Arzev bölgesi (Cezayir’in kuzeybatısı) için bilgi değeri ve frekans oranı kullanılarak heyelan duyarlılık haritalaması

Jeolojik afetler, Cezayir’in kuzeybatısındaki Arzev bölgesinin (Oran vilayeti) gelişmesinin önündekien önemli engellerden birini teşkil etmektedir. Heyelanlar, çalışma alanında ve özellikle engebelibölgelerde en yaygın doğal olaylardan biri olarak kabul edilir. Bu problemin sonuçlarını en azaindirmek ve azaltmak için, şev duraysızlığına maruz kalan farklı bölgelerin haritalanmasına ilişkinön çalışmaların yapılması gerekmektedir. Bu çalışmanın temel amacı, Arzev bölgesi için istatistikselmodeller ve CBS (Coğrafi Bilgi Sistemleri) teknikleri ile heyelan duyarlılık haritasının yapılmasıdır.Bu hedefe ulaşmak için analitik bir yaklaşım uygulanmıştır. İlk olarak, geçmişte yapılmış envanterharitaları, uydu görüntüleri, hava fotoğrafları ve saha araştırmaları kullanılarak bir heyelan envanterharitası hazırlanmıştır. İkinci olarak, heyelan duyarlılığını değerlendirmek için eğim derecesi, bakı,litoloji, arazi kullanımı, akarsulara uzaklık, yola uzaklık ve yükseklik gibi yedi adet hazırlayıcıfaktör kullanılmıştır. Üçüncü olarak, hazırlayıcı faktörlerinin her bir sınıfı için ağırlık değeri, CBSişlevlerine dayanan Frekans Oranı (FR) ve Bilgi Değeri (IV) modelleri kullanılarak belirlenmiştir.Sonuç olarak, Heyelan Duyarlılık Haritaları (LSM’ler), küresel Heyelan Duyarlılık İndekslerinin(LSI’ler) sınıflandırma işlemi ile beş sınıfa ayrılmıştır. Son olarak, deney doğrulaması için, FRve IV modelleri ile elde edilen LSM’ler, hem Alıcı İşletim Karakteristikleri (ROC) hem de KökHücre Alanı İndeksi (SCAI) modelleri kullanılarak heyelan envanter haritasıyla karşılaştırılarakteyit edilmiştir. Eğri altındaki alan (AUC) sonuçları, LSM için IV yönteminin (% 89.03) FRyönteminden (% 85.57) daha iyi performansı olduğunu göstermektedir. Ayrıca, SCAI kullanılarakyapılan doğrulama sonuçları, IV modelinin FR modelinden daha hassas olduğunu da doğrulamıştır.Bu çalışmada kullanılan modeller, çalışma alanının heyelan duyarlılığı sorununu çözme yeteneğinesahiptir. Üretilen duyarlılık haritaları gelecekteki arazi kullanım planlaması için kullanılabilir veheyelanlara bağlı riskin mekansal dağılımını çözmek için güçlü bir araç olarak düşünülebilir.

Landslide susceptibility mapping using information value and frequency ratio for the Arzew sector (North-Western of Algeria)

Geological hazards present one of the most important constraints for the development of the Arzew sector (Oran province), North Western of Algeria. Landslides are considered us one of the most common phenomena in the study area and especially in the hilly area. For minimizing and reducing the consequences of this problem, it is necessary to carry out preliminary studies on the cartography of the different zones exposed to the slope instability phenomena. The main objective of this study is to perform the landslide susceptibility mapping by statistical models and GIS techniques for the Arzew area. To achieve this goal, an analytical approach was carried out. Firstly, a landslide inventory map was prepared using previous inventory maps, satellite images, aerial photos and field surveys. Secondly seven conditioning factors such as slope degree, aspect, lithology, land use, distance to the streams, distance to the road and altitude were exploited to assess landslide susceptibility. Thirdly, the weight value for each class of the conditioning factors was determined using Frequency Ratio (FR) and Information Value (IV) models based in GIS functionalities. Consequently, Landslide Susceptibility Maps (LSMs) were produced by the classification process of the global Landslide Susceptibility Indexes (LSIs) into five classes. Finally, for experiment verification, the LSMs obtained with the FR and IV models were confirmed comparing LSMs with landslide inventory map using both the Receiver Operating Characteristics (ROC) and the Seed Cell Area Index (SCAI) models. The area under curve (AUC) results, demonstrate that the IV method more performance (89.03%) for LSM than FR method (85.57%). Furthermore, the validation results using SCAI also confirmed that the IV model was more accurate than FR model. The models employed in this study are capable to resolve the issue of the landslide susceptibility of the study area. The produced susceptibility maps can be used for future land use planning and can be considered as a powerful tool to resolve the spatial distribution of the risk associated to landslides.

