Flood susceptibility mapping is a key tool for disaster risk reduction (DRR), particularly in regions exposed to recurrent flooding. This study presents a GIS-based regional flood susceptibility assessment for Tokat Province in the Central Black Sea region of Türkiye. A dual statistical framework combining a modified frequency ratio (FR) approach and logistic regression (LR) was used to evaluate flood proneness. An inventory of 142 historical flood locations was integrated with ten conditioning factors. Conventional FR values were transformed into normalized flood susceptibility indices and then used as inputs for LR modeling to assess multivariate effects. Model performance was evaluated using ROC and Kappa metrics. ROC–AUC results showed satisfactory predictive performance for both models, with LR demonstrating stronger discrimination (AUC = 0.84) than the FR-based model (AUC = 0.79). However, at the fixed 0.5 threshold, the FR-based model produced more stable categorical performance (Kappa = 0.43; accuracy = 0.71), whereas the lower Kappa and accuracy of LR mainly reflected the asymmetric distribution of predicted probabilities. The findings provide valuable insights for spatial planning, risk mitigation strategies, and regional-scale disaster management. Considering population and settlement characteristics of the region, flood hazard and risk assessments should be initiated urgently across the province.

Geological strength index (GSI) has been widely used as an input parameter in predicting the strength and deformation properties of rock masses. This study derived a series of equations to satisfy the original GSI lines on the basic GSI chart. Two axes ranging from 0 to 100 were employed for surface conditions of the discontinuities and the structure of rock mass, which are independent of the input parameters. The derived equations can analyze GSI values ranging from 0 to 100 within ±5% error. The engineering dimensions (EDs) such as the slope height, tunnel width, and foundation width were used together with representative elementary volume (REV) in jointed rock mass to define scale factor (sf) from 0.2 to 1 in evaluating the rock mass structure including joint pattern. The transformation of GSI into a scale-dependent parameter based on engineering scale addresses a crucial requirement in various engineering applications. The improvements proposed in this study were applied to a real slope which was close to the time of failure. The results of stability assessments show that the new proposals have sufficient capability to define rock mass quality considering EDs.

To assess the landslide hazard (LH) of the area between Lapseki and Guzelyal & imath; (C,anakkale, NW Turkiye) the LH map and the landslide density hazard map were produced. The LH maps produced in this study were calculated by multiplying the spatial probability, size probability, and temporal probability. The landslide susceptibility (LS) map was produced using the Random Forest method. While producing the LS map, elevation, land use, curvature, lithology, NDVI, distance to streams, slope, TWI, and aspect were used as input parameters. The rainfall triggering landslides was obtained as 220 mm. Using Gumbel distribution, the exceedance probability of the 220 mm rainfall value in 5, 10, 25, and 50 years were calculated as 0.453, 0.701, 0.951, and 0.997, respectively. The probability of occurrence of a landslide that is equal to or greater than a selected area was found using landslide frequency-area distribution. The probability of a landslide in the study area, surpassing an area of 0.1 km2, an area of 0,35 km2, and an area of 1 km2, with corresponding probabilities of 0.701, 0,361, and 0.184, respectively. To solve questions about where and how densely potential landslides will occur at a given time, a landslide density hazard map was produced. The Landslide density hazard map was calculated from the spatial probability, landslide density, and temporal probability. It was seen in this study that the landslide hazard concept should be considered by the decision makers for the future works such as land-use management and urban development strategies. (c) 2025 COSPAR. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

This study focuses on landslide susceptibility assessment of the area between Güzelyalı and Lapseki (Çanakkale, Türkiye) by using logistic regression, artificial neural network (ANN) and support vector machine methods. Nine input parameters such as topographic elevation, lithology, slope, land use, aspect, curvature, distance to streams, TWI, and NDVI were selected as the landslide conditioning parameters. The frequency ratio values were also calculated for the parameters and their subclasses and were assigned to express all continuous and categorical input parameters in the same scale for the considered prediction models. In addition, sensitivity (Recall), accuracy, precision, kappa indexes, F 1-score and receiver operating characteristic based on area under curve approach were calculated to assess the performances of the so produced landslide susceptibility maps. Considering all performance indicators, the most successful model was revealed as the map produced by ANN model. Producing such maps, testing their performances and using them into the practice, sustainability can be achieved in regional planning, land use and urban development stages. More importantly, a fundamental step will be taken for future works such as hazard and risk assessments in the region.

