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    A comparative study of frequency ratio, weights of evidence and logistic regression methods for landslide susceptibility mapping: Sultan Mountains, SW Turkey
    (PERGAMON-ELSEVIER SCIENCE LTD, 2013) Ozdemir, Adnan; Altural, Tolga
    This study evaluated and compared landslide susceptibility maps produced with three different methods, frequency ratio, weights of evidence, and logistic regression, by using validation datasets. The field surveys performed as part of this investigation mapped the locations of 90 landslides that had been identified in the Sultan Mountains of south-western Turkey. The landslide influence parameters used for this study are geology, relative permeability, land use/land cover, precipitation, elevation, slope, aspect, total curvature, plan curvature, profile curvature, wetness index, stream power index, sediment transportation capacity index, distance to drainage, distance to fault, drainage density, fault density, and spring density maps. The relationships between landslide distributions and these parameters were analysed using the three methods, and the results of these methods were then used to calculate the landslide susceptibility of the entire study area. The accuracy of the final landslide susceptibility maps was evaluated based on the landslides observed during the fieldwork, and the accuracy of the models was evaluated by calculating each model's relative operating characteristic curve. The predictive capability of each model was determined from the area under the relative operating characteristic curve and the areas under the curves obtained using the frequency ratio, logistic regression, and weights of evidence methods are 0.976, 0.952, and 0.937, respectively. These results indicate that the frequency ratio and weights of evidence models are relatively good estimators of landslide susceptibility in the study area. Specifically, the results of the correlation analysis show a high correlation between the frequency ratio and weights of evidence results, and the frequency ratio and logistic regression methods exhibit correlation coefficients of 0.771 and 0.727, respectively. The frequency ratio model is simple, and its input, calculation and output processes are easily understood. The interpretations of the susceptibility map reveal that geology, slope steepness, slope aspect, and elevation played major roles in landslide occurrence and distribution in the Sultan Mountains. The landslide susceptibility maps produced from this study could therefore assist planners and engineers during development and land-use planning. (C) 2012 Elsevier Ltd. All rights reserved.
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    GEOGRAPHIC INFORMATION SYSTEM FOR KONYA CLOSED BASIN PROJECT
    (BULGARIAN CARTOGRAPHIC ASSOC, 2012) Ustun, Aydin; Bildirici, I. Oztug; Ustuntas, Taner; Tusat, Ekrem; Ozkan, Ihsan; Eren, Yasar; Ozdemir, Adnan
    The main goal of the Konya Closed Basin Project is to investigate land subsidence within the basin. The vertical changes have been investigated through GPS measurements and InSAR images taken at different dates. In order to decide whether the land subsidence is significant for land use in residential and agricultural areas within the basin, a GIS system is necessary. For this purpose GoogleEarth, MapInfo and Generic Mapping Tools (GMT) were chosen as GIS software packages. At first, a preliminary study has been performed using I: 100 000 and 1: 250 000 topographic maps which are scanned and registered. A continuous mosaic of map sheets created from them is overlaid on the terrain in the Google Earth. GPS deformation network was designed over the mosaic map considering land use and hydrogeological properties of the KCB. Other data that the system contains are GPS points, wells, at which water depth is measured, InSAR images, geologic layers created from geological maps, and land use maps created by using NVDI method. The geology maps are digitized in MapInfo. After the completion of data collection, GIS analyses will be undertaken in order to evaluate land subsidence potential of the basin.
