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1.
. 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.  相似文献   

2.
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   

3.
The purpose of this study is to produce landslide susceptibility map of a landslide-prone area (Daguan County, China) by evidential belief function (EBF) model and weights of evidence (WoE) model to compare the results obtained. For this purpose, a landslide inventory map was constructed mainly based on earlier reports and aerial photographs, as well as, by carrying out field surveys. A total of 194 landslides were mapped. Then, the landslide inventory was randomly split into a training dataset; 70% (136 landslides) for training the models and the remaining 30% (58 landslides) was used for validation purpose. Then, a total number of 14 conditioning factors, such as slope angle, slope aspect, general curvature, plan curvature, profile curvature, altitude, distance from rivers, distance from roads, distance from faults, lithology, normalized difference vegetation index (NDVI), sediment transport index (STI), stream power index (SPI), and topographic wetness index (TWI) were used in the analysis. Subsequently, landslide susceptibility maps were produced using the EBF and WoE models. Finally, the validation of landslide susceptibility map was accomplished with the area under the curve (AUC) method. The success rate curve showed that the area under the curve for EBF and WoE models were of 80.19% and 80.75% accuracy, respectively. Similarly, the validation result showed that the susceptibility map using EBF model has the prediction accuracy of 80.09%, while for WoE model, it was 79.79%. The results of this study showed that both landslide susceptibility maps obtained were successful and would be useful for regional spatial planning as well as for land cover planning.  相似文献   

4.
The main purpose of this paper is to present the use of multi-resource remote sensing data, an incomplete landslide inventory, GIS technique and logistic regression model for landslide susceptibility mapping related to the May 12, 2008 Wenchuan earthquake of China. Landslide location polygons were delineated from visual interpretation of aerial photographs, satellite images in high resolutions, and verified by selecting field investigations. Eight factors, including slope angle, slope aspect, elevation, distance from drainages, distance from roads, distance from main faults, seismic intensity and lithology were selected as controlling factors for earthquake-triggered landslide susceptibility mapping. Qualitative susceptibility analyses were carried out using the map overlaying techniques in GIS platform. The validation result showed a success rate of 82.751 % between the susceptibility probability index map and the location of the initial landslide inventory. The predictive rate of 86.930 % was obtained by comparing the additional landslide polygons and the landslide susceptibility probability index map. Both the success rate and the predictive rate show sufficient agreement between the landslide susceptibility map and the existing landslide data, and good predictive power for spatial prediction of the earthquake-triggered landslides.  相似文献   

5.
Ardesen is a settlement area which has been significantly damaged by frequent landslides which are caused by severe rainfalls and result in many casualties. In this study a landslide susceptibility map of Ardesen was prepared using the Analytical Hierarchy Process (AHP) with the help of Geographical Information Systems (GIS) and Digital Photogrametry Techniques (DPT). A landslide inventory, lithology–weathering, slope, aspect, land cover, shear strength, distance to the river, stream density and distance to the road thematics data layers were used to create the map. These layer maps are produced using field, laboratory and office studies, and by the use of GIS and DPT. The landslide inventory map is also required to determine the relationship between these maps and landslides using DPT. In the study field in the Hemsindere Formation there are units that have different weathering classes, and this significantly affects the shear strength of the soil. In this study, shear strength values are calculated in great detail with field and laboratory studies and an additional layer is evaluated with the help of the stability studies used to produce the landslide susceptibility map. Finally, an overlay analysis is carried out by evaluating the layers obtained according to their weight, and the landslide susceptibility map is produced. The study area was classified into five classes of relative landslide susceptibility, namely, very low, low, moderate, high, and very high. Based on this analysis, the area and percentage distribution of landslide susceptibility degrees were calculated and it was found that 28% of the region is under the threat of landslides. Furthermore, the landslide susceptibility map and the landslide inventory map were compared to determine whether the models produced are compatible with the real situation resulting in compatibility rate of 84%. The total numbers of dwellings in the study area were determined one by one using aerial photos and it was found that 30% of the houses, with a total occupancy of approximately 2,300 people, have a high or very high risk of being affected by landslides.  相似文献   

