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1.
Landslide susceptibility zonation mapping is a fundamental procedure for geo-disaster management in tropical and sub-tropical regions. Recently, various landslide susceptibility zonation models have been introduced in Nepal with diverse approaches of assessment. However, validation is still a problem. Additionally, the role of various predisposing causative parameters for landslide activity is still not well understood in the Nepal Himalaya. To address these issues of susceptibility zonation and landslide activity, about 4,000 km2 area of central Nepal was selected for regional-scale assessment of landslide activity and susceptibility zonation mapping. In total, 655 new landslides and 9,229 old landslides were identified with the study area with the help of satellite images, aerial photographs, field data and available reports. The old landslide inventory was “blind landslide database” and could not explain the particular rainfall event responsible for the particular landslide. But considering size of the landslide, blind landslide inventory was reclassified into two databases: short-duration high-intensity rainfall-induced landslide inventory and long-duration low-intensity rainfall-induced landslide inventory. These landslide inventory maps were considered as proxy maps of multiple rainfall event-based landslide inventories. Similarly, all 9,884 landslides were considered for the activity assessment of predisposing causative parameters. For the Nepal Himalaya, slope, slope aspect, geology and road construction activity (anthropogenic cause) were identified as most affective predisposing causative parameters for landslide activity. For susceptibility zonation, multivariate approach was considered and two proxy rainfall event-based landslide databases were used for the logistic regression modelling, while a relatively recent landslide database was used in validation. Two event-based susceptibility zonation maps were merged and rectified to prepare the final susceptibility zonation map and its prediction rate was found to be more than 82 %. From this work, it is concluded that rectification of susceptibility zonation map is very appropriate and reliable. The results of this research contribute to a significant improvement in landslide inventory preparation procedure, susceptibility zonation mapping approaches as well as role of various predisposing causative parameters for the landslide activity.  相似文献   

2.
Particularly in the last decade, landslide susceptibility and hazard maps have been used for urban planning and site selection of infrastructures. Most of the procedures for preparing of landslide susceptibility maps need high-quality landslide inventory map. Although the rainfall and seismic activities are accepted as triggering factor for landslides, designation of the triggering factor for each landslide in the inventory is almost impossible when well-documented records are unavailable. Therefore, during preparation of landslide susceptibility map, whole landslide records in the inventory map are used together without classifying based on the triggering factors. Although seismic activity is accepted as a triggering factor, possible effect of the use of seismic activity on production of landslide susceptibility map was investigated in this study, and the subject is open to discussion. For this purpose, a series of stability analyses based on circular failure and infinite slope model were performed considering different pseudostatic conditions. The results of analyses show that gentle slopes have higher susceptibility to failure than steeper ones, even if their stability conditions (susceptibilities) are similar for static condition. The seismic forces acting on failure surfaces may not be sufficiently taken into consideration in the conventionally prepared landslide susceptibility maps. Employing the general decreasing trend in stability condition based on slope face angle and the seismic acceleration, a new procedure was introduced for preparing of the landslide susceptibility map for a scenario earthquake. The prediction performance of occurring landslides increased after the procedure was applied to the conventionally prepared landslide susceptibility map. According to the threshold independent spatial performance analyses of the proposed methodology and the produced landslide susceptibility maps, the area under ROC curve values were calculated as 0.801, 0.933, and 0.947 for the maps prepared by considering conventional method and scenario earthquakes having M w values of 5.5 and 7.5, respectively.  相似文献   