One of the Türkiye’s most destructive natural hazards is landslides. Although much progress has been achieved in this subject throughout the country, there are still some problems related to adequate meteorological and high-quality landslide data. The aim of this study, which was carried out in the eastern part of Bartın province in the Western Black Sea region of Türkiye, is to indirectly determine the possible threshold values for landslides known to be triggered by precipitation. For this purpose, first, data related to landslides, precipitation, and streamflow were compiled and analyzed. Although many landslides have been mapped in the area, it has been determined that the number of reliable data on the dates (only three exact dates) of landslide occurrences is quite limited in the area. The relationship between the landslides that occurred in 1985, 1998, and 2021, and the stream gauging–precipitation data was analyzed. Then, due to the data scarcity related to the precipitation data, an indirect method, called Soil Conservation Service Curve Number (SCS-CN), was used to determine the relation between runoff and precipitation. The results revealed that daily 80 mm and cumulative 160 mm could be selected as the threshold values that may trigger the landslides. This study serves as an illustration of how an indirect approach can be used to approximate potential precipitation thresholds in a data-scarce region. Therefore, it will be possible to use these precipitation thresholds as a basis for future landslide hazard and risk assessments.

Doğal tehlikelerden biri olan heyelanlar nedeniyle, Türkiye’de ve diğer ülkelerde hem can ve mal kayıpları hem de ekonomik ve çevresel kayıplar ortaya çıkabilmektedir. Afet bilinci kavramının, özellikle son yıllarda yaygınlaşması ve gerek ulusal, gerekse uluslararası inisiyatiflerin dikkate aldıkları önlemler ve iyileştirme çalışmaları ile doğal tehlikelerden kaynaklanan zararların, en düşük seviyeye düşürülmesine çalışılmaktadır. Bunlardan, heyelan tehlike ve risk çalışmalarının temel girdi parametrelerinden biri olan heyelan duyarlılık çalışmaları da, son derece büyük öneme sahiptir. Heyelan duyarlılık çalışmalarında parametre seçimi ile bu parametrelerin doğru ve temsil edici bir şekilde kullanılması da önemli bir konudur. Bu nedenle, bu çalışma kapsamında, heyelan duyarlılık değerlendirmelerinde sıklıkla ve öznel olarak dikkate alınan akarsulara uzaklık parametresinin kullanımına yönelik olarak yeni bir yaklaşım önerilmesi ve mevcut yöntemlerle karşılaştırmasının yapılması amaçlanmıştır. Heyelan duyarlılığının değerlendirmesinde Frekans Oranı yöntemi temel alınarak, topoğrafik yükseklik, yamaç eğimi, arazi kullanımı, litoloji, bakı, yamaç eğriselliği ve üç farklı yöntemle oluşturulan akarsulara uzaklık parametreleri dikkate alınmıştır. Akarsulara uzaklık parametresi dışındaki parametreler sabit tutularak, üç farklı heyelan duyarlılık haritası üretilmiş ve performansları iki farklı yöntemle sınanmıştır. Bu çalışmada önerilen şekliyle akarsulara uzaklık parametresinin kullanımının, her iki performans sınama yönteminde de en iyi performansı gösterdiği, sonuç heyelan duyarlılık değerlendirmelerinde yaklaşık olarak % 10’luk bir iyileştirmeye yol açtığı belirlenmiştir. Önerilen yöntemin nesnel ve kullanılabilir olduğu sonucuna varılmış olsa da, farklı sahalarda uygulanarak performansa yönelik etkilerinin araştırılması önerilmektedir.

Over the last 2 decades, Analytical Hierarchy Process (AHP) has attracted great interest of the researchers in many fields like landslide susceptibility analyses. In addition to the classical AHP method, utilization of hybrid AHP methods, such as fuzzy AHP (F-AHP), has also increased in recent years. In this study, adhering to the general operating principles of AHP, except for the pairwise comparison concept, a new data-driven F-AHP method, called FR-AHP, which can be applied in landslide susceptibility mapping using fuzzy relations and fuzzy matrices concepts, is proposed. Fuzzy Geometric Mean (FGM) and Fuzzy Extent Analyses (FEA) methods were also applied to compare the proposed FR-AHP method in Seydikemer (Muğla) region, located in the southwestern part of Turkey. Ten parameters and 108 mapped landslides were taken into account for the landslide susceptibility analyses and 3 maps were produced and compared by Area Under Curve (AUC) approach. AUC values of FEA, FGM and FR-AHP maps were calculated as 0.813, 0.806 and 0.802, respectively. Considering the difficulties in evaluating the effects of some parameters according to expert opinion and the limitations in the studies conducted in large regions, it is of great importance in terms of using more objective data-driven methods in landslide susceptibility analyses. When considered from this point of view, it is thought that the proposed FR-AHP method in this study has the potential to be a feasible, objective and high-performance approach, supported by future studies in different regions.

