Discontinuity controlled probabilistic slope failure risk maps of the Altindag (settlement) region in Turkey

The evaluation of potential rock slope problems using stereographic projection techniques known as kinematic analysis is one of the most important parts of a slope stability investigation to be carried out in jointed rock media. In conventional stereoprojection techniques for the assessment of possible rock slope failures, the peak orientations of joints together with the slope geometry and the friction angle of the weakness planes are used. Other possible joint orientations which may be encountered in the rock media are ignored, although they belong to the group of joint peak orientations. In this study, nearly vertical jointed andesites cropped out at the Altindag settlement region in Ankara were studied in order to evaluate the relevance of this ignored discontinuity orientation data on slope stability. As a result, probabilistic risk maps for planar, toppling and wedge failures were produced using the kinematic rules and digital elevation model of the study area. The comparison of the distribution of the actual failures in the area and the probabilistic risk maps prepared for the study area revealed that all of the identified failures are found to be located in the higher risk zones on the probabilistic risk maps.     

Landslide Susceptibility Zoning North of Yenice (NW Turkey) by Multivariate Statistical Techniques

Dramatic effects resulting from landslides on human life and economy of many nations are observed sometimes throughout the world. Landslide inventory and susceptibility mapping studies are accepted as the first stage of landslide hazard mitigation efforts. Generally, these landslide inventory studies include identification and location of landslides. The main benefit is to provide a basis for statistical susceptibility zoning studies. In the present study, a landslide susceptibility zoning near Yenice (NW Turkey) is carried out using the factor analysis approach. The study area is approximately 64 km² and 57 landslides were identified in this area. The area is covered completely by Ulus Formation that has a flysh-like character. Slope angle, elevation, slope aspect, land-use, weathering depth and water conditions were considered as the main conditioning factors while the heavy precipitation is the main trigger for landsliding. According to the results of factor analysis, the importance weights for slope angle, land-use, elevation, dip direction, water conditions and weathering depth were determined as 45.2%, 22.4%, 12.5%, 8.8%, 8.1% and 3.0% respectively. Also, using these weights and the membership values of each conditioning factor, the membership value for landslide susceptibility was introduced. In the study area, the lowest membership value for landslide susceptibility was calculated as 0.20. Consequently, combining all results, a landslide susceptibility map was obtained. Compared with the obtained map, a great majority of the landslides (86 %) identified in the field were found to be located in susceptible and highly susceptible zones.     

Dynamics of a complex mass movement triggered by heavy rainfall: a case study from NW Turkey

Following a period of heavy precipitation, a large and complex mass movement, namely the Dagkoy landslide, occurred in the West Black Sea Region of Turkey on May 21, 1998. This paper describes the conditioning factors of the landslide and interprets the mass transport processes in terms of a movement scenario. Geology, geomorphology and vegetation cover were considered as the conditioning factors of the failure. Observations showed that the gently sloping (about 10°) area is mostly covered by dense forest trees at the crown where the motion initiated. Significant intersection of the collapsed slope with dip of the local marls seems to have contributed to the formation and geometry of the landslide. The distance from the crown down to the toe of the landslide measured more than 600 m, with about 0.6 km³ total earth material displaced. The landslide has both a block sliding characteristics in the upper portions and a debris flow/soil flow component around the margins of the sliding blocks in the middle parts and at the toe. The proposed scenario for the landslide reveals that the movement was initiated near crown as a result of the excess water content in the marls at the end of 3 days of heavy rainfall. The early perturbations (transverse cracks, ridges, etc.) lasted for 6–7 h, after which the central part of the zone started to move as a soil flow in which very large intact blocks were transported. Even though the movement was very rapid (1.2 m/min), there was no loss of life. However, the movement destroyed 38 houses, one mosque and a considerable amount of farmland.     