3.
Landslide inventories are the most important data source for landslide process, susceptibility, hazard, and risk analyses. The objective of this study was to identify an effective method for mapping a landslide inventory for a large study area (19,186 km2) from Light Detection and Ranging (LiDAR) digital terrain model (DTM) derivatives. This inventory should in particular be optimized for statistical susceptibility modeling of earth and debris slides. We compared the mapping of a representative set of landslide bodies with polygons (earth and debris slides, earth flows, complex landslides, and areas with slides) and a substantially complete set of earth and debris slide main scarps with points by visual interpretation of LiDAR DTM derivatives. The effectiveness of the two mapping methods was estimated by evaluating the requirements on an inventory used for statistical susceptibility modeling and their fulfillment by our mapped inventories. The resulting landslide inventories improved the knowledge on landslide events in the study area and outlined the heterogeneity of the study area with respect to landslide susceptibility. The obtained effectiveness estimate demonstrated that none of our mapped inventories are perfect for statistical landslide susceptibility modeling. However, opposed to mapping polygons, mapping earth and debris slides with a point in the main scarp were most effective for statistical susceptibility modeling within large study areas. Therefore, earth and debris slides were mapped with points in the main scarp in entire Lower Austria. The advantages, drawbacks, and effectiveness of landslide mapping on the basis of LiDAR DTM derivatives compared to other imagery and techniques were discussed.  相似文献   

4.
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 (rij) 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.  相似文献   

5.
We model the rainfall-induced initiation of shallow landslides over a broad region using a deterministic approach, the Transient Rainfall Infiltration and Grid-based Slope-stability (TRIGRS) model that couples an infinite-slope stability analysis with a one-dimensional analytical solution for transient pore pressure response to rainfall infiltration. This model permits the evaluation of regional shallow landslide susceptibility in a Geographic Information System framework, and we use it to analyze susceptibility to shallow landslides in an area in the eastern Umbria Region of central Italy. As shown on a landslide inventory map produced by the Italian National Research Council, the area has been affected in the past by shallow landslides, many of which have transformed into debris flows. Input data for the TRIGRS model include time-varying rainfall, topographic slope, colluvial thickness, initial water table depth, and material strength and hydraulic properties. Because of a paucity of input data, we focus on parametric analyses to calibrate and test the model and show the effect of variation in material properties and initial water table conditions on the distribution of simulated instability in the study area in response to realistic rainfall. Comparing the results with the shallow landslide inventory map, we find more than 80% agreement between predicted shallow landslide susceptibility and the inventory, despite the paucity of input data.  相似文献   

6.
Statistical approach to earthquake-induced landslide susceptibility   总被引：13，自引：0，他引：13  
Susceptibility analysis for predicting earthquake-induced landslides has most frequently been done using deterministic methods; multivariate statistical methods have not previously been applied. In this study, however, we introduce a statistical methodology that uses the intensity of earthquake shaking as a landslide triggering factor. This methodology is applied in a study of shallow earthquake-induced landslides in central western Taiwan. The results show that we can accurately interpret landslide distribution in the study area and predict the occurrence of landslides in neighboring regions. This susceptibility model is capable of predicting shallow landslides induced during an earthquake scenario with similar range of ground shaking, without requiring the use of geotechnical, groundwater or failure depth data.  相似文献   

7.
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.  相似文献   

8.

Landslides are the main secondary effects of earthquakes in mountainous areas. The spatial distribution of these landslides is controlled by the local seismic ground motion and the local slope stability. While gravitational instabilities in arid and semi-arid environments are understudied, we document the landslides triggered by the Sarpol Zahab earthquake (November 12, 2017, Mw7.3, Iran/Iraq border), the largest event ever recorded in the semi-arid Zagros Mountains. An original earthquake-induced landslide inventory was derived, encompassing landslides of various sizes and velocities (from rapid disrupted rockfalls to slow-moving coherent landslides). This inventory confirms the low level of triggered landslides in semi-arid environments. It also displays clear differences in the spatial and volumetric distributions of earthquake-induced landslides, having 386 rockfalls of limited size triggered around the epicenter, and 9 giant (areas of ca. 106 m2) active and ancient deep-seated landslides coseismically accelerated at locations up to 180 km from the epicenter. This unusual distant triggering is discussed and interpreted as an interaction between the earthquake source properties and the local geological conditions, emphasizing the key role of seismic ground motion variability at short spatial scales in triggering landslides. Finally, the study documents the kinematics of slow-moving ancient landslides accelerated by earthquakes, and opens up new perspectives for studying landslide triggering over short (~?1–10 years) and long-time (~?1000–10,000 years) periods.