6.
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   

7.
This paper presents the results of geographical information system (GIS)-based landslide susceptibility mapping in Ayvalık, western Turkey using multi-criteria decision analysis. The methodology followed in the study includes data production, standardization, and analysis stages. A landslide inventory of the study area was compiled from aerial photographs, satellite image interpretations, and detailed field surveys. In total, 45 landslides were recorded and mapped. The areal extent of the landslides is 1.75 km2. The identified landslides are mostly shallow-seated, and generally exhibit progressive character. They are mainly classified as rotational, planar, and toppling failures. In all, 51, 45, and 4% of the landslides mapped are rotational, planar, and toppling types, respectively. Morphological, geological, and land-use data were produced using existing topographical and relevant thematic maps in a GIS framework. The considered landslide-conditioning parameters were slope gradient, slope aspect, lithology, weathering state of the rocks, stream power index, topographical wetness index, distance from drainage, lineament density, and land-cover and vegetation density. These landslide parameters were standardized in a common data scale by fuzzy membership functions. Then, the degree to which each parameter contributed to landslides was determined using the analytical hierarchy process method, and the weight values of these parameters were calculated. The weight values obtained were assigned to the corresponding parameters, and then the weighted parameters were combined to produce a landslide susceptibility map. The results obtained from the susceptibility map were evaluated with the landslide location data to assess the reliability of the map. Based on the findings obtained in this study, it was found that 5.19% of the total area was prone to landsliding due to the existence of highly and completely weathered lithologic units and due to the adverse effects of topography and improper land use.  相似文献   

8.
浙西梅雨滑坡易发性评价模型对比   总被引：1，自引：0，他引：1       下载免费PDF全文
我国目前滑坡易发性评价研究主要集中在西南地区,对东南部降雨引发特别是梅雨引发的滑坡研究较少.选取浙江省西北部梅雨控制区淳安县为研究区,通过遥感解译结合野外详细调查,共确定滑坡596处,并建立滑坡编录数据库.选取高程、坡向、坡度、曲率、工程岩组、断层、道路、建设用地、植被等9个滑坡影响因子,基于GIS栅格分析方法,采用人工神经网络(ANN)、logistic回归和信息量3种评价模型,分别对32种不同影响因子组合进行滑坡易发性对比评价,得到滑坡易发性指数图.应用评价曲线下面积AUC(area under curve)对评价结果进行检验,ANN、logistic回归和信息量3种模型的正确率分别是93.75%、89.76%和90.06%;采用淳安县2014年梅汛期发生的13处滑坡作为预测样本,3种模型预测率分别是94.75%、94.33%和77.21%.上述分析结果表明:ANN模型优于其他两者.以ANN模型评价结果指数图为基础进行易发性分区,采用滑坡强度指标进行分区结果检验,滑坡强度值由易发性低、较低、中和高依次递增,说明分区结果合理.研究成果可以为浙西降雨型滑坡特别是由梅雨引发滑坡的易发性评价提供参考.   相似文献   

9.
The purpose of this study is to present a weighting method, integrating subjective weight with objective weight, for landslides susceptibility mapping based on geographical information system (GIS). First, the landslide inventory, aspect, slope, proximity to streams of drainage network, proximity to railway, proximity to road, topography, elevation, lithology, tectonic activity and annual precipitation, including their subclasses, were taken as independent landslide causal factors. Second, objective weights of the causal factors were calculated according to the landslide area density based on entropy weighting method, and key factors were selected according to the rank of the objective weights. Third, trapezoidal fuzzy number weighting approach was used to assess the sub-classes of each key factor. Finally, a case study was carried out in Guizhou province, China. A landslide susceptibility map was created using weighted linear combination model based on GIS. Using a predicted map of probability, the study area was classified into four categories of landslide susceptibility: low, moderate, moderate-high, and high.  相似文献   

10.
Owing to fragile geo-morphology, extreme climatic conditions, and densely populated settlements and rapid development activities, West Java Province is the most landslide hazardous area in Indonesia. So, a landslide risk map for this province bears a great importance such as for land-use planning. It is however widely accepted that landslide risk analysis is often difficult because of the difficulties involved in landslide hazard assessment and estimation of consequences of future landslide events. For instance, lack of multi-temporal inventory map or records of triggering events is often a major problem in landslide hazard mapping. In this study, we propose a simple technique for converting a landslide susceptibility map into a landslide hazard map, which we have employed for landslide risk analysis in one ideally hazardous part of volcanic mountains in West Java Province. The susceptibility analysis was carried out through correlation between past landslides and eight spatial parameters related to instability, i.e. slope, aspect, relative relief, distance to river, geological units, soil type, land use and distance to road. The obtained susceptibility map was validated using cross-time technique, and was collaborated with the frequency-area statistics to respond to ‘when landslide will occur’ and ‘how large it will be’. As for the judgment of the consequences of future landslides, expert opinion was used considering available literature and characteristic of the study area. We have only considered economic loss in terms of physical damage of buildings, roads and agricultural lands for the landslide risk analysis. From this study, we understand the following: (1) the hazard map obtained from conversion of the susceptibility map gives spatial probability and the area of an expected landslide will be greater than 500m2 in the next 2 years, (2) the landslide risk map shows that 24% of the total area is in high risk; 30% in moderate risk; 45% in low risk and no risk covers only 1% of the total area, and (3) the loss will be high in agricultural lands, while it will be low in the road structures and buildings.  相似文献   