___

  • Achour, Y., Boumezbeur, A., Hadji, R., Chouabbi, A., Cavaleiro, V., Bendaoud, E. A. 2017. Landslide susceptibility mapping using analytic hierarchy process and information value methods along a highway road section in Constantine, Algeria. Arabian Journal of Geosciences 10:194.
  • Aghdam, I., N., Varzandeh, M.H.M., Pradhan, B. 2016. Landslide susceptibility mapping using an ensemble statistical index (Wi) and adaptive neuro-fuzzy inference system (ANFIS) model at Alborz Mountains (Iran). Environmental Earth Sciences 75:553.
  • 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. Environmental Geology 54:1127-1143.
  • Bai, S., Lü, G., Wang, J., Zhou, P., Ding, L. 2011 GIS-based rare events logistic regression for landslidesusceptibility mapping of Lianyungang, China. Environmental Earth Sciences 62:139-149.
  • Ballabio, C., Sterlacchini, S. 2012. Support vector machines for landslide susceptibility mapping: the Staffora River Basin case study, Italy. Mathematical geosciences 44:47-70
  • Benabdellah, M. 2010. Mis en évidence des phénomènes contrôlant le littoral oranais (de la Calère a la pointe de Canastel) : étape fondamentale pour une cartographie des risques géologiques. Mémoire de magister, Université d’Oran, 258p.
  • Benaissa, A., Cordary, D., Gioraud, A. 1989. Les mouvements de terrain dans la zone urbaine de Constantine (Algérie). Bulletin of the International Association of Engineering Geology-Bulletin de l’Association Internationale de Géologie de l’Ingénieur 40:85-90
  • Beneder. 2011. Carte d’occupation du sol wilaya d’Oran notice explicative. Bureau national d’études pour le développement rural, Rapport inédite, 13p.
  • Bourenane, H., Bouhadad, Y., Guettouche, MS., Braham, M. 2015. GIS-based landslide susceptibility zonation using bivariate statistical and expert approaches in the city of Constantine (Northeast Algeria). Bulletin of Engineering Geology and the Environment 74:337-355.
  • Bui, D.T., Lofman, O., Revhaug, I., Dick, O. 2011. Landslide susceptibility analysis in the Hoa Binh province of Vietnam using statistical index and logistic regression. Natural Hazards 59:1413.
  • Chen, W., Li, W., Chai, H., Hou, E., Li, X., Ding, X. 2016. GIS-based landslide susceptibility mapping using analytical hierarchy process (AHP) and certainty factor (CF) models for the Baozhong region of Baoji City, China. Environmental Earth Sciences 75:63.
  • Chen, W., Pourghasemi, H. R., Zhao, Z. 2017. A GIS-based comparative study of Dempster-Shafer, logistic regression and artificial neural network models for landslide susceptibility mapping. Geocarto International 32:367-385.
  • Ciszak, R. 1993. Evolution géodynamique de la chaîne tellienne en Oranie (Algérie occidentale) pendant le Paléozoïque et le Mésozoïque vol 20. Laboratoire de géologie sédimentaire et paléontologie, Thèse de doctorat, Université Paul Sabatier, 513p.
  • Conforti, M., Pascale, S., Robustelli, G., Sdao, F. 2014. Evaluation of prediction capability of the artificial neural networks for mapping landslide susceptibility in the Turbolo River catchment (northern Calabria, Italy). Catena 113:236-250.
  • Corominas, J., Van Westen, C., Frattini, P., Cascini, L., Malet, J. P., Fotopoulou, S., Catani, F., Van DenEeckhaut, M., Mavrouli, O., Agliardi, F., Pitilakis, K., Winter, M.G., Pastor, M., Ferlisi, S., Tofani, V., Herva´s, J., Smith, J.T. 2014. Recommendations for the quantitative analysis of landslide risk. Bulletin of Engineering Geology and the Environment 73, 209–263.
  • Cruden, D.M, Varnes, D.J. 1996. Landslide Types and Processes, Special Report, Transportation Research Board, National Academy of Sciences, 247: 36-75.
  • Cui, K., Lu, D., Li, W. 2016. Comparison of landslide susceptibility mapping based on statistical index, certainty factors, weights of evidence and evidential belief function models. Geocarto International:1-21.
  • Dahoua, L., Yakovitch, S., Hadji, R. 2017.GIS-based technic for roadside-slope stability assessment: an bivariate approach for A1 East-West highway, North Algeria. Mining Science 24.
