Landslide susceptibility mapping of vicinity of Yaka Landslide (Gelendost, Turkey) using conditional probability approach in GIS

Özdemir, Adnan

doi:10.1007/s00254-008-1449-z

Cited by 50 publications

(21 citation statements)

References 16 publications

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“…In this regard, there have been studies on landslide susceptibility evaluation using GIS, and many of these studies have applied probabilistic models such as frequency ratio, weight of evidence etc. (Bednarik and Pauditš 2010;Lee et al 2004a;Lee and Min 2001;Lee and Pradhan 2006b;Mousavi et al 2009;Oh et al 2009;Ozdemir 2009;Pirasteh et al 2009;Pradhan and Youssef 2009;Regmi et al 2010;Yilmaz 2010). One of the statistical models available, the logistic regression model, has also been applied to landslide susceptibility mapping (Akgun and Bulut 2009;Bai et al 2010a, b;Chauhan et al 2010;Das et al 2010;Kincal et al 2009;Lee 2005Lee , 2007aNandi and Shakoor 2010;Oh et al 2009;Pradhan and Lee 2010a, b).…”

Section: Introductionmentioning

confidence: 95%

Landslide susceptibility mapping on Panaon Island, Philippines using a geographic information system

Lee

2010

Environ Earth Sci

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For landslide susceptibility mapping, this study applied, verified and compared the Bayesian probability model, the weights-of-evidence to Panaon Island, Philippines, using a geographic information system. Landslide locations were identified in the study area from the interpretation of aerial photographs and field surveys, and a spatial database was extracted from SRTM (Shuttle Radar Topographic Mission) DEM (Digital Elevation Model) imagery, aerial photograph, topographic map, and geological map. The factors that influence landslide occurrence, such as slope, aspect, curvature, topographic wetness index and stream power index of topography, were calculated from SRTM imagery. Distance from drainage was extracted from topographic database. Lithology and distance from fault were extracted and calculated from geological database. Terrain mapping unit was classified from aerial photographs. The spatial association between the factors and the landslides was calculated as the contrast values, W ? and W -using the weights-of-evidence model. Tests of conditional independence were performed for the selection of the factors, allowing the large number of combinations of factors to be analyzed. For each factor rating, the contrast values, W ? and W -were overlaid for landslide susceptibility mapping. The results of the analysis showed that contrast rating (78.60%) for each factor's multiclass had better accuracy of 5.90% than combinations of factor assigned to binary class with W ? and W -(72.70%).

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Section: Introductionmentioning

confidence: 95%

Landslide susceptibility mapping on Panaon Island, Philippines using a geographic information system

Lee

2010

Environ Earth Sci

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“…Recently, there have been studies on landslide hazard evaluation using GIS, and many of these studies have applied probabilistic models (Dahal et al 2008;Lee and Min 2001;Lee and Pradhan 2006;Oh et al 2009;Ozdemir 2009;Regmi et al 2010;Yilmaz 2009;2010;Zhou et al 2002). One of the statistical models available, the logistic regression models, has also been applied to landslide hazard mapping (Akgün and Bulut 2007;Bai et al 2010a, b;Das et al 2010;Lee 2005Lee , 2007bNandi and Shakoor 2010;Lee 2009a, 2010a), as has the geotechnical model and the safety factor model (Gorsevski et al 2006;Legorreta Paulin and Bursik 2009;Ray and De Smedt 2009;Shou et al 2009).…”

Section: Introductionmentioning

confidence: 97%

Cross-application used to validate landslide susceptibility maps using a probabilistic model from Korea

Lee

2010

Environ Earth Sci

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A study of landslides in Youngin, Janghung and Boeun, Korea, using the geographic information system (GIS) validates a spatial probabilistic model for landslide susceptibility analysis. Locations were identified from aerial photographs, satellite images and field surveys. Topography, soil-type, forest-cover and land-cover maps were constructed from spatial data sets. Landslide occurrence is influenced by 13 factors, evidence for which was extracted from the database with the frequency ratio of each factor computed. Landslide susceptibility maps use frequency ratios derived not only from data for each area but also ratios, one from the probabilistic model, calculated from the other two areas (nine maps in all) as a cross-check of method validity. For validation, analytical results were compared in each study area with actual landslide locations: Boeun based on its frequency ratio showed the best accuracy (82.49%) whereas Janghung based on the Boeun frequency ratio showed the worst (69.53%).