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    GIS-based groundwater spring potential mapping in the Sultan Mountains (Konya, Turkey) using frequency ratio, weights of evidence and logistic regression methods and their comparison
    (ELSEVIER, 2011) Ozdemir, Adnan
    In this study, groundwater spring potential maps produced by three different methods, frequency ratio, weights of evidence, and logistic regression, were evaluated using validation data sets and compared to each other. Groundwater spring occurrence potential maps in the Sultan Mountains (Konya, Turkey) were constructed using the relationship between groundwater spring locations and their causative factors. Groundwater spring locations were identified in the study area from a topographic map. Different thematic maps of the study area, such as geology, topography, geomorphology, hydrology, and land use/cover, have been used to identify groundwater potential zones. Seventeen spring-related parameter layers of the entire study area were used to generate groundwater spring potential maps. These are geology (lithology), fault density, distance to fault, relative permeability of lithologies, elevation, slope aspect, slope steepness, curvature, plan curvature, profile curvature, topographic wetness index, stream power index, sediment transport capacity index, drainage density, distance to drainage, land use/cover, and precipitation. The predictive capability of each model was determined by the area under the relative operating characteristic curve. The areas under the curve for frequency ratio, weights of evidence and logistic regression methods were calculated as 0.903, 0.880, and 0.840, respectively. These results indicate that frequency ratio and weights of evidence models are relatively good estimators, whereas logistic regression is a relatively poor estimator of groundwater spring potential mapping in the study area. The frequency ratio model is simple; the process of input, calculation and output can be readily understood. The produced groundwater spring potential maps can serve planners and engineers in groundwater development plans and land-use planning. (C) 2011 Elsevier B.V. All rights reserved.
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    Land subsidence in Konya Closed Basin and its spatio-temporal detection by GPS and DInSAR
    (SPRINGER, 2015) Ustun, Aydin; Tusat, Ekrem; Yalvac, Sefa; Ozkan, Ihsan; Eren, Yasar; Ozdemir, Adnan; Bildirici, I. Oztug
    Konya Closed Basin that includes two depression blocks, Konya and Tuz Golu, is the biggest endorheic basin in Turkey. A lowering in the ground levels of the depositional areas has been shown with respect to the surrounding mountains. In the past, this process was controlled by geological and hydrogeological phenomena; nowadays, it has gained a new dimension due to the excessive pumping of groundwater to the Earth's surface. The geodetic techniques such as Global Positioning System (GPS) and Interferometric Synthetic Aperture Radar (InSAR) reveal a considerable land subsidence resulting in the rate of 1-4 cm/year in Konya sub-basin. It seems that the calculated amounts are responsible for changing environmental conditions like seasonality. Both GPS and differential InSAR techniques verify these relatively small fluctuations in the subsidence development. Target districts that should be observed primarily are agricultural zones where groundwater is overused for irrigation and regions where human population density is high. The geocoded interferogram and vegetation index map verify the spatial relation between the subsidence and green areas. In this study, a project dealing with the investigation of the land subsidence occurrences and of their possible causes and consequences within a specific part of Konya Closed Basin is introduced.
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    Landslide susceptibility mapping of vicinity of Yaka Landslide (Gelendost, Turkey) using conditional probability approach in GIS
    (SPRINGER, 2009) Ozdemir, Adnan
    On 19 February 2007, a landslide occurred on the AlaardÄaut +/-double dagger Slope, located 1.6 km south of the town of Yaka (Gelendost, Turkey.) Subsequently, the displaced materials transformed into a mud flow in Eglence Creek and continued 750 m downstream towards the town of Yaka. The mass poised for motion in the Yaka Landslide source area and its vicinity, which would be triggered to a kinetic state by trigger factors such as heavy or sustained rainfall and/or snowmelt, poise a danger in the form of loss of life and property to Yaka with its population of 3,000. This study was undertaken to construct a susceptibility mapping of the vicinity of the Yaka Landslide's source area and to relate it to movement of the landslide mass with the goal of prevention or mitigation of loss of life and property. The landslide susceptibility map was formulated by designating the relationship of the effecting factors that cause landslides such as lithology, gradient, slope aspect, elevation, topographical moisture index, and stream power index to the landslide map, as determined by analysis of the terrain, through the implementation of the conditional probability method. It was determined that the surface area of the Goksogut formation, which has attained lithological characteristics of clayey limestone with a broken and separated base and where area landslides occur, possesses an elevation of 1,100-1,300 m, a slope gradient of 15A degrees-35A degrees and a slope aspect between 0A degrees-67.5A degrees and 157A degrees-247A degrees. Loss of life and property may be avoided by the construction of structures to check the debris mass in Eglence Creek, the cleaning of the canal which passes through Yaka, the broadening of the canal's base area, elevating the protective edges along the canal and the establishment of a protective zone at least 10-m wide on each side of the canal to deter against damage from probable landslide occurrence and mud flow.