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9.
The main purpose of this study is to develop a new hazard evaluation technique considering the current limitations, particularly for shallow landslides. For this purpose, the Buyukkoy catchment area, located in the East Black Sea Region in the east of Rize province and the south of Cayeli district, was selected as the study area. The investigations were executed in four different stages. These were (1) preparation of a temporal shallow landslide inventory of the study area, (2) assessment of conditioning factors in the catchment, (3) susceptibility analyses and (4) hazard evaluations and mapping. A total of 251 shallow landslides in the period of 1955–2007 were recognised using different data sources. A ‘Sampling Circle’ approach was proposed to define shallow landslide initiation in the mapping units in susceptibility evaluations. To accomplish the susceptibility analyses, the method of artificial neural networks was implemented. According to the performance analyses conducted using the training and testing datasets, the prediction and generalisation capacities of the models were found to be very high. To transform the susceptibility values into hazard rates, a new approach with a new equation was developed, taking into account the behaviour of the responsible triggering factor over time in the study area. In the proposed equation, the threshold value of the triggering factor and the recurrence interval are the independent variables. This unique property of the suggested equation allows the execution of more flexible and more dynamic hazard assessments. Finally, using the proposed technique, shallow landslide initiation hazard maps of the Buyukkoy catchment area for the return periods of 1, 2, 5, 10, 50 and 100 years were produced.  相似文献   

10.
A Luoi is a Vietnamese–Laotian border district situated in the western part of Thua Thien Hue province, central Vietnam, where landslides occur frequently and seriously affect local living conditions. This study focuses on the spatial analysis of landslide susceptibility in this 263-km2 area. To analyze landslide manifestation in the study area, causative factor maps are derived of slope angle, weathering, land use, geomorphology, fault density, geology, drainage distance, elevation, and precipitation. The analytical hierarchical process approach is used to combine these maps for landslide susceptibility mapping. A landslide susceptibility zonation map with four landslide susceptibility classes, i.e. low, moderate, high, and very high susceptibility for landsliding, is derived based on the correspondence with an inventory of observed landslides. The final map indicates that about 37% of the area is very highly susceptible for landsliding and about 22% is highly susceptible, which means that more than half of the area should be considered prone to landsliding.  相似文献   

11.
Tanyaş  Hakan  Görüm  Tolga  Fadel  Islam  Yıldırım  Cengiz  Lombardo  Luigi 《Landslides》2022,19(6):1405-1420

On November 14, 2016, the northeastern South Island of New Zealand was hit by the magnitude Mw 7.8 Kaikōura earthquake, which is characterized by the most complex rupturing mechanism ever recorded. The widespread landslides triggered by the earthquake make this event a great case study to revisit our current knowledge of earthquake-triggered landslides in terms of factors controlling the spatial distribution of landslides and the rapid assessment of geographic areas affected by widespread landsliding. Although the spatial and size distributions of landslides have already been investigated in the literature, a polygon-based co-seismic landslide inventory with landslide size information is still not available as of June 2021. To address this issue and leverage this large landslide event, we mapped 14,233 landslides over a total area of approximately 14,000 km2. We also identified 101 landslide dams and shared them all via an open-access repository. We examined the spatial distribution of co-seismic landslides in relation to lithologic units and seismic and morphometric characteristics. We analyzed the size statistics of these landslides in a comparative manner, by using the five largest co-seismic landslide inventories ever mapped (i.e., Chi-Chi, Denali, Wenchuan, Haiti, and Gorkha). We compared our inventory with respect to these five ones to answer the question of whether the landslides triggered by the 2016 Kaikōura earthquake are less numerous and/or share size characteristics similar to those of other strong co-seismic landslide events. Our findings show that the spatial distribution of the Kaikōura landslide event is not significantly different from those belonging to other extreme landslide events, but the average landslide size generated by the Kaikōura earthquake is relatively larger compared to some other large earthquakes (i.e., Wenchuan and Gorkha).