Rock quality designation (RQD) has been considered as a one-dimensional jointing degree property since it should be determined by measuring the core lengths obtained from drilling. Anisotropy index of jointing degree (AIjd) was formulated by Zheng et al. (2018) by considering maximum and minimum values of RQD for a jointed rock medium in three-dimensional space. In accordance with spacing terminology by ISRM (1981), defining the jointing degree for the rock masses composed of extremely closely spaced joints as well as for the rock masses including widely to extremely widely spaced joints is practically impossible because of the use of 10 cm as a threshold value in the conventional form of RQD. To overcome this limitation, theoretical RQD (TRQDt) introduced by Priest and Hudson (1976) can be taken into consideration only when the statistical distribution of discontinuity spacing has a negative exponential distribution. Anisotropy index of the jointing degree was improved using TRQDt which was adjusted to wider joint spacing by considering Priest (1993)'s recommendation on the use of variable threshold value (t) in TRQDt formulation. After applications of the improved anisotropy index of a jointing degree (AIjd′) to hypothetical jointed rock mass cases, the effect of persistency of joints on structural anisotropy of rock mass was introduced to the improved AIjd′ formulation by considering the ratings of persistency of joints as proposed by Bieniawski (1989)'s rock mass rating (RMR) classification. Two real cases were assessed in the stratified marl and the columnar basalt using the weighted anisotropy index of jointing degree (W_AIjd′). A structural anisotropy classification was developed using the RQD classification proposed by Deere (1963). The proposed methodology is capable of defining the structural anisotropy of a rock mass including joint pattern from extremely closely to extremely widely spaced joints.

The preparation of undisturbed representative samples for testing is almost impossible for geological masses such as jointed rock masses, rock accumulations and block-in-matrix-rocks (bimrocks). In this regard the work of Lindquist (1994) on the strength evaluations (and of Medley (1994) on characterization) of bimrocks are now regarded as pioneering research. Subsequent literature confirms the fundamental outcome of Lindquist’s work that when the volumetric block proportion (VBP) in a bimrock increases, the internal friction angle increases and the cohesion decreases. Further: the strength of blocks does not influence overall strength of bimrock – instead due to the strength contrast between strong blocks and weak matrix, the blocks force failure surfaces to pass tortuously around the blocks. More recent work (Sonmez et al. 2018) emphasized that under sufficient normal or confining stress conditions, the failure surfaces may also penetrate into the blocks for block-rich bimrocks with block to block contacts. Therefore, non-linear shear strength envelopes may be expected for especially block-rich bim materials such as rock accumulation (or rockfill) and jointed rock masses. In this study, a modification was introduced to Lindquist’s procedure by incorporating Leps’ (1970) non-linear shear strength envelope for rockfill (or rock accumulation) to model the strength of completely blocky accumulated rock materials (VBP goes to 100%). The modified Lindquist approach was tested by determination of the factors of safety of hypothetical models of bimslopes.

Stability analyses of slopes have been a hot topic for several decades and numerous methodologies have been introduced since the beginning of these analyses. One of these methodologies is the limit equilibrium theory, and it has been applied in different forms to various cases for almost a hundred years. Although numerous investigations and works have been carried out on this methodology, there are still wide gaps needed to be investigated. Various methods have been introduced through the years including two- and three-dimensional solutions to the slope stability. However, an extensive investigation on the effects of real-life scenarios is still absent in the literature. Therefore, this study was aimed at modelling and evaluating the slope stability considering different scenarios in two (2D) and three dimensions (3D). Available methods have been investigated in both 2D and 3D separately by considering well known cases in the literature. Also, a comparison has been conducted between two- and three-dimensional versions of the same methods. Five different hypothetical cases and a multitude of scenarios representing the possible conditional changes on the slopes were investigated during the analyses. Thus, three distinctive comparisons have been conducted by analyzing 942 data related to the factor of safety. Many intriguing results have been discovered throughout the analyses and some of them have been found against the literature. A considerable amount of the computations has produced lower factors of safety in three-dimensional models. This outcome is arguably the most significant finding of this study.

