Ebrahim Karimi SANGCHİNİ, Mohammad Reza NOWJAVAN, Abdolhossein ARAMİ

Landslide susceptibility mapping using logistic statistical regression in Babaheydar Watershed, Chaharmahal Va Bakhtiari Province, Iran

Toprak kaymaları, dağlık bölgelerdeki en zarar verici doğal felaketler arasında yer almaktadır . Her yıl,dünyanın dört bir yanında yüzlerce insan toprak kayması neticesinde ölüyor. Ayrıca, bu olayların yerel ve globalekonomi üzerinde de büyük etkileri bulunmaktadır. Bu çalışmada, toprak kayması tehlikesine sahip bölgeleri tespitetmek üzere lojistik regresyon kullanılarak Baba Haydar Havzasında toprak kayması tehlikesi haritası çıkartılmıştır.İlk olarak, havadan çekilmiş fotoğraf yorumları ve saha incelemeleri kullanılarak toprak kayması envanter haritasıhazırlanmıştır. Bir sonraki adımda rakım, eğim yüzdesi, eğim açısı, litoloji, fay hatlarına olan mesafe, nehirler,yerleşim yerleri ve yollar, arazi kullanımı ve yağış miktarı olmak üzere toprak kaymasına neden olabilecek on adetfaktör, çalışma bölgesinde toprak kaymasında etkin faktörler olarak seçilmiştir. Ardından, Coğrafi Bilgi Sisteminde(GIS) lojistik regresyon modeli kullanılarak toprak kayması hassasiyeti haritası oluşturulmuştur. Modeldeğerlendirmesi için ROC ve Pseudo -R2 endeksleri kullanılmıştır. Sonuçlar, lojistik regresyon modelinin , 0.876lıkROC değeri ile birlikte Baba Haydar Havzasında toprak kayması hassasiyet haritasının yüksek bir tahmin doğruluğusağladığını göstermiştir. Ayrıca sonuçlar, havza bölgelerinin yaklaşık %44ünün yüksek ve son derece tehlikelisınıflarda yer aldığını ortaya çıkartmıştır. Sonuç olarak elde edilen toprak kayması hassasiyeti haritaları, uygun havzayönetimi uygulamalarında ve bölgenin sürdürülebilir bir şekilde geliştirilmesinde faydalı olabilir .

İran ın Çaharmahal ve Bahtiyari Bölgesi ndeyer alan Baba Haydar Havzası nda lojistik regresyon kullanılarak heyelan hassasiyeti haritasının çıkartılması

Landslides are amongst the most damaging natural hazards in mountainous regions. Every year, hundredsof people all over the world lose their lives in landslides; furthermore, there are large impacts on the local and globaleconomy from these events. In this stu dy, landslide hazard zonation in Babaheydar watershed using logisticregression was conducted to determine landslide hazard areas. At first, the landslide inventory map was preparedusing aerial photograph interpretations and field surveys. The next step, ten landslide conditioning factors such asaltitude, slope percentage, slope aspect, lithology, distance from faults, rivers, settlement and roads, land use, andprecipitation were chosen as effective factors on landsliding in the study area. Subsequently, landslide susceptibilitymap was constructed using the logistic regression model in Geographic Information System (GIS). The ROC andPseudo -R2 indexes were used for model assessment. Results showed that the logistic regression model providedslightly high prediction accuracy of landslide susceptibility maps in the Babaheydar Watershed with ROC equal to0.876. Furthermore, the results revealed that about 44% of the watershed areas were located in high and very highhazard classes. The resultant landslide su sceptibility maps can be useful in appropriate watershed managementpractices and for sustainable development in the region .

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