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    Landslide susceptibility mapping using Bayesian approach in the Sultan Mountains (AkAYehir, Turkey)
    (SPRINGER, 2011) Ozdemir, Adnan
    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 AkAYehir, 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 AkAYehir 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 25A degrees-35A degrees and a slope aspect of 22.5A degrees-157.5A degrees facing slopes.
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    Monitoring landslides with geophysical and geodetic observations
    (SPRINGER, 2015) Zeybek, Mustafa; Sanlioglu, Ismail; Ozdemir, Adnan
    The objective of this study was to evaluate and predict land movement by integrating geodetic, geophysical and meteorological data in a landslide area. Specifically, electrical resistivity tomography surveying, Global Navigation Satellite System and terrestrial laser scanning techniques were integrated to monitor a landslide. The study area lies to the southeast of the town of Ta kent in southern Turkey, close to Balcflar in the Central Taurus mountain chain. Landslides result in considerable damage to structures, farmland and the environment in this area; therefore, it is important to characterise the size, extent and timing of past land movements in order to mitigate damage from future landslides. Analysis presented in this paper shows that the greatest land movements in the region occur in spring, when average motions can be up to 1.5 m per month. It is demonstrated that integrated techniques provide a better means for monitoring landslide processes and gathering data for predictions of future movements. Mapping landslide movements by integrating geophysical and geodetic observations can provide a meaningful evaluation of a landslide and its dynamics.
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    Using a binary logistic regression method and GIS for evaluating and mapping the groundwater spring potential in the Sultan Mountains (Aksehir, Turkey)
    (ELSEVIER, 2011) Ozdemir, Adnan
    The purpose of this study is to produce a groundwater spring potential map of the Sultan Mountains in central Turkey, based on a logistic regression method within a Geographic Information System (GIS) environment. Using field surveys, the locations of the springs (440 springs) were determined in the study area. In this study, 17 spring-related factors were used in the analysis: geology, relative permeability, land use/land cover, precipitation, elevation, slope, aspect, total curvature, plan curvature, profile curvature, wetness index, stream power index, sediment transport capacity index, distance to drainage, distance to fault, drainage density, and fault density map. The coefficients of the predictor variables were estimated using binary logistic regression analysis and were used to calculate the groundwater spring potential for the entire study area. The accuracy of the final spring potential map was evaluated based on the observed springs. The accuracy of the model was evaluated by calculating the relative operating characteristics. The area value of the relative operating characteristic curve model was found to be 0.82. These results indicate that the model is a good estimator of the spring potential in the study area. The spring potential map shows that the areas of very low, low, moderate and high groundwater spring potential classes are 105.586 km(2) (28.99%), 74.271 km(2) (19.906%), 101.203 km(2) (27.14%), and 90.05 km(2) (24.671%), respectively. The interpretations of the potential map showed that stream power index, relative permeability of lithologies, geology, elevation, aspect, wetness index, plan curvature, and drainage density play major roles in spring occurrence and distribution in the Sultan Mountains. The logistic regression approach has not yet been used to delineate groundwater potential zones. In this study, the logistic regression method was used to locate potential zones for groundwater springs in the Sultan Mountains. The evolved model was found to be in strong agreement with the available groundwater spring test data. Hence, this method can be used routinely in groundwater exploration under favourable conditions. (C) 2011 Elsevier B.V. All rights reserved.