wu Y., Li W., Liu P., Bai H., Wang Q., He J., Liu Y., Sun S., 2016. Application of analytic hierarchy process model for landslide susceptibility mapping in the Gangu County, Gansu Province, China, Environ Earth Sci, 75:422, DOI 10.1007/s12665-015-5194-9
• Xu C, Xu X, 2013. Controlling parameter analyses and hazard mapping for earthquake-triggered landslides: an example from a square region in Beichuan County, Sichuan Province, China, Arab J Geosci, 6:3827–3839.
• Yalcin, A., Reis, S., Aydinoglu, A., Yomralioglu, T., 2011. A GIS-based comparative study of frequency ratio, analytical hierarchy process, bivariate statistics and logistics regression methods for landslide susceptibility mapping in Trabzon, NE Turkey, Catena, 85, 274–287.
• Yeon Y-K, Han J-G, Ryu KH., 2010. Landslide susceptibility mapping in Inje, Korea, using a decision tree, Eng Geol, 116:274–283.
• Yetkil, V., 2009, Gölova (Sivas) Güneydoğusunda Kuzey Anadolu Fay Zonu’nun Neotektonik Özellikleri,” Yüksek Lisans Tezi, Cumhuriyet Üniverstesi, Fen Bilimleri Enstitüsü, Sivas, 74 s.
• Yılmaz, A., 1983, Tokat (Dumanlıdağı) ile Sivas (Çeltekdağı) dolaylarının temel jeoloji özellikleri ve ofiyolitli karışığın konumu: MTA. Dergisi 99-100, 1-18.
• Yılmaz, A., 1985, Yukarı Kelkit Çayı ile Munzur Dağları arasının temel jeolojik özellikleri ve yapısal evrimi. Türkiye Jeoloji Kurumu Bülteni, 28, 79-92.
• Yılmaz, A., Yılmaz, H., 2010. Kuzey Anadolu Fayı’ nın Suşehri ile Gölova (Agvanis) arasındaki bölgede atımı. Cumhuriyet Yerbilimleri Dergisi, 27 (2), 89-96.
• Yilmaz I., 2009. Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: a case study from Kat landslides (Tokat-Turkey), Comput Geosci, 35:1125–1138.
• Zhao C., Chen W., Wang Q., Wu Y., and Yang B. 2015. A comparative study of statistical index and certainty factor models in landslide susceptibility mapping: a case study for the Shangzhou District, Shaanxi Province, China, Arab J Geosci, 8:9079–9088, DOI 10.1007/s12517-015-1891-7.