  • Djerbal, L., Khoudi, I., Alimrina, N., Melbouci, B., Bahar, R. 2017 Assessment and mapping of earthquakeinduced landslides in Tigzirt City, Algeria. Natural Hazards:1-21.
  • Djerbal, L., Melbouci, B. 2013. Contribution to the mapping of the landslide of Aïn El Hammam (Algeria). In: Advanced Materials Research,. Trans Tech Publ, pp 332-336.
  • Ercanoğlu, M., Kasmer, O., Temiz, N. 2008. Adaptation and comparison of expert opinion to analytical hierarchy process for landslide susceptibility mapping. Bulletin of Engineering Geology and the Environment 67:565-578.
  • Fell, R., Corominas, J., Bonnard, C., Cascini, L., Leroi, E., Savage, WZ. 2008 .Guidelines for landslide susceptibility, hazard and risk zoning for land use planning. Engineering Geology 102:85-98.
  • Fenet, B. 1975. Recherches sur l’alpinisation de la bordure septentrionale du Bouclier africain à partir de l’étude d’un élément de l’orogène nord-maghrébin : les monts du Djebel Tessala et les massifs du littoral oranais, Thèse de doctorat, Université de Nice, 310p.
  • Ghosh, K., Bandyopadhyay, S., De, S.K. 2017. A Comparative Evaluation of Weight-Rating and Analytical Hierarchical (AHP) for Landslide Susceptibility Mapping in Dhalai District, Tripura. In: Environment and Earth Observation. Springer, pp 175-193.
  • Gomes, A., Gaspar, J., Goulart, C., Queiroz, G. 2005. Evaluation of landslide susceptibility of Sete Cidades Volcano (S. Miguel Island, Azores). Natural Hazards and Earth System Science 5:251- 257.
  • Gorsevski, P.V., Gessler, P.E., Boll, J., Elliot, W.J., Foltz, R.B. 2006a. Spatially and temporally distributed modeling of landslide susceptibility. Geomorphology 80:178-198.
  • Gorsevski, P.V., Gessler, P.E., Foltz, R.B., Elliot, W.J. 2006b. Spatial prediction of landslide hazard using logistic regression and ROC analysis. Transactions in GIS 10:395-415.
  • Gorsevski, P.V., Jankowski, P., Gessler, P.E. 2006c. An heuristic approach for mapping landslide hazard by integrating fuzzy logic with analytic hierarchy process. Control and Cybernetics 35:121-146.
  • Gourinard, Y. 1952a. Carte géologique détaillée de l’Algérie. Feuille Arzew (127) 2ème idition, Serv. Carte Géol. Alger, Algérie.
  • Gourinard, Y. 1952b. Carte géologique détaillée de l’Algérie. Feuille Oran (159) 2ème idition, Serv. Carte Géol, Alger, Algérie.
  • Guemache, M.A., Chatelain, J.L., Machane, D., Benahmed, S., Djadia, L. 2011. Failure of landslide stabilization measures: the Sidi Rached viaduct case (Constantine, Algeria). Journal of African Earth Sciences 59:349-358.
  • Guzzetti, F., Reichenbach, P., Cardinali, M., Galli, M., Ardizzone, F. 2005. Landslide hazard assessment in the Staffora basin, northern Italian Apennines. Geomorphology 72:272-299.
  • Hadji, R., Boumazbeur, A., Limani, Y., Baghem, M., el Madjid Chouabi, A., Demdoum, A. 2013.
  • Geologic, topographic and climatic controls in landslide hazard assessment using GIS modeling: a case study of Souk Ahras region, NE Algeria. Quaternary International 302:224-237.
  • Hadji, R., Limani, Y., Demdoum, A. 2014. Using multivariate approach and GIS applications to predict slope instability hazard case study of Machrouha municipality, NE Algeria. In: Information and Communication Technologies for Disaster Management (ICT-DM), 1st International Conference on, 2014. IEEE, pp 1-10.
  • Hadji, R., Rais, K., Gadri, L., Chouabi, A., Hamed, Y. 2017. Slope failure characteristics and slope movement susceptibility assessment using GIS in a medium scale: a case study from Ouled Driss and Machroha municipalities, Northeast Algeria. Arabian Journal for Science and Engineering 42:281-300.
  • Intarawichian, N., Dasananda, S. 2010. Analytical Hierarchy Process For Landslide Susceptibility Mapping In Lower Mae Chaem Watershed, Northern Thailand. Suranaree Journal of Science & Technology 17.
  • Lee, S., Talib, J.A. 2005. Probabilistic landslide susceptibility and factor effect analysis Environmental geology 47:982-990