Landslides are one of the most destructive natural hazards in Turkey. In addition to loss of lives, there were many negative impacts of landslides on properties and the environment. To minimize the losses and damages related to landslides, a series of labour-intensive studies starting from landslide inventory to landslide risk mapping is required. Thus, this study aims to assess the landslide risk by a semi-quantitative approach in a landslide-prone area located in the Eastern Mediterranean region of Turkey. This region has been suffering from landslides with its high population and industrial characteristics. A total of 215 deep-seated rotational earth slides were mapped during field studies. Then, landslide-susceptibility mapping was performed by frequency ratio and logistic regression methods. For the hazard stage, the susceptibility map and the triggering indicator maps were used to produce a Landslide Hazard Index (LHI) map. As for the vulnerability analysis, a relative evaluation was performed by considering land use, infrastructure and population density data. All maps were combined at the final stage to produce a Landslide Risk Index (LRI) map of the study area. It was revealed that areal coverages of the produced LRI map were 21.4% very low (VL), 10.8% as low (L), 37.4% as medium (M), 24.8% as high (H) and 5.6% as very high (VH) LRI, respectively. The so-produced LRI map would be beneficial for further and detailed risk analyses to be performed in the future since it highlights the landslide risk hotspots in a regional scale.

Landslide inventory mapping studies have been received special attention from a wide range of specialists. In accordance with this situation, the main purpose of this study was to produce a semi-automatic GIS-based inventory mapping for locating landslides by a multiresolution segmentation process, which is the first phase of Object-Oriented Analyses (OOA). Ulus district of Bartin located in the Western Black Sea Region of Turkey was chosen as the study area. For the multiresolution segmentation process, a total of 1132 objects were automatically extracted using the first 4 bands of the Landsat ETM + satellite image and three thematic maps (slope, curvature and Normalized Difference Vegetation Index) of the study area. Multiresolution segmentation process was performed with Definiens Professional Earth (DPE in Definiens professional 5 UserGuide, Definiens AG, Munchen, Germany, 2006) software. In order to determine semi-automatically landslide locations in the study area, Artificial Neural Networks (ANN) method has been applied to the study area with 8 parameters (brightness, shape index, GLDV Contrast, Length/Width, Maximum Difference, Asymmetry, GLCM Contrast and GLCM Homogeneity) as an input and landslide (1) and no landslide (0) information as an output. This semi-automatically inventory map of the area estimated 78.2% of the existing landslides accurately. The applicability of this method is easy and quick, but when applying this method to the study area, thematic, spectral, shape and textural properties of the landslides must be revealed accurately and in detail.

As in the case throughout the world, landslides in Turkey have accounted for significant amount of economic losses and caused damage to properties as well as the environment and inhabitants. For example, considering the last 70 years' landslide records in Turkey, it was revealed that more than 60,000 people were affected due to landslides. Thus, in order to minimize the undesired landslide consequences, some measures and initiatives had to be taken. Particularly in the last 10 years, many projects have been initiated by the governmental agencies in Turkey. Of these, a web-based landslide susceptibility and hazard mapping system project, namely Disaster and Risk Reduction System (ARAS), has been initiated in 2016. The most important objective of ARAS is to establish a spatial decision support and analysis system to reduce the mass movement risk for mitigation efforts using today's technologies and data processing techniques. In this study, it was aimed at introducing ARAS and its applications on producing landslide susceptibility and hazard maps in a web-based platform. For this purpose, whole stages of ARAS in its current version were explained and landslide susceptibility and hazard maps of Kastamonu city, located in Middle Black Sea region of Turkey, were produced for this study. In ARAS, risk assessment stage is an ongoing process at the moment, and will be completed in a few years. When completed, decision-makers, planners and local authorities will benefit from the advantages of ARAS, which will provide significant gains for sustainable risk management in Turkey.