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12.
Landslide susceptibility mapping is essential for land-use activities and management decision making in hilly or mountainous regions. The existing approaches to landslide susceptibility zoning and mapping require many different types of data. In this study, we propose a fractal method to map landslide susceptibility using historical landslide inventories only. The spatial distribution of landslides is generally not uniform, but instead clustered at many different scales. In the method, we measure the degree of spatial clustering of existing landslides in a region using a box-counting method and apply the derived fractal clustering relation to produce a landslide susceptibility map by means of GIS-supported spatial analysis. The method is illustrated by two examples at different regional scales using the landslides inventory data from Zhejiang Province, China, where the landslides are mainly triggered by rainfall. In the illustrative examples, the landslides from the inventory are divided into two time periods: The landslides in the first period are used to produce a landslide susceptibility map, and those in the late period are taken as validation samples for examining the predictive capability of the landslide susceptibility maps. These examples demonstrate that the landslide susceptibility map created by the proposed technique is reliable.  相似文献   

13.
In many regions, the absence of a landslide inventory hampers the production of susceptibility or hazard maps. Therefore, a method combining a procedure for sampling of landslide-affected and landslide-free grid cells from a limited landslide inventory and logistic regression modelling was tested for susceptibility mapping of slide- and flow-type landslides on a European scale. Landslide inventories were available for Norway, Campania (Italy), and the Barcelonnette Basin (France), and from each inventory, a random subsample was extracted. In addition, a landslide dataset was produced from the analysis of Google Earth images in combination with the extraction of landslide locations reported in scientific publications. Attention was paid to have a representative distribution of landslides over Europe. In total, the landslide-affected sample contained 1,340 landslides. Then a procedure to select landslide-free grid cells was designed taking account of the incompleteness of the landslide inventory and the high proportion of flat areas in Europe. Using stepwise logistic regression, a model including slope gradient, standard deviation of slope gradient, lithology, soil, and land cover type was calibrated. The classified susceptibility map produced from the model was then validated by visual comparison with national landslide inventory or susceptibility maps available from literature. A quantitative validation was only possible for Norway, Spain, and two regions in Italy. The first results are promising and suggest that, with regard to preparedness for and response to landslide disasters, the method can be used for urgently required landslide susceptibility mapping in regions where currently only sparse landslide inventory data are available.  相似文献   

14.
This paper describes the potential applicability of a hydrological–geotechnical modeling system using satellite-based rainfall estimates for a shallow landslide prediction system. The physically based distributed model has been developed by integrating a grid-based distributed kinematic wave rainfall-runoff model with an infinite slope stability approach. The model was forced by the satellite-based near real-time half-hourly CMORPH global rainfall product prepared by NOAA-CPC. The method combines the following two model outputs necessary for identifying where and when shallow landslides may potentially occur in the catchment: (1) the time-invariant spatial distribution of areas susceptible to slope instability map, for which the river catchment is divided into stability classes according to the critical relative soil saturation; this output is designed to portray the effect of quasi-static land surface variables and soil strength properties on slope instability and (2) a produced map linked with spatiotemporally varying hydrologic properties to provide a time-varying estimate of susceptibility to slope movement in response to rainfall. The proposed hydrological model predicts the dynamic of soil saturation in each grid element. The stored water in each grid element is then used for updating the relative soil saturation and analyzing the slope stability. A grid of slope is defined to be unstable when the relative soil saturation becomes higher than the critical level and is the basis for issuing a shallow landslide warning. The method was applied to past landslides in the upper Citarum River catchment (2,310 km2), Indonesia; the resulting time-invariant landslide susceptibility map shows good agreement with the spatial patterns of documented historical landslides (1985–2008). Application of the model to two recent shallow landslides shows that the model can successfully predict the effect of rainfall movement and intensity on the spatiotemporal dynamic of hydrological variables that trigger shallow landslides. Several hours before the landslides, the model predicted unstable conditions in some grids over and near the grids at which the actual shallow landslides occurred. Overall, the results demonstrate the potential applicability of the modeling system for shallow landslide disaster predictions and warnings.  相似文献   