11.
In this study, we present a landslide susceptibility assessment carried out after the devastating 2008 Wenchuan earthquake. For the Zhouqu segment in the Bailongjiang basin in north-western China landslide susceptibility was computed by a logistic regression method. This region has been experiencing landslides for a long time, and numerous additional slope failures were triggered by the 2008 Wenchuan earthquake. The data used for this study consists of slope failures attributed to the 2008 earthquake, the 878 post Wenchuan earthquake landslides and collapses inventory build up by combination the field investigation, monoscopic manual interpretation, image classification and texture analysis using SPOT 5 and ALOS remote-sensing image data. All data derived from remote sensing images are validated during field investigations. The landslide pre-disposing factor database was constructed. A digital elevation model (DEM) with a 30 × 30 m resolution, orthophotos, geological and land-use maps and information on peak ground acceleration data from the 2008 earthquake is used. The statistical analysis of the relation between Wencuan earthquake-triggered landslides and pre-disposing factors show the great influence of lithological and topographical conditions for earthquake-triggered slope failures. The quality of susceptibility mapping was validated by splitting the study area into a training and validation set. The prediction capability analysis showed that the landslide susceptibility map could be used for land planning as well as emergency planning by local authorities in this region.  相似文献   

12.
The article draws a comparison between different ways of landslide geometry interpretation in the scope of the statistical landslide hazard and risk assessment processing. The landslides are included as a major input variable, which are compared with all of the input parametric factors. Based on the above comparison the input data are classified and the final map of landslide susceptibility is constructed. Methodology of multivariate conditional analysis has been used for the construction of final maps. Unique condition units was developed by combination of geological map (lithological units) and slope angle map. Lithological units were derived from geological map and subsequently reclassified into 22 classes. Slope angle map was calculated from digital elevation model (contour map at a scale 1:10,000) and reclassified into nine classes. As a case study, a wide area of Horná Súča (western Slovakia) strongly affected by landsliding (predominantly made of Flysch) has been chosen. Spatial data in the form of parametric maps, as well as final statistical data set were processed in GIS GRASS environment. Four different approaches are used for landslides interpretation: (1) area of landslide body including accumulation zone, (2) area of depletion zone, (3) lines of elongated main scarps, (4) lines of main scarp upper edge. For each approach, a zoning map of landslide susceptibility was compiled and these were compared with each other. Depending on the interpretation approach, the final susceptibility zones are markedly different (in tens of percent).  相似文献   

13.
遗传算法优化BP网络在滑坡灾害预测中的应用研究   总被引：1，自引：0，他引：1       下载免费PDF全文
在陕西省宝鸡市附近长寿沟地区滑坡详细调查和遥感解译的基础上,完成了1∶10000滑坡编目图。通过使用GIS的水文分析功能,运用正反DEM技术,将长寿沟地区划分为216个自然斜坡单元,其中包括123个滑坡单元和93个未发生滑坡单元,分析滑坡发生与坡高、坡度、坡向、坡形、人类工程活动和水文地质条件影响因子之间的统计规律。利用经遗传算法优化后的BP神经网络对80个滑坡样本和40个未滑坡样本进行训练学习,然后再利用训练好的网络对预测样本进行评价分析。结果表明:43个已滑坡单元中只有3个被误判为无滑坡,正确率为9302%,53个未滑坡单元中有10个被预测为滑坡,正确率为8113%,总体正确率为8646%。通过对被预测为滑坡的10个斜坡单元进行分析,发现这些单元在坡形、坡高等影响因素的组合上已经具备了发生滑坡的条件,虽然目前没有发生滑坡,但作为潜在的滑坡危险区,可以为滑坡灾害预测预报和防灾减灾工作提供参考。  相似文献   

14.
The purpose of this study is to assess the susceptibility of landslides in parts of Western Ghats, Kerala, India, using a geographical information system (GIS). Landslide inventory of the area was made by detailed field surveys and the analysis of the topographical maps. The landslide triggering factors are considered to be slope angle, slope aspect, slope curvature, slope length, distance from drainage, distance from lineaments, lithology, land use and geomorphology. ArcGIS version 8.3 was used to manipulate and analyse all the collected data. Probabilistic-likelihood ratio was used to create a landslide susceptibility map for the study area. The result was validated using the Area under Curve (AUC) method and temporal data of landslide occurrences. The validation results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations. As the result, the success rate of the model was (84.46%) and the prediction rate of the model was (82.38%) shows high prediction accuracy. In the reclassified final landslide susceptibility zone map, 5.68% of the total area is classified as critical in nature. The landslide susceptibility map thus produced can be used to reduce hazards associated with landslides and to land cover planning.  相似文献   