A new approach to use AHP in landslide susceptibility mapping: a case study at Yenice (Karabuk, NW Turkey)

This study aimed to investigate the parameter effects in preparing landslide susceptibility maps with a data-driven approach and to adapt this approach to analytical hierarchy process (AHP). For this purpose, at the first stage, landslide inventory of an area located in the Western Black Sea region of Turkey covering approximately 567?km² was prepared, and a total of 101 landslides were mapped. In order to assess the landslide susceptibility, a total of 13 parameters were considered as the input parameters: slope, aspect, plan curvature, topographical elevation, vegetation cover index, land use, distance to drainage, distance to roads, distance to structural elements, distance to ridges, stream power index, sediment transport capacity index, and wetness index. AHP was selected as the major assessment methodology since the adapted approach and AHP work in data pairs. Adapted to AHP, a similarity relation?Cbased approach, namely landslide relation indicator (LRI) for parameter selection method, was also proposed. AHP and parametric effect analyses were performed by the proposed approach, and seven landslide susceptibility maps were produced. Among these maps, the best performance was gathered from the landslide susceptibility map produced by 9 parameter combinations using area under curve (AUC) approach. For this map, the AUC value was calculated as 0.797, while the others ranged between 0.686 and 0.771. According to this map, 38.3?% of the study area was classified as having very low, 8.5?% as low, 15.0?% as moderate, 20.3?% as high, and 17.9?% as very high landslide susceptibility, respectively. Based on the overall assessments, the proposed approach in this study was concluded as objective and applicable and yielded reasonable results.     

Two- and three-dimensional slope stability evaluation in a residential area: Denizkonak landslides in Cide (Kastamonu,NW Turkey)

Natural Hazards - In this study, it was aimed at evaluating the slope stability conditions in a residential area exposed to two landslides in the past by using two- and three-dimensional limit...     

Use of fuzzy relations to produce landslide susceptibility map of a landslide prone area (West Black Sea Region, Turkey)

Preparation of landslide susceptibility maps is important for engineering geologists and geomorphologists. However, due to complex nature of landslides, producing a reliable susceptibility map is not easy. For this reason, many procedures have been used to produce such maps. In this study, a new attempt is tried to produce landslide susceptibility map of a part of West Black Sea Region of Turkey. To obtain the fuzzy relations for producing the susceptibility map, a landslide inventory database is compiled by both field surveys and airphoto studies. A total of 266 landslides are identified in the study area, and dominant mode of failure is rotational slide while the other mode of failures are soil flow and shallow translational slide. The landslide inventory and the parameter maps are analyzed together using a computer program (FULLSA) developed in this study. The computer program utilizes the fuzzy relations and produces the landslide susceptibility map automatically. According to this map, 9.6% of the study area is classified as very high susceptibility, 10.3% as high susceptibility, 8.9% as moderate susceptibility, 27.5% as low susceptibility and 43.8% as very low susceptibility or nonsusceptible areas. The prediction performance of the susceptibility map is checked by considering actual landslides in the study area. For this purpose, strength of the relation (r_ij) and the root mean square error (RMSE) values are calculated as 0.867 and 0.284, respectively. These values show that the produced landslide susceptibility map in the present study has a sufficient reliability. It is believed that the approach employed in this study mainly prevents the subjectivity sourced from the parameter selection and provides a support to improve the landslide susceptibility mapping studies.     

Application of logistic regression and fuzzy operators to landslide susceptibility assessment in Azdavay (Kastamonu,Turkey)

Landslides and their assessments are of great importance since they damage properties, infrastructures, environment, lives and so on. Particularly, landslide inventory, susceptibility, and hazard or risk mapping have become important issues in the last few decades. Such maps provide useful information and can be produced by qualitative or quantitative methods. The work presented in this paper aimed to assess landslide susceptibility in a selected area, covering 570.625 km² in the Western Black Sea region of Turkey, by two quantitative methods. For this purpose, in the first stage, a detailed landslide inventory map was prepared by extensive field studies. A total of 96 landslides were mapped during these studies. To perform landslide susceptibility analyses, six input parameters such as topographical elevation, lithology, land use, slope, aspect and distance to streams were considered. Two quantitative methods, logistic regression and fuzzy approach, were used to assess landslide susceptibility in the selected area. For the fuzzy approach, the fuzzy and, or, algebraic product, algebraic sum and gamma operators were considered. At the final stage, 18 landslide susceptibility maps were produced by the logistic regression and fuzzy operators in a GIS (Geographic Information System) environment. Two performance indicators such as ROC (relative operating characteristics) and cosine amplitude method (r _ij ) were used to validate the final susceptibility maps. Based on the analyses, the landslide susceptibility map produced by the fuzzy gamma operator with a level of 0.975 showed the best performance. In addition, the maps produced by the logistic regression, fuzzy algebraic product and the higher levels of gamma operators showed more satisfactory results, while the fuzzy and, or, algebraic sum maps were not sufficient to provide reliable outputs.     