15.
In this paper, we propose a methodology for landslide susceptibility assessment at a regional scale in Yunnan, southwestern province of China. A landslide inventory map including 3,242 landslide points was prepared for the study area. Five factors recognized as correlated to landslide (namely, lithology, relative relief, tectonic fault density, rainfall, and road density) were analyzed and mapped in geographic information system. An index expressing the correlation between each factor and landslides [called class landslide susceptibility index (CLSI)] was proposed in the study. While analyzing landslide distribution in a large area, point aggregation might be expected. To quantify the uncertainty caused by aggregation, class landslide aggregation index was proposed. To account for the importance of each of the factors in the landslide susceptibility assessment, some weights were calculated by means of analytic hierarchy process. We propose a weighted class landslide susceptibility model (WCLSM), obtained by the combination of CLSI values of each factor with the correspondent weight. WCLSM performance in the study area was evaluated comparing the results obtained by first modeling all landslides and then by performing a time partition. The model was run including only landslides that occurred before 2009 and then validated with respect to landslides that occurred after 2009. The prediction–rate curve shows that the WCLSM model provides a good prediction for the study area. Of the study area, 21.4 % shows very high and high susceptibility and includes the 87.7 % of the number of landslides that occurred after 2009.  相似文献   

16.
Landslides are one of the most frequent and common natural hazards in Malaysia. Preparation of landslide susceptibility maps is one of the first and most important steps in the landslide hazard mitigation. However, due to complex nature of landslides, producing a reliable susceptibility map is not easy. For this reason, a number of different approaches have been used, including direct and indirect heuristic approaches, deterministic, probabilistic, statistical, and data mining approaches. Moreover, these landslides can be systematically assessed and mapped through a traditional mapping framework using geoinformation technologies. Since the early 1990s, several mathematical models have been developed and applied to landslide hazard mapping using geographic information system (GIS). Among various approaches, fuzzy logic relation for mapping landslide susceptibility is one of the techniques that allows to describe the role of each predisposing factor (landslide-conditioning parameters) and their optimal combination. This paper presents a new attempt at landslide susceptibility mapping using fuzzy logic relations and their cross application of membership values to three study areas in Malaysia using a GIS. The possibility of capturing the judgment and the modeling of conditioning factors are the main advantages of using fuzzy logic. These models are capable to capture the conditioning factors directly affecting the landslides and also the inter-relationship among them. In the first stage of the study, a landslide inventory was complied for each of the three study areas using both field surveys and airphoto studies. Using total 12 topographic and lithological variables, landslide susceptibility models were developed using the fuzzy logic approach. Then the landslide inventory and the parameter maps were analyzed together using the fuzzy relations and the landslide susceptibility maps produced. Finally, the prediction performance of the susceptibility maps was checked by considering field-verified landslide locations in the studied areas. Further, the susceptibility maps were validated using the receiver-operating characteristics (ROC) success rate curves. The ROC curve technique is based on plotting model sensitivity—true positive fraction values calculated for different threshold values versus model specificity—true negative fraction values on a graph. The ROC curves were calculated for the landslide susceptibility maps obtained from the application and cross application of fuzzy logic relations. Qualitatively, the produced landslide susceptibility maps showed greater than 82% landslide susceptibility in all nine cases. The results indicated that, when compared with the landslide susceptibility maps, the landslides identified in the study areas were found to be located in the very high and high susceptibility zones. This shows that as far as the performance of the fuzzy logic relation approach is concerned, the results appeared to be quite satisfactory, the zones determined on the map being zones of relative susceptibility.  相似文献   

