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1.
The primary objective of landslide susceptibility mapping is the prediction of potential landslides in landslide-prone areas.The predictive power of a landslide susceptibility mapping model could be tested in an adjacent area of similar geoenvironmental conditions to find out the reliability.Both the 2008 Wenchuan Earthquake and the 2013 Lushan Earthquake occurred in the Longmen Mountain seismic zone,with similar topographical and geological conditions.The two earthquakes are both featured by thrust fault and similar seismic mechanism.This paper adopted the susceptibility mapping model of co-seismic landslides triggered by Wenchuan earthquake to predict the spatial distribution of landslides induced by Lushan earthquake.Six influencing parameters were taken into consideration: distance from the seismic fault,slope gradient,lithology,distance from drainage,elevation and Peak Ground Acceleration(PGA).The preliminary results suggested that the zones with high susceptibility of coseismic landslides were mainly distributed in the mountainous areas of Lushan,Baoxing and Tianquan counties.The co-seismic landslide susceptibility map was completed in two days after the quake and sent to the field investigators to provide guidance for rescue and relief work.The predictive power of the susceptibility map was validated by ROC curve analysis method using 2037 co-seismic landslides in the epicenter area.The AUC value of 0.710 indicated that the susceptibility model derived from Wenchuan Earthquake landslides showed good accuracy in predicting the landslides triggered by Lushan earthquake.  相似文献   

2.
Earthquake-triggered landslides are a major geological hazard in the eastern Tibetan Plateau, and have prolonged impact on earth surface processes and fluvial system. To determine how long co-seismic landslides affect basins, a massive number of landslides existing in Qionghai Lake Basin were investigated for landslide distribution characteristics and geomorphological evidences, with further comparison and analysis using historic seismic analog method. The landslides found in Qionghai Lake Basin showed clear features of seismic triggering with strongly controlled by Zemuhe fault. These landslides are still active at present. Some new slides generally occur in ancient slope failure zones causing serious secondary hazards in recent years. In this study we strengthen the idea that the landslides triggered by the 185o Xichang earthquake （Ms7.5） have long term activity and prolonged impact on the mountain disasters with a period of more than 16o years. Our results support growing evidence that coseismic landslides have a prolonged effect on secondary disasters in a basin, and invite more careful consideration of the relationship between current basin condition and landslide history for a longer period.  相似文献   

3.
为了阐明地震滑坡的运动特性并对其进行致灾距的预测,基于遥感影像解译和野外调查数据,借助经验公式法,分析了汶川地震滑坡水平最大运移距离L与前后缘高差H之间的相关性,给出了经验公式;探讨了不同滑坡之间滑程的差异与异常。结果表明:若已知H,可用L=aH+b或L=aHb对总位移进行预测初探;将视摩擦系数H/L=0.45作为汶川地震高速远程型滑坡的上限较合适;滑坡体积、源区破裂面积与L呈正相关,与H/L呈负相关;地震滑坡易发生在山脊线平行于断裂带、垂直于地震波传播方向的山体两侧;崩塌型滑坡易发前后缘高差范围在10~100m之间,大型高速远程型滑坡易发前后缘高差大于200m;滑坡源区易发坡度分布在25°51°之间,滑床坡降变化范围为0~58°,高速远程型滑坡的滑床坡降主要在8°20°之间;分析认为滑程差异和异常是距离效应、能量传递与岩体挡板效应、滚动润滑与气垫效应、体积与破裂面积效应、地质因子、地形因子、颗粒级配与颗粒流效应等因素综合作用的结果,考虑上述因素有益于滑坡-碎屑流致灾距的预测分析。   相似文献   

