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İki ve Çok Değişkenli İstatistik ve Sezgisel Tabanlı Heyelan Duyarlılık Modellerinin Karşılaştırılması: Ayvalık (Balıkesir, Kuzeybatı Türkiye) Örneği

Comparison of Bivariate and Multivariate Statistical and Heuristic-Based Landslide Susceptibility Models: an Example From Ayvalık (Balıkesir, Northwestern Turkey)

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Abstract (2. Language): 
Landslides are one of the most destructive natural hazards which frequently occur after earthquakes in our country and in the world. From engineering point of view, prediction of landsliding before its occurence has a great importance to mitigate the landslide related damages, and determination of landslide prone areas by the methods, based on probability, has spread out both in our country and in the world in the last two decades. In this study, a comparison of the most common landslide susceptibility mapping methods, namely bivariate, multivariate statistical and heuristic methods, were carried out. For this purpose, Ayvalık (Balıkesir) and its near vicinity were selected as study area, and in total 45 landslides were mapped. Morphologic, geologic and land-use data were produced in Geographical Information Systems (GIS) by using available topographical and relevant thematic maps. In the area, slope gradient and aspect, lithology, weathering conditions of the rocks, stream power index (SPI), topographical wetness index (TWI), distance from drainage, density of structural features, land-cover and vegetation cover density were considered as the parameters causing the landslides. All of the parameters were standardized in a common scale by using fuzzy membership functions. Then, the contribution of each of these parameters for the landslide occurrence were investigated by likelihood ratio, logistic regression and analytical hierarchy methods, and the weight values of the parameters were calculated. Considering the weight values determined by each method, landslide susceptibility maps were produced, and the performances of the produced maps were tested by comparing landslide locations using Area Under Curvature (AUC) approach. Based on this, the AUC values were determined to be 0.76, 0.77 and 0.89 for likelihood ratio, logistic regression and analytical hierarchy models, respectively. Accorrding to these results, analytical hierarcy model was considered to be the best landslide susceptibility method for the study area.
Abstract (Original Language): 
Heyelanlar, ülkemizde ve dünyada depremlerden sonra en fazla sıklıkla meydana gelen ve en çok zarar verici potansiyele sahip doğal afetlerden birisidir. Mühendislik açısından, heyelan zararlarının en aza indirilmesi amacıyla, heyelan olayının önceden tahmin edilmesi büyük önem taşımakta olup, olasılığa dayalı yöntemlerle heyelana duyarlı alanların belirlenmesi, özellikle son yirmi yılda, gerek dünyada gerekse ülkemizde oldukça yaygınlaşmıştır. Bu çalışma kapsamında, heyelan duyarlılık haritalarının hazırlanmasında en fazla kullanılan yöntemlerden iki ve çok değişkenli istatistik yöntemler ile sezgisel yöntemin karşılaştırması yapılmıştır. Amaca yönelik olarak, Ayvalık ilçesi (Balıkesir) ve yakın çevresi inceleme alanı olarak seçilmiş ve toplam 45 heyelan haritalanmıştır. Morfolojik, jeolojik ve arazi kullanımı verileri, Coğrafi Bilgi Sistemleri (CBS) kapsamında mevcut topoğrafik ve ilgili tematik haritalar kullanılarak üretilmiştir. Çalışma alanında, heyelana neden olan parametreler olarak; yamaç eğimi ve yönelimi, litoloji, kayaların ayrışma durumu, akarsu gücü indeksi (AGİ), topoğrafik nemlilik indeksi (TNİ), drenaj ağından uzaklık, yapısal unsurların yoğunluğu, arazi ve bitki örtüsü yoğunluğu dikkate alınmıştır. Bu heyelan parametreleri, bulanık üyelik fonksiyonları yardımıyla ortak bir ölçekte standartlaştırılmıştır. Daha sonra, her bir parametrenin heyelan oluşumuna katkısı; benzerlik oranı, mantıksal regresyon ve analitik hiyerarşi yöntemleri kullanılarak incelenmiş ve bu parametrelerin ağırlık değerleri hesaplanmıştır. Her bir yöntemle belirlenen ağırlık değerleri dikkate alınarak heyelan duyarlılık haritaları üretilmiş, üretilen haritaların performansları, mevcut heyelan lokasyonları ile karşılaştırılarak Eğri Altındaki Alan (EAA) yaklaşımıyla sınanmıştır. Buna göre, EAA değerleri sırasıyla benzerlik oranı yöntemi için 0.76, mantıksal regresyon için 0.77 ve analitik hiyerarşi yöntemi için 0.89 olarak belirlenmiştir. Bu sonuçlara göre inceleme alanı için en başarılı heyelan duyarlılık değerlendirmesinin, analitik hiyerarşi yöntemi ile olduğu görülmüştür.
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