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“…The landslide susceptibility map is based on the distribution of past landslides, slope steepness, type of soil/bedrock, structure, hydrology and other pertinent data (Nandi and Shakoor 2009). Many different methods and techniques for evaluating landslide susceptibility have been proposed and tested (Akgun et al 2008;Atkinson and Massari 2011;Brenning 2005;Clerici et al 2006;Dahal et al 2008;Dewitte et al 2010;Ercanoglu et al 2008;Ghosh and Carranza 2010;Gorsevski and Jankowski 2010;Jaiswal et al 2010;Lee 2005;Lee and Dan 2005;Pradhan 2006, 2007;Nefeslioglu et al 2008;Oh et al 2009;Oh and Pradhan 2011;Ozdemir 2009;Pirasteh et al 2009;Pistocchi et al 2002;Pradhan et al 2006Pradhan et al , 2010aPradhan and Youssef 2010;Rossi et al 2010;Saha et al 2005a, b;Sezer et al 2011;Sterlacchini et al 2011;van Den Eeckhaut et al 2009van Westen 2004;Yeon et al 2010;Yilmaz 2009Yilmaz , 2010Youssef et al 2009;Zhou et al 2002). General overviews of research into landslide susceptibility can be found in the work of Leroi (1996), Aleotti and Chowdhury (1999), Guzzetti et al (1999), Dai et al (2001), …”

Section: Introductionmentioning

confidence: 99%

Landslide susceptibility mapping using Bayesian approach in the Sultan Mountains (Akşehir, Turkey)

Özdemir

2011

Nat Hazards

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Landslides cause heavy damage to property and infrastructure, in addition to being responsible for the loss of human lives in many parts of the Turkey. The paper presents GIS-based spatial data analysis for landslide susceptibility mapping in the regions of the Sultan Mountains, West of Akşehir, and central part of Turkey. Landslides occur frequently in the area and seriously affect local living conditions. Therefore, spatial analysis of landslide susceptibility in the Sultan Mountains is important. The relationships between landslide distributions with the 19 landslide affecting parameters were analysed using a Bayesian model. In the study area, 90 landslides were observed. The landslides were randomly subdivided into 80 training landslides and 10 test landslides. A landslide susceptibility map was produced by using the training landslides. The test landslides were used in the accuracy control of the produced landslide susceptibility map. Approximately 9% of the study area was classified as high susceptibility zone. Medium, low and very low susceptibility zones covered 8, 23 and 60% of the study area, respectively. Most of the locations of the observed landslides actually fall into moderate (17.78%) and high (77.78. %) susceptibility zones of the produced landslide susceptibility map. This validates the applicability of proposed methods, approaches and the classification scheme. The high susceptibility zone is along both sides of the Akşehir Fault and at the north-eastern slope of the Sultan Mountains. It was determined that the surface area of the Harlak and Deresenek formations, which have attained lithological characteristics of clayey limestone with a broken and separated base, and where area landslides occur, possesses an elevation of 1,100-1,600 m, a slope gradient of 25°-35°and a slope aspect of 22.5°-157.5°facing slopes.

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Landslide susceptibility mapping of vicinity of Yaka Landslide (Gelendost, Turkey) using conditional probability approach in GIS

Cited by 50 publications

References 16 publications

Landslide susceptibility mapping on Panaon Island, Philippines using a geographic information system

Landslide susceptibility mapping on Panaon Island, Philippines using a geographic information system

Cross-application used to validate landslide susceptibility maps using a probabilistic model from Korea

Landslide susceptibility mapping using Bayesian approach in the Sultan Mountains (Akşehir, Turkey)

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