4.
The"5.12"Wenchuan earthquake in 2008 triggered a large number of co-seismic landslides.The rear boundary or cracks of co-seismic landslide are generally located at the steep free surface of thin or thick mountains.Dynamic process of this kind of landslides could be divided into two parts:the seismic dynamic response of the slope and the movement process of rock mass.Taking the Laoyingyan rockslide as an example,the amplification effect was studied by single-degree-of-freedom system analysis method.Besides,the dynamic process of landslide under seismic loading was simulated by the finite difference method(FDM)and discrete element method(DEM).The amplification coefficient of the rockslide to seismic wave is 1.25.The results show that the critical sliding surface of the Laoyingyan rockslide was formed at the 23 th seconds under the action of seismic wave.At the same time,tension failure occurred at the rear edge of the sliding mass and shear failure occurred at the front edge.The maximum displacement was 0.81 m and the initial velocity was 2.78 m/s.During the initiation process of the rockslide,the rock mass firstly broke down along the joints which are along the dip of the rock stratum,and then collapsed bodily along the secondary structural planes.In the process of movement,the maximum velocity of rock mass was 38.24 m/s.After that,the rock mass underwent multiple collisions,including contact,deceleration to 0 and speed recovery after rebound.Finally,due to the constant loss of energy,the rocks stopped and accumulated loosely at the foot of the slope.The longest distance of movement was about 494 m.Besides,the smaller the damping ratio,the farther the rock mass moved.Compared with the results without considering the amplification factor,the movement distance of landslide by considering the amplification factor was more accurate.The study of the Laoyingyan rockslide is helpful to strengthen our field identification of potential co-seismic rockslides.At the same time,understanding its movement and accumulation process can help us better predict the hazard scope of the co-seismic rockslides,and provide a reference for the design of treatment projects.  相似文献   

5.
The Ms 8.0 May 12,2008 Wenchuan earthquake triggered tens of thousands of landslides.The widespread landslides have caused serious casualties and property losses,and posed a great threat to post-earthquake reconstruction.A spatial database,inventoried 43,842 landslides with a total area of 632 km 2,was developed by interpretation of multi-resolution remote sensing images.The landslides can be classified into three categories:swallow,disrupted slides and falls;deep-seated slides and falls,and rock avalanches.The correlation between landslides distribution and the influencing parameters including distance from co-seismic fault,lithology,slope gradient,elevation,peak ground acceleration(PGA) and distance from drainage were analyzed.The distance from co-seismic fault was the most significant parameter followed by slope gradient and PGA was the least significant one.A logistic regression model combined with bivariate statistical analysis(BSA) was adopted for landslide susceptibility mapping.The study area was classified into five categories of landslide susceptibility:very low,low,medium,high and very high.92.0% of the study area belongs to low and very low categories with corresponding 9.0% of the total inventoried landslides.Medium susceptible zones make up 4.2% of the area with 17.7% of the total landslides.The rest of the area was classified into high and very high categories,which makes up 3.9% of the area with corresponding 73.3% of the total landslides.Although the susceptibility map can reveal the likelihood of future landslides and debris flows,and it is helpful for the rebuilding process and future zoning issues.  相似文献   

6.
以2003年千将坪滑坡事件为例,基于地震信号分析大型高速滑坡启动之后的滑体运动特性。通过国家地震台网采集因滑坡激发产生的地震信号,反演得到滑坡区域的受力-时间函数,再经由时频分析划分滑坡期间的子事件,进而推导滑体的运动参数并还原滑坡过程。结果显示,由地震信号反演所求得的滑床坡度、滑坡方向以及滑体位移等数值与现场勘踏所得数据相符;同时,通过对滑坡子事件的分析,可分辨出因对岸河堤阻挡而产生的部分滑体反倾过程,从而还原较完整的滑坡过程。  相似文献   

