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The paper proposes a methodology for quantitative landslide risk assessment for regional-scale analysis. Each component of risk, i.e., hazard, vulnerability, and consequence analysis, is quantitatively assessed. The developed landslide risk assessment methodology is tested in Kumluca watershed, in Bartın, Turkey. Geographic information systems and remote sensing techniques are used to create landslide factor maps, to obtain susceptibility maps, hazard maps, elements at risk, and risk maps. Susceptibility maps are obtained by using a logistic regression model while adopting a grid-based mapping unit. In addition to spatial probability of occurrence of damaging events, landslide hazard calculation requires the determination of the temporal probability. Precipitation triggers the majority of landslides in the study region. The critical rainfall thresholds were estimated by using antecedent rainfalls and landslide occurrence dates based on Gumble Distribution approach. The elements at risk are extracted from existing digital cadastral databases and the vulnerabilities are obtained by adopting some generalization approaches. To conclude, quantitative risk maps were produced on a continuous scale where numerical values indicate the distribution of risk including the annual probability of expected losses in TL per pixel and the annual probability of life loss per pixel for property and life, respectively. For the considered case study, it is found that the annual probability of property loss is the highest for the provincial highway and the provincial road. The property loss map highlights that the annual expected loss to power network is medium. The annual probability of life loss map illustrates that the region surrounded by Kumluca town, Kızıllar, and Zafer villages have medium and high annual expected loss of population values, respectively. [ABSTRACT FROM AUTHOR]

In this study, landslide risk assessment for Izmir city (west Turkey) was carried out, and the environmental effects of landslides on further urban development were evaluated using geographical information systems and remote sensing techniques. For this purpose, two different data groups, namely conditioning and triggering data, were produced. With the help of conditioning data such as lithology, slope gradient, slope aspect, distance from roads, distance from faults and distance from drainage lines, a landslide susceptibility model was constructed by using logistic regression modelling approach. The accuracy assessment of the susceptibility map was carried out by the area under curvature (AUC) approach, and a 0.810 AUC value was obtained. This value shows that the map obtained is successful. Due to the fact that the study area is located in an active seismic region, earthquake data were considered as primary triggering factor contributing to landslide occurrence. In addition to this, precipitation data were also taken into account as a secondary triggering factor. Considering the susceptibility data and triggering factors, a landslide hazard index was obtained. Furthermore, using the Aster data, a land-cover map was produced with an overall kappa value of 0.94. From this map, settlement areas were extracted, and these extracted data were assessed as elements at risk in the study area. Next, a vulnerability index was created by using these data. Finally, the hazard index and the vulnerability index were combined, and a landslide risk map for Izmir city was obtained. Based on this final risk map, it was observed that especially south and north parts of the Izmir Bay, where urbanization is dense, are threatened to future landsliding. This result can be used for preliminary land use planning by local governmental authorities. [ABSTRACT FROM AUTHOR]

The northeast part of Turkey is prone to landslides because of the climatic conditions, as well as geologic and geomorphologic characteristics of the region. Especially, frequent landslides in the Rize province often result in significant damage to people and property. Therefore, in order to mitigate the damage from landslides and help the planners in selecting suitable locations for implementing development projects, especially in large areas, it is necessary to scientifically assess susceptible areas. In this study, the frequency ratio method and the analytical hierarchy process (AHP) were used to produce susceptibility maps. Especially, AHP gives best results because of allowing better structuring of various components, including both objective and subjective aspects and comparing them by a logical and thorough method, which involves a matrix-based pairwise comparison of the contribution of different factors for landslide. For this purpose, lithology, slope angle, slope aspect, land cover, distance to stream, drainage density, and distance to road were considered as landslide causal factors for the study area. The processing of multi-geodata sets was carried out in a raster GIS environment. Lithology was derived from the geological database and additional field studies; slope angle, slope aspect, distance to stream, distance to road and drainage density were invented from digital elevation models; land cover was produced from remote sensing imagery. In the end of study, the results of the analysis were verified using actual landslide location data. The validation results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations. [ABSTRACT FROM AUTHOR]