  • Mahdadi, F., Boumezbeur, A., Hadji, R., Kanungo, D.P., Zahri, F. 2018. GIS-based landslide susceptibility assessment using statistical models: a case study from Souk Ahras province, NE Algeria. Arabian Journal of Geosciences 11:476
  • Özdemir, A., Altural, T. 2013. A comparative study of frequency ratio, weights of evidence and logistic regression methods for landslide susceptibility mapping: Sultan Mountains, SW Turkey. Journal of Asian Earth Sciences 64:180-197.
  • Peng, L., Niu, R., Huang, B., Wu, X., Zhao, Y., Ye, R. 2014. Landslide susceptibility mapping based on rough set theory and support vector machines: A case of the Three Gorges area, China. Geomorphology 204:287-301.
  • Perrodon, A. 1957. Etude géologique des bassins néogènes sublittoraux de l’Algérie occidentale. Thèse de doctorat, Université d’ Oran, 301p.
  • Pourghasemi, H., Moradi, H., Aghda, S.F. 2013. Landslide susceptibility mapping by binary logistic regression, analytical hierarchy process, and statistical index models and assessment of their performances. Natural Hazards 69:749-779.
  • 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 18:471- 493.
  • Pradhan, B., Jebur, M.N., Abdullahi, S. 2017. Spatial Prediction of Landslides Along Jalan Kota in Bandar Seri Begawan (Brunei) Using Airborne LiDAR Data and Support Vector Machine. Laser Scanning Applications in Landslide Assessment. Springer, pp 167-178.
  • Raja, NB., Çiçek, I., Türkoğlu, N., Aydın, O., Kawasaki, A. 2017. Landslide susceptibility mapping of the Sera River Basin using logistic regression model. Natural Hazards 85:1323-1346.
  • Regmi, N.R., Giardino, J.R., Vitek, J.D. 2010. Modeling susceptibility to landslides using the weight of evidence approach: Western Colorado, USA. Geomorphology 115:172-187.
  • Sezer, E.A., Pradhan, B., Gökçeoğlu, C. 2011. Manifestation of an adaptive neuro-fuzzy model on landslide susceptibility mapping: Klang valley. Malaysia Expert Systems with Applications 38:8208-8219.
  • Süzen, M., Doyuran, V. 2004. A comparison of the GIS based landslide susceptibility assessment methods: multivariate versus bivariate. Environmental geology 45:665-679.
  • Thiery, Y. 2007. Susceptibilité du Bassin de Barcelonnette (Alpes du Sud, France) aux’mouvements de versant’: cartographie morphodynamique, analyse spatiale et modélisation probabiliste. Thèse de doctorat, Université de Caen, 445p.
  • Thomas, G. 1985. Géodynamique d’un bassin intramontagneux Le bassin du Bas Chélif occidental (Algérie) durant le Mio-PlioQuaternaire. Thèse de doctorat, Université de Pau, 594p.
  • Van Westen, C. J. 1993. Application of geographic information systems to landslide hazard zonation. ITC Publication, Vol.15. International Institute for Aerospace Survey and Earth Sciences, Enschede 245pp.
  • Yalçın, A., Reis, S., Aydınoğlu, A., Yomralıoğlu, 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.
  • Yeşilnacar, 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 79:251-266.
  • Yılmaz, I. 2009. A case study from Koyulhisar (SivasTurkey) for landslide susceptibility mapping by artificial neural networks Bulletin of Engineering Geology and the Environment 68:297-306.
  • Yılmaz, I. 2010. Comparison of landslide susceptibility mapping methodologies for Koyulhisar, Turkey: conditional probability, logistic regression, artificial neural networks, and support vector machine. Environmental Earth Sciences 61:821- 836.
  • Yin, K., Yan, T. 1988. Statistical prediction model for slope instability of metamorphosed rocks. In: Proceedings of the 5th International Symposium on Landslides. sl]:[sn], pp 1269-1272.
  • Youssef, A.M., Al-Kathery, M., Pradhan, B. 2015. Landslide susceptibility mapping at Al-Hasher area, Jizan (Saudi Arabia) using GIS-based frequency ratio and index of entropy models. Geosciences Journal 19:113-134.
Maden Tetkik ve Arama Dergisi-Cover
  • ISSN: 0026-4563
  • Yayın Aralığı: Yılda 3 Sayı
  • Başlangıç: 1950
  • Yayıncı: Cahit DÖNMEZ
Sayıdaki Diğer Makaleler