7.
Field investigations and aerial photography after the earthquake of May 12,2008 show a large number of geo-hazards in the zone of extreme earthquake effects.In particular,landslides and debris flows,the geo-hazards that most threaten post-disaster reconstruction,are widely distributed.We describe the characteristics of these geo-hazards in Beichuan County using high-resolution remote sensing of landslide distribution,and the relationships between the area and volume of landslides and the peak-discharges of debris flows both pre-and post-earthquake.The results show:1) The concentration(defined as the number of landslide sources per unit area:Lc) of earthquaketriggered landslides is inversely correlated with distance from the earthquake(DF) fault.The relationship is described by the following equation:Lc = 3.2264exp(-0.0831DF)(R2 = 0.9246);2) 87 % of the earthquake-triggered landslides were less than 15×104 m2 in area,and these accounted only for 50% of the total area;84% of the landslide volumes were less than 60×104 m3,and these accounted only for 50% of the total volume.The probability densities of the area and volume distributions are correlated:landslide abundance increases with landslide area and volume up to maximum values of 5 × 104 m2 and 30 × 104 m3,respectively,and then decreases exponentially.3) The area(AL) and volume(VL) of earthquake-triggered landslides are correlated as described with the following equation:VL=6.5138AL1.0227(R2 = 0.9131);4) Characteristics of the debris flows changed after the earthquake because of the large amount of landslide material deposited in the gullies.Consequently,debris flow peak-discharge increased following the earthquake as described with the following equation:Vpost = 0.8421Vpre1.0972(R2 = 0.9821)(Vpre is the peak discharge of pre-earthquake flows and the Vpost is the peak discharge of post-earthquake flows).We obtained the distribution of the landslides based on the above analyses,as well as the magnitude of both the landslides and the post-earthquake debris flows.The results can be useful for guiding post-disaster reconstruction and recovery efforts,and for the future mitigation of these geo-hazards.However,the equations presented are not recommended for use in site-specific designs.Rather,we recommend their use for mapping regional seismic landslide hazards or for the preliminary,rapid screening of sites.  相似文献   

8.
地震滑坡解译是震后重建的重要基础工作,主要通过室内人工遥感解译和室外野外调查确定。地震滑坡相比其他地物来说更为复杂,很难通过简单指数识别。室内遥感解译通过滑坡后壁、侧壁和堆积等纹理特征进行识别,大面积同震滑坡解译工作往往耗费大量人力和物力,且耗时长,难以满足灾害应急需求。本研究利用U-net神经网络模型,结合Google Earth Engine（GEE）云平台和人工智能学习平台Tensorflow,以地震局解译的汶川滑坡作为样本数据,以震后30 m分辨率的Landsat影像、高程、坡度以及NDVI数据作为模型输入参数,自动识别并获取了汶川地震后的同震滑坡数据,同时比较了不同参数组合情况下U-net神经网络模型的分割识别精度。研究表明：① U-net模型可以用于以Landsat影像为基础数据的同震滑坡快速自动识别;② 随着高程、坡度以及NDVI等输入参数增加,模型分割精度在逐渐提高,但假阳性结果也会出现增多,震后滑坡影像+高程+坡度+NDVI的输入参数组合精度最高;③ 在细节上,模型在多参数组合的情况下,大型滑坡能够很好被识别,一些较小型的滑坡受制于影像分辨率的影响,分割精度较差。为了更好识别小型滑坡,后续研究可能需提高影像的分辨率。此外,GEE云平台大大提高了训练样本获取的效率,为科研人员快速进行基于神经网络与遥感数据的地物识别研究提供了条件。  相似文献   

9.
The 5.12 Wenchuan Earthquake in 2008 induced hundreds of large-scale landslides. This paper systematically analyzes 112 large-scale landslides (surface area > 50000 m2), which were identified by interpretation of remote sensing imagery and field investigations. The analysis suggests that the distribution of large-scale landslides is affected by the following four factors: (a) distance effect: 80% of studied large-scale landslides are located within a distance of 5 km from the seismic faults. The farther the distance to the faults, the lower the number of large-scale landslides; (b) locked segment effect: the large-scale landslides are mainly located in five concentration zones closely related with the crossing, staggering and transfer sections between one seismic fault section and the next one, as well as the end of the NE fault section. The zone with the highest concentration was the Hongbai-Chaping segment, where a great number of large-scale landslides including the two largest landslides were located. The second highest concentration of large-scale landslides was observed in the Nanba-Donghekou segment at the end of NE fault, where the Donghekou landslide and the Woqian landslide occurred; (c) Hanging wall effect: about 70% of the large-scale landslides occurred on the hanging wall of the seismic faults; and (d) direction effect: in valleys perpendicular to the seismic faults, the density of large-scale landslides on the slopes facing the seismic wave is obviously higher than that on the slopes dipping in the same direction as the direction of propagation of the seismic wave. Meanwhile, it is found that the sliding and moving directions of large-scale landslides are related to the staggering direction of the faults in each section. In Qingchuan County where the main fault activity was horizontal twisting and staggering, a considerable number of landslides showed the feature of sliding and moving in NE direction which coincides with the staggering direction of the seismic faults.  相似文献   