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 equilibrium analyses. Two separate, but interdependent, landslides were observed in the investigated area. In 1992 and 1994, two landslides occurred in the region after heavy precipitation and caused damages on the houses and infrastructures. An extensive field work was performed to obtain input parameters for the analyses. In addition, an unmanned aerial vehicle was flown to obtain a three-dimensional view of the landslide area for better understanding of the past failures. The landslides occurred in a flysch-type material representing complex geological characteristics. Hoek–Brown failure criterion and Geological Strength Index were chosen for the strength and visual definition of the geological unit. Since the landslide triggering factor was precipitation, the analyses were focused on the water conditions causing the failure. Sensitivity and back-analyses were performed to obtain the conditions of failure. It was revealed that a high pore pressure ratio was needed to trigger the landslides. However, the second landslide was failed with a lower pore water pressure and the current topography was determined to be on the edge of failure with a slight increase in the pore pressure ratio. In other words, the study area was still found to be prone to possible landslides in the future.

Landslides and their consequences are of great importance throughout the world and they constitute an important responsibility on the damages and fatalities among the natural or man-made hazards. Landslide mapping and assessment studies have become a very important issue for the geoscientists and the decision makers to prevent from the consequences of the landslides, particularly in the last decades. In addition to the increase in population and poor economic conditions, unconsciously built settlements, located in the landslide-prone areas, were the most influencing factors on these losses and damages sourced from the landslides. This section particularly focuses on the landslide mapping and assessment methods considering the chronological development of these methods. In addition, this section also summarizes the landslide inventory, susceptibility, hazard and risk concepts, considering the scientific landslide literature. Furthermore, past-actual trends and new perspectives on these issues were also compiled to show the readers how this subject emerged and evolved progressively.

Dünya genelinde ekonomik, sosyolojik, çevresel ve fiziksel kırılganlıkların artması, son yıllarda afetler sonucunda oluşan can ve mal kayıplarını önemli oranda arttırmıştır. Coğrafi yapısı, iklimsel ve jeolojik özellikleri nedeniyle afetlere sık sık maruz kalan Türkiye’de özellikle depremler, heyelanlar ve taşkınlar önemli miktarda can ve mal kaybına sebep olmaktadır. Yıkıcı etkiye sahip olan heyelanların verdiği zararların boyutlarının gereğinden daha düşük tahmin edilmesi, heyelanlara ilişkin detaylı çalışmaların yapılmasını zaruri kılmaktadır.Bu çalışmada heyelan duyarlılığı, tehlikesi ve riski ile ilgili bilimsel çalışmalarda Türkiye ve Avrupa Birliği (AB)’ne üye ülkelerin karşılaştırılması amaçlanmıştır. Yapılan taramalara göre heyelan duyarlılığı, tehlikesi ve riski ile ilgili AB’ne üye ülkelerdeki ve Türkiye’deki araştırmacılar tarafından uluslararası dergilerde yayımlanan toplam 714 çalışma incelenmiştir. Bu çalışmalar incelendiğinde en fazla çalışmanın heyelan duyarlılığı konusunda yapıldığı görülmektedir. AB’ne üye ülkelerdeki araştırmacılar tarafından yapılan toplam 335 heyelan duyarlılığı, 164 heyelan tehlikesi ve 122 heyelan riski ile ilgili çalışmaya ulaşılırken, Türkiye’deki araştırmacılar tarafından yapılan 85 heyelan duyarlılığı, 3 heyelan tehlikesi ve 5 heyelan riski ile ilgili çalışmaya ulaşılmıştır.Heyelan duyarlılığı ile ilgili çalışmalar kıyaslandığında, toplam çalışma sayısı açısından İtalya’daki araştırmacılar tarafından yapılan 107 çalışma ilk sırada yer almaktadır. Alınan toplam atıf sayısı açısından ise Türkiye’deki araştırmacılar tarafından yapılan ve toplam çalışma sayısı açısından 2. sırada olan 85 çalışma, aldıkları 5344 atıfla ilk sırada gelmektedir. AB’ne üye ülkelerle kıyaslandığında Türkiye’de yapılan heyelan duyarlılığı çalışmaları bu alanda önemli bir yer tutarken, heyelan tehlikesi ve riski ile ilgili az sayıda çalışma olması bu alanlarda daha fazla çalışılmasının gerekliliğini göstermektedir.