17.
Statistical and deterministic methods are widely used in geographic information system based landslide susceptibility mapping. This paper compares the predictive capability of three different models, namely the Weight of Evidence, the Fuzzy Logic and SHALSTAB, for producing shallow earth slide susceptibility maps, to be included as informative layers in land use planning at a local level. The test site is an area of about 450 km2 in the northern Apennines of Italy where, in April 2004, rainfall combined with snowmelt triggered hundreds of shallow earth slides that damaged roads and other infrastructure. An inventory of the landslides triggered by the event was obtained from interpretation of aerial photos dating back to May 2004. The pre-existence of mapped landslides was then checked using earlier aerial photo coverage. All the predictive models were run on the same set of geo-environmental causal factors: soil type, soil thickness, land cover, possibility of deep drainage through the bedrock, slope angle, and upslope contributing area. Model performance was assessed using a threshold-independent approach (the ROC plot). Results show that global accuracy is as high as 0.77 for both statistical models, while it is only 0.56 for SHALSTAB. Besides the limited quality of input data over large areas, the relatively poorer performance of the deterministic model maybe also due to the simplified assumptions behind the hydrological component (steady-state slope parallel flow), which can be considered unsuitable for describing the hydrologic behavior of clay slopes, that are widespread in the study area.  相似文献   

18.
A new method for estimating shallow landslide susceptibility by combining Geographical Information System (GIS), nonparametric kernel density estimation and logistic regression is described. Specifically, a logistic regression is applied to predict the spatial distribution by estimating the probability of occurrence of a landslide in a 16 km2 area. For this purpose, a GIS is employed to gather the relevant sample information connected with the landslides. The advantages of pre-processing the explanatory variables by nonparametric density estimation (for continuous variables) and a reclassification (for categorical/discrete ones) are discussed. The pre-processing leads to new explanatory variables, namely, some functions which measure the favourability of occurrence of a landslide. The resulting model correctly classifies 98.55% of the inventaried landslides and 89.80% of the landscape surface without instabilities. New data about recent shallow landslides were collected in order to validate the model, and 92.20% of them are also correctly classified. The results support the methodology and the extrapolation of the model to the whole study area (278 km2) in order to obtain susceptibility maps.  相似文献   

19.
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20.
Landslides are common natural hazards in the seismically active North Anatolian Fault Zone of Turkey. Although seismic activity, heavy rainfall, channel incisions, and anthropogenic effects are commonly the main triggers of landslides, on March 17, 2005, a catastrophic large landslide in Sivas, northeastern of Turkey, the Kuzulu landslide, was triggered by snowmelt without any other precursor. The initial failure of the Kuzulu landslide was rotational. Following the rotational failure, the earth material in the zone of accumulation exhibited an extremely rapid flow caused by steep gradient and high water content. The Agnus Creek valley, where Kuzulu village is located, was filled by the earth-flow material and a landslide dam was formed on the upper part of Agnus Creek. The distance from the toe of the rotational failure down to the toe of the earth flow measured more than 1800 m, with about 12.5 million m3 of displaced earth material. The velocity of the Kuzulu landslide was extremely fast, approximately 6 m/s. The main purposes of this study are to describe the mechanism and the factors conditioning the Kuzulu landslide, to present its environmental impacts, and to produce landslide-susceptibility maps of the Kuzulu landslide area and its near vicinity. For this purpose, a detailed landslide inventory map was prepared and geology, slope, aspect, elevation, topographic-wetness index and stream-power index were considered as conditioning factors. During the susceptibility analyses, the conditional probability approach was used and a landslide-susceptibility map was produced. The landslide-susceptibility map will help decision makers in site selection and the site-planning process. The map may also be accepted as a basis for landslide risk-management studies to be applied in the study area.  相似文献   

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