On the Effect of Dem Quality for Landslide Susceptibility Mapping

Abstract

Abstract. Generating precise and up-to-date landslide susceptibility maps (LSMs) in landslide-prone areas is important to identify hazard potential in the future. The data quality and the method selection affect the accuracy of the LSMs. In this context, the accuracy and precision of the digital elevation models (DEMs) used as input are among the most important performance elements. Therefore, the influence of DEM accuracy and spatial resolution in producing LSMs was investigated here. A high accuracy DEM with 5 m grid spacing produced from aerial photographs and the EU-DEM v1.1 freely accessible from Copernicus Land Monitoring Service with 25 m spatial resolution were used for producing two different LSMs using the Random Forest (RF) method in this study. The RF method has proven success for this purpose. A total of eight conditioning factors, which include topographical and geological features, was used as model input. The landslide inventory was derived with the help of aerial stereo images with 20 cm and 30 cm ground sampling distances. The performances of the LSMs were assessed with receiver operating characteristics (ROC) area under curve (AUC) values. In addition, the results were compared with visual inspection. The results show that although the AUC values obtained from the aerial DEM (0.95) and EU-DEM v1.1 (0.93) were comparable; based on the visual assessments, the LSM obtained from the higher resolution DEM was found more successful in detecting the landslides and thus exhibited better prediction performance.

Frequency Ratio Assessment for Landslides Triggered by 6 February 2023 Kahramanmaras Turkiye Earthquakes Between Golbasi and Erkenek

“…As the aerial photogrammetric digital elevation model (DEM) of the area was not yet provided, EU-DEM v1.1 (EEA) was used to generate the conditioning factors: altitude, slope, topographic wetness index, aspect, profile and plan curvature. The efficiency of using EU-DEM v1.1 was proven in previous landslide susceptibility assessment studies (e.g., Karakas et al, 2022). The land use land cover (LULC) obtained from ESA WorldCover (Zanaga, 2022), lithology and faults obtained from the General Directorate of Mineral Research and Exploration (MTA) (Akbas et al 2016) were also considered as input factors.…”

“…The Frequency Ratio (FR) method is one of the commonly utilized statistical analysis techniques in the generation of landslide susceptibility maps (Nefeslioglu et al, 2012;Karakas et al, 2022). The FR has proven to be an effective tool for assessing landslide susceptibility by considering the spatial relationship between landslide events and various conditioning factors.…”