Landslides have a significant portion of responsibility on the damages and losses caused by natural hazards such as earthquakes, floods, storms, and tsunamis all over the world. Thus, landslides and their consequences are of great importance among the scientists and authorities who want to minimize these effects for a long time. This procedure simply begins with the preparation of landslide database and inventory maps, which constitutes a fundamental basis for the further steps including landslide susceptibility, hazard, and risk assessments. In this aspect, this procedure can be considered as one of the most important stages for any landslide work to minimize the undesired consequences of landslides. This stage can be realized using some statistical techniques such as simple random, systematic, stratified and cluster sampling strategies in the literature. In this chapter, firstly, basic landslide definitions and concepts were discussed. Then, landslide inventory, susceptibility and hazard concepts were pointed out and linked to the sampling strategies with the recent literature. Although, every considered method has pros and cons, it could be concluded that the sampling carried out in the rupture zones of landslides as polygon features or seed cell approach representing the pre-failure conditions seem to be more realistic to obtain more accurate maps. The other important issue pointed out in this chapter is on the selection of data mining technique(s). Since landslides are complex processes and can be affected by many factors, this stage is very important to reflect the landslide conditions with huge amount of data. In many cases, the researchers generally encounter to struggle with huge amount of data related to the landslide initiation and/or mechanisms. Thus, the selection of data mining techniques deserve the necessary precaution and is elaborately discussed overall the chapter.

Although general approaches to the effect of water on the mechanisms causing landslides have been adopted, the work presented in this paper was carried out to quantify the landslide susceptibility variation in space and time, integrating the soil moisture distribution and routing (SMDR) model and landslide susceptibility concept. The approach proposed in the present study reflects the temporal effects of the saturation degree index (SDI) on landslide susceptibility as a new index to understand the effect of soil saturation. The topographic wetness index (TWI) is a conventional parameter that represents the relative wetness on landsliding. The new proposed landslide susceptibility approach is used in the study area to understand the effect of soil saturation and the emergence of the Derebaşı landslide in the study area. The comparative results of landslide susceptibility maps obtained from the new approach utilizing the proposed SDI and conventional TWI are remarkable. Accordingly, a new substantial method is proposed using the attainable monthly mean meteorological data to generate monthly landslide susceptibility maps. The results obtained for the Derebaşı landslide using the proposed method are validated with the other landslide that has occurred in the same watershed. The results revealed that the approach proposed in this study was compatible with the landslide mechanism in the study area and may help to express the water effect in landslide susceptibility analyses.

This study aims to investigate the performances of different training algorithms used for an artificial neural network (ANN) method to produce landslide susceptibility maps. For this purpose, Ovacık region (southeast of Karabük Province), located in the Western Black Sea Region (Turkey), was selected as the study area. A total of 196 landslides were mapped, and a landslide database was prepared. Topographical elevation, slope angle, aspect, wetness index, lithology, and vegetation index parameters were taken into account for the landslide susceptibility analyses. Two different ANN structures, which were composed of single and double hidden layers, were applied to compare the effects of the ANN. Four different training algorithms, namely batch back-propagation, quick propagation, conjugate gradient descent (CGD), and Levenberg–Marquardt, were used for the training stage of the ANN models. Thus, eight different landslide susceptibility maps were produced for the study area using different ANN structures and algorithms. In order to assess the effects and spatial performances of the considered training algorithms on the ANN models, the relative operating characteristics (ROC) and relation value (rij) approaches were used. The susceptibility map produced by CGD1 has the highest AUC (0.817) and rij values (0.972). Comparison of the susceptibility maps indicated that CGD training algorithm is the slowest one among the other algorithms, but this algorithm showed the highest performance on the results.

Abstract Natural hazards and their consequences are of great importance throughout the world. In Turkey, landslides constitute approximately 5% of the overall damage. The most important part of any landslide study is to extract landslide properties and database. In this study, Karabük city was selected as a study area which is known as one of the most landslide prone areas in Turkey. The study area contains the official borders of Karabük province. The area surrounded by the coordinates of 4518148N-4603891N and 424593E-512511E which has an areal extent of 4067 km square. The data of 1663 occurred landslides in Karabük, were digitized from 1/500.000 scale Turkey Landslide Inventory Map by considering the scarps with point vector format. Considering the literature, parameters of lithology, slope, topographical elevation, NDVI and aspect, which were frequently used among the researchers in landslide assessments, were produced and analyzed a GIS (Geographical Information System) platform. In order to perform analyses, the study area was divided into 62 watersheds. Then, lithology, slope, aspect, topographical elevation and NVDI characteristics of the region were automatically extracted by considering the landslide locations. In this type of study, GIS provides many advantages. For the next stages of landslide assessments such as susceptibility, hazard and risk, this stage provides important inputs and can be considered as the most important stage.