Oligosen yaşlı Datça-Kale-Acı Göl havzasında çökelme ile eş yaşlı tektonizma izleri, Batı Anadolu

Gürol SEYİTOĞLU, Nizamettin KAZANCI, Veysel IŞIK, Gülşen ELMAS

Arzev bölgesi (Cezayir’in kuzeybatısı) için bilgi değeri ve frekans oranı kullanılarak heyelan duyarlılık haritalaması

Roukh ZINE EL ABIDINE, Nadji ABDELMANSOUR

İstanbul - Yenikapı’daki Holosen yaşlı istifin sedimentolojik özellikleri ve çökelme ortamları

M. Namık YALÇIN, Oya ALGAN, Meltem SEZERER BULUT

Doğu Akdeniz’in gaz hidrat potansiyeli

Şükrü MEREY, Sotirios Nik. LONGINOS

İstatistik ve kokriging yöntemlerini kullanarak sondaj ve IP-Rs verilerinin kombinasyonu ile mineral kaynaklarının tahmin edilmesi

Kamran MOSTAFAEI, Hamidreza RAMAZI

Babaeski-Lüleburgaz-Muratlı-Çorlu bölgesindeki Paleojen-Neojen istiflerinin paleoortamsal özellikleri ve ostrakod incelemesi (Güneydoğu Trakya, Türkiye)

Ümit ŞAFAK

Nummulites sireli Deveciler (N. sireli Alan türünün Junior Homonimi) Nummulites ercumenti nom. nov. olarak yeniden isimlendirilmesi

Ali DEVECİLER

Beni Mellal Atlas (Fas)’ın karstik masifinde aeromanyetik prospeksiyon ve uzaktan algılama verilerini kullanarak jeolojik yapıların haritalanması

Ikram BOUTIRAME, Ahmed BOUKDIR, Ahmed AKHSSAS, Ahmed MANAR

Doğu Karadeniz Bölümü (Ordu, Rize, Artvin-KD Türkiye) jeotermal sahalarının nadir toprak elementleri ve itriyum jeokimyası

Arzu FIRAT ERSOY, Fatma GÜLTEKİN, Esra HATİPOĞLU TEMİZEL

Rezidüel gravite alanı verilerinden 2 boyutlu doğrusal ve doğrusal olmayan ters çözüm modelini kullanarak bir tuz domunun simülasyonu

Soheyl POURREZA, Farnush HAJIZADEH