15.
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   

16.
证据权法在区域滑坡危险性评价中的应用以贵州省为例   总被引：3，自引：0，他引：3  
以GIS为技术平台,采用证据权法对研究区进行了滑坡地质灾害危险性分析。综合分析历史滑坡数据及其环境因素和触发因素,数据源主要有地形图、DEM、地质图,选取地层岩性、构造、高程、坡度、坡向、地形起伏度、道路、水系作为危险性评价因子。首先应用ArcGIS软件对数据源进行处理,提取各个评价因子图层,并对每个图层进行分级、缓冲区分析等处理,建立若干证据层。然后将历史灾害点与评价因子进行空间关联分析,计算每个评价因子等级的权重,最后计算出评价单元的危险性指数,并将危险性分为极高危险区、高危险区、中等危险区、低危险区。采用成功率曲线法对证据权法评价精度进行验证,结果表明本次评价的精度为71%。利用历史滑坡数据对评价结果进行验证,结果显示评价结果与实际情况较为吻合,说明证据权可以客观定量地评价各影响因子对滑坡的影响程度,该方法应用于区域地质灾害危险性评价比较有效。  相似文献   

17.
Landslides are one of the most frequent and common natural hazards in many parts of Himalaya. To reduce the potential risk, the landslide susceptibility maps are one of the first and most important steps in the landslide hazard mitigation. Earth observation satellite and geographical information system-based techniques have been used to derive and analyse various geo-environmental parameters significant to landslide hazards. In this study, a bivariate statistics method was used for spatial modelling of landslide susceptibility zones. For this purpose, thematic layers including landslide inventory, geology, slope angle, slope aspect, geomorphology, slope morphology, drainage density, lineament and land use/land cover were used. A large number of landslide occurrences have been observed in the upper Tons river valley area of Western Himalaya. The result has been used to spatially classify the study area into zones of very high, high, moderate, low and very low landslide susceptibility zones. About 72% of active landslides have been observed to occur in very high and high hazard zones. The result of the analysis was verified using the landslide location data. The validation result shows significant agreement between the susceptibility map and landslide location. The result can be used to reduce landslide hazards by proper planning.  相似文献   

18.
In volcanic terrains, dormant stratovolcanoes are very common and can trigger landslides and debris flows continually along stream systems, thereby affecting human settlements and economic activities. It is important to assess their potential impact and damage through the use of landslide inventory maps and landslide models. In Mexico, numerous geographic information systems (GIS)-based applications have been used to represent and assess slope stability. However, there is no practical and standardized landslide mapping methodology under a GIS. This work provides an overview of the ongoing research project from the Institute of Geography at the National Autonomous University of Mexico that seeks to conduct a multi-temporal landslide inventory and produce a landslide susceptibility map by using GIS. The Río El Estado watershed on the southwestern flank of Pico de Orizaba volcano, the highest mountain in Mexico, is selected as a study area. The geologic and geomorphologic factors in combination with high seasonal precipitation, high degree of weathering, and steep slopes predispose the study area to landslides. The method encompasses two main levels of analysis to assess landslide susceptibility. First, the project aims to derive a landslide inventory map from a representative sample of landslides using aerial orthophotographs and field work. Next, the landslide susceptibility is modelled by using multiple logistic regression implemented in a GIS platform. The technique and its implementation of each level in a GISs-based technology is presented and discussed.  相似文献   

19.
Landslides are very common natural problems in the Black Sea Region of Turkey due to the steep topography, improper use of land cover and adverse climatic conditions for landslides. In the western part of region, many studies have been carried out especially in the last decade for landslide susceptibility mapping using different evaluation methods such as deterministic approach, landslide distribution, qualitative, statistical and distribution-free analyses. The purpose of this study is to produce landslide susceptibility maps of a landslide-prone area (Findikli district, Rize) located at the eastern part of the Black Sea Region of Turkey by likelihood frequency ratio (LRM) model and weighted linear combination (WLC) model and to compare the results obtained. For this purpose, landslide inventory map of the area were prepared for the years of 1983 and 1995 by detailed field surveys and aerial-photography studies. Slope angle, slope aspect, lithology, distance from drainage lines, distance from roads and the land-cover of the study area are considered as the landslide-conditioning parameters. The differences between the susceptibility maps derived by the LRM and the WLC models are relatively minor when broad-based classifications are taken into account. However, the WLC map showed more details but the other map produced by LRM model produced weak results. The reason for this result is considered to be the fact that the majority of pixels in the LRM map have high values than the WLC-derived susceptibility map. In order to validate the two susceptibility maps, both of them were compared with the landslide inventory map. Although the landslides do not exist in the very high susceptibility class of the both maps, 79% of the landslides fall into the high and very high susceptibility zones of the WLC map while this is 49% for the LRM map. This shows that the WLC model exhibited higher performance than the LRM model.  相似文献   

20.
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