Landslide Susceptibility Assessment in Constantine Region (NE Algeria) By Means of Statistical Models

Abstract

The purpose of the present study was to compare the prediction performances of three statistical methods, namely, information value (IV), weight of evidence (WoE) and frequency ratio (FR), for landslide susceptibility mapping (LSM) at the east of Constantine region. A detailed landslide inventory of the study area with a total of 81 landslide locations was compiled from aerial photographs, satellite images and field surveys. This landslide inventory was randomly split into a testing dataset (70%) for training the models, and the remaining (30%) was used for validation purpose. Nine landslide-related factors such as slope gradient, slope aspect, elevation, distance to streams, lithology, distance to lineaments, precipitation, Normalized Difference Vegetation Index (NDVI) and stream density were used in the landslide susceptibility analyses. The inventory was adopted to analyse the spatial relationship between these landslide factors and landslide occurrences. Based on IV, WoE and FR approaches, three landslide susceptibility zonation maps were categorized, namely, “very high, high, moderate, low, and very low”. The results were compared and validated by computing area under Road the receiver operating characteristic (ROC) curve (AUC). From the statistics, it is noted that prediction scores of the FR, IV and WoE models are relatively similar with 73.32%, 73.95% and 79.07%, respectively. However, the map, obtained using the WoE technique, was experienced to be more suitable for the study area. Based on the results, the produced LSM can serve as a reference for planning and decision-making regarding the general use of the land.

Multivariate statistical-based approach to the physical-chemical behavior of shallow groundwater in a semiarid dry climate: The case study of the Gadaïne-Ain Yaghout plain NE Algeria

“…In order to know the reliability of our chemical results, the ionic balance calculated for all analyzed water samples is estimated at about 5% for all samples. All mapping of the various studied parameters is performed using the GIS technique [42]- [46]. The statistical processing was carried out using the Statistics and Phreeqc-2 (V 2.10) program [47], [48].…”

Slope failure characterization: A joint multi-geophysical and geotechnical analysis, case study of Babor Mountains range, NE Algeria

“…The direct approach requires field and laboratory data as well as a safety factor calculation using one of the well-known stability analysis techniques such as the limit equilibrium and finite elements methods [10]. Their disadvantage is that the information is provided in a specific location and assessment of the spatial distribution of safety factors is not economically efficient, since a large number of samples and tests are required in the affected area [11], [12]. These techniques would allow landslides to be assessed at some scattered locations, giving an idea on the stability state, but an additional geophysical study would be an ideal tool to deal with this difficulty [13].…”

GIS‐based susceptibility assessment of the occurrence of gully headcuts and pipe collapses in a semi‐arid environment: Golestan Province, NE Iran

“…Recently, susceptibility modelling approaches related to single processes have been established to a considerable extent (Kappes et al, ; Karim, Hadji, & Hamed, ; Manchar, Benabbas, Hadji, Bouaicha, & Grecu, ). However, neither a terminology nor a uniform conceptual approach have been established to analyse two or more hazards jointly.…”