Application of Chebyshev theorem to data preparation in landslide susceptibility mapping studies:an example from Yenice(Karabük,Turkey) region

Landslide database construction is one of the most crucial stages of the landslide susceptibility mapping studies. Although there are many techniques for preparing landslide database in the literature, representative data selection from huge data sets is a challenging, and, to some extent, a subjective task. Thus, in order to produce reliable landslide susceptibility maps, data-driven, objective and representative database construction is a very important stage for these maps. This study mainly focuses on a landslide database construction task. In this study, it was aimed at building a representative landslide database extraction approach by using Chebyshev theorem to evaluate landslide susceptibility in a landslide prone area in the Western Black Sea region of Turkey. The study area was divided into two different parts such as training (Basin 1) and testing areas (Basin 2). A total of nine parameters such as topographical elevation, slope, aspect, planar and profile curvatures, stream power index, distance to drainage, normalized difference vegetation index and topographical wetness index were used in the study. Next, frequency distributions of the considered parameters in both landslide and nonlandslide areas were extracted using different sampling strategies, and a total of nine different landslide databases were obtained. Of these, eight databases were gathered by the methodology proposed by this study based on different standard deviations and algebraic multiplication of raster parameter maps. To evaluate landslide susceptibility, Artificial Neural Network method was used in the study area considering the different landslide and nonlandslide data. Finally, to assess the performances of the so-produced landslide susceptibility maps based on nine data sets, Area Under Curve (AUC) approach was implemented both in Basin 1 and Basin 2. The best performances (the greatest AUC values) were gathered by the landslide susceptibility map produced by two standard deviation database extracted by the Chebyshev theorem, as 0.873 and 0.761, respectively. Results revealed that the methodology proposed by this study is a powerful and objective approach in landslide susceptibility mapping.     

Fuzzified kinematic analysis of discontinuity-controlled rock slope instabilities

In this study, it is aimed to bring a different approach to kinematic analyses of discontinuity-controlled rock slope instabilities. For this purpose, the data of a detailed discontinuity survey carried out in Ankara, the capital city of Turkey, were updated and reevaluated. Serious discontinuity-controlled instability events were observed in the andesites covering large areas with dense population in the city. Instead of analyzing the effects of the planes belonging only to the major discontinuity sets on the stereographic projection net, all discontinuities were taken into consideration, and kinematic analyses were carried out for planar, wedge, and toppling type failures on pixel basis of the Digital Elevation Model (DEM) of the study area. By doing so, it could be possible to compensate for the deficiency created by neglecting the planes in the lower concentration zones of the stereographic projection. A computer program named FUDIKA (Fuzzified Digital Kinematic Analyses) was written to perform modular kinematic analyses and fuzzy operations, having four modules and operating in three stages. First, Potential Instability Index (PII) was introduced to define instability potential of the rock slopes based on the number of possible instability events for each failure type. Next, the PII values were normalized and fuzzified to obtain PII map of the area. It was seen that when tested on previously occurred instabilities in the area, the PII values obtained through the methodology proposed in the study showed quite a high performance.     

Assessment of landslide susceptibility for a landslide-prone area (north of Yenice, NW Turkey) by fuzzy approach

. Regional landslide susceptibility assessments pose complex problems. To solve these problems, numerous approaches, such as statistical analysis, geotechnical engineering approach, geomorphologic approach and fuzzy logic, have been employed. However, all the available methods for regional landslide susceptibility assessments have some uncertainties due to a lack of knowledge and variability. Minimizing these uncertainties provides realistic approaches. Use of the fuzzy logic approach to produce a landslide susceptibility map of a landslide-prone area in NW Turkey is the main purpose of the present study. For this purpose, the study includes five main stages, these being the preparation of a landslide inventory of the study area, the application of factor analysis, the extraction of fuzzy if-then rules, the use of a geographical information system, and the control of the reliability of the resulting landslide susceptibility map. Slope angle, slope aspect, land use, weathering depth, water conditions and topographical elevation were considered as landslide conditioning factors for the study area. A total of 23 if-then rules was extracted from the field data. Employing these rules, fuzzified index maps representing each parameter were obtained. Finally, combining these maps, the landslide susceptibility map of the area was prepared. When compared with the landslide susceptibility map, the landslides identified in the area were found to be located in the very high- and high-susceptibility zones. As far as the performance of the fuzzy approach for processing is concerned, the images appear to be quite satisfactory, the zones determined on the map being zones of relative susceptibility.