10.
Roads constructed in fragile Siwaliks are prone to large number of instabilities. Bhalubang–Shiwapur section of Mahendra Highway lying in Western Nepal is one of them. To understand the landslide causative factor and to predict future occurrence of the landslides, landslide susceptibility mapping(LSM) of this region was carried out using frequency ratio(FR) and weights-of-evidence(W of E) models. These models are easy to apply and give good results. For this, landslide inventory map of the area was prepared based on the aerial photo interpretation, from previously published/unpublished reposts, and detailed field survey using GPS. About 332 landslides were identified and mapped, among which 226(70%) were randomly selected for model training and the remaining 106(30%) were used for validation purpose. A spatial database was constructed from topographic, geological, and land cover maps. The reclassified maps based on the weight values of frequency ratio and weights-of-evidence were applied to get final susceptibility maps. The resultant landslide susceptibility maps were verified andcompared with the training data, as well as with the validation data. From the analysis, it is seen that both the models were equally capable of predicting landslide susceptibility of the region(W of E model(success rate = 83.39%, prediction rate = 79.59%); FR model(success rate = 83.31%, prediction rate = 78.58%)). In addition, it was observed that the distance from highway and lithology, followed by distance from drainage, slope curvature, and slope gradient played major role in the formation of landsides. The landslide susceptibility maps thus produced can serve as basic tools for planners and engineers to carry out further development works in this landslide prone area.  相似文献   

11.
The Niumiangou landslide was the largest landslide triggered by the 2008 Wenchuan earthquake, which was significantly affected by the amplification effect of seismic acceleration. The ringshear experiments indicated that the materials in the source area of the Niumiangou landslide were subjected to friction degradation under a big shear displacement, which may result in rapid movement of the landslide. In order to better understand the landslide movement and study the effect of the friction degradation on movement mechanisms, the dynamic process of Niumiangou landslide was simulated with a new numerical method, which combines the finite difference method(FDM) and the discontinuous deformation analysis(DDA). First, the FDM was used to study the initiation time, amplification effect and velocity of the landslide. Afterwards, these initiation velocities were applied to the blocks in the DDA model by corresponding coordination in the FDM model. A displacementdependent friction model of the sliding surface was incorporated into DDA code to further understand the kinetic behavior of the landslide. The results show that the displacement-dependent friction strongly decreases the friction coefficient of sliding surface under a big displacement, which can obviously promote the run-out and velocity of landslide. The model output well matches the topographic map formed by the landslide. This implies that the proposed model can be applied to the simulation of earthquake-induced landslides with amplification effect, and the friction degradation model is important to clarify the movement mechanism of high-speed and long-distance landslides.  相似文献   

12.
滑坡堰塞坝是由斜坡失稳堵塞河道而形成的天然坝体,且易溃坝诱发洪水,对沿岸群众生命财产构成巨大的威胁。为提升主动减灾防灾能力,急需构建了一种快速预测与判断滑坡堵江成坝能力的方法。通过文献资料查阅,结合遥感技术,提取了70处典型滑坡的地貌特征参数,其中50处为堵江成坝滑坡。运用K-S检验和M-W U检验方法分析了滑坡地貌特征因子的敏感性,利用Boruta算法确定了因子重要度,筛选了滑坡体积、面积、高差、长度及河宽共5个地貌特征参数。基于此,利用Bayes判别法与逻辑回归方法,分别建立了滑坡堰塞坝形成的预测模型,准确率超过90%。选取高重要度且差异显著的因子,利用比值法建立了滑坡堵江成坝阈值判据,实现了滑坡堰塞坝形成的快速判定。统计不同诱因下滑坡地貌特征,对比V-Wr经验公式,确定了滑坡堰塞坝形成与诱因间的关系,为进一步构建不同诱因下滑坡堰塞坝形成预测模型提供了技术支撑。   相似文献   

13.
The loess area in the northern part of Baoji City, Shaanxi Province, China is a region with frequently landslide occurrences. The main aim of this study is to quantitatively predict the extent of landslides using the index of entropy model(IOE), the support vector machine model(SVM) and two hybrid models namely the F-IOE model and the F-SVM model constructed by fractal dimension. First, a total of 179 landslides were identified and landslide inventory map was produced, with 70%(125) of the landslides which was optimized by 10-fold crossvalidation being used for training purpose and the remaining 30%(54) of landslides being used for validation purpose. Subsequently, slope angle, slope aspect, altitude, rainfall, plan curvature, distance to rivers, land use, distance to roads, distance to faults, normalized difference vegetation index(NDVI), lithology, and profile curvature were considered as landslide conditioning factors and all factor layers were resampled to a uniform resolution. Then the information gain ratio of each conditioning factors was evaluated. Next, the fractal dimension for each conditioning factors was calculated and the training dataset was used to build four landslide susceptibility models. In the end, the receiver operating characteristic(ROC) curves and three statistical indexes involving positive predictive rate(PPR), negative predictive rate(NPR) and accuracy(ACC) were applied to validate and compare the performance of these four models. The results showed that the F-SVM model had the highest PPR, NPR, ACC and AUC values for training and validation datasets, respectively, followed by the F-IOE model.Finally, it is concluded that the F-SVM model performed best in all models, the hybrid model built by fractal dimension has advantages than original model, and can provide reference for local landslide prevention and decision making.  相似文献   

14.
Analysis of landslide dam geometries   总被引：2，自引：1，他引：1  
The geometry of a landslide dam is an important component of evaluating dam stability. However, the geometry of a natural dam commonly cannot be obtained immediately with field investigations due to their remote locations. A rapid evaluation model is presented to estimate the geometries of natural dams based on the slope of the stream, volume of landslides, and the properties of the deposit. The proposed model uses high resolution satellite images to determine the geometry of the landside dam. These satellite images are the basic information to a preliminary stability analysis of a natural dam. This study applies the proposed method to two case studies in Taiwan. One is the earthquake-induced Lung-Chung landslide dam in Taitung, and the second is the rainfall-induced Shih-Wun landslide dam in Pingtung.  相似文献   

15.
Nepal was hit by a 7.8 magnitude earthquake on 25th April, 2015. The main shock and many large aftershocks generated a large number of coseismic landslips in central Nepal. We have developed a landslide susceptibility map of the affected region based on the coseismic landslides collected from remotely sensed data and fieldwork, using bivariate statistical model with different landslide causative factors. From the investigation, it is observed that most of the coseismic landslides are independent of previous landslides. Out of 3,716 mapped landslides, we used 80% of them to develop a susceptibility map and the remaining 20% were taken for validating the model. A total of 11 different landslide-influencing parameters were considered. These include slope gradient, slope aspect, plan curvature, elevation, relative relief, Peak Ground Acceleration (PGA), distance from epicenters of the mainshock and major aftershocks, lithology, distance of the landslide from the fault, fold, and drainage line. The success rate of 87.66% and the prediction rate of 86.87% indicate that the model is in good agreement between the developed susceptibility map and the existing landslides data. PGA, lithology, slope angle and elevation have played a major role in triggering the coseismic mass movements. This susceptibility map can be used for relocating the people in the affected regions as well as for future land development.  相似文献   

16.
《山地科学学报》2020,17(2):358-372
The earthquake that occurred on May 12, 2008, in Wenchuan County aroused a great deