A Combined Method for Preparation of Landslide Susceptibility Map in Izmir (Türkiye)

Kıncal C., Kayhan H.

applied sciences, cilt.12, ss.1-28, 2022 (SCI-Expanded)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 12
  • Basım Tarihi: 2022
  • Dergi Adı: applied sciences
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Agricultural & Environmental Science Database, Applied Science & Technology Source, Communication Abstracts, INSPEC, Metadex, Directory of Open Access Journals, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1-28
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Landslide susceptibility maps (LSMs) have been used frequently by researchers for many

years in prediction of the occurrence of landslides. Since many landslides have occurred there in

the past, Izmir, which is the third largest city of Türkiye, was selected for landslide susceptibility

assessment using geographical information systems (GIS) and remote sensing (RS) techniques. The

aim of this study is to create a better landslide susceptibility map (LSM) for the Izmir metropolitan

area and its surroundings by minimizing the shortcomings of some of the commonly used methods.

For this purpose, four different LSMs were prepared using the logistic regression (LR), analytical

hierarchy process (AHP), frequency ratio (FR) and index of entropy (IOE) methods with susceptibility

classes ranging from extremely low to extremely high. These four maps were then overlaid. The

highest susceptibility class was chosen for each pixel to form a combined landslide susceptibility map

(CLSM). The final CLSM is a thematic map presenting landslide susceptibility using five different

classes. The geo-environmental factors selected for use in this analysis were slope angle, slope aspect,

lithology, slope curvature, elevation, density of discontinuity, stream power index (SPI), land use

and distance from stream. Finally, the areas under receiver-operating characteristic (ROC) curves

were employed to compare the predictive capability of the five models used. Overall, the Combined

Method (CM) (AUC = 0.887) performed very well for landslide susceptibility assessment. Out of all

the models, the IOE model (AUC = 0.841) had a slightly lower predictive capability than the CM

model, and AHP (AUC = 0.816) was better than FR (AUC = 0.738) and LR (AUC = 0.727). It was

observed that, compared to rural areas, residential areas of Izmir city are particularly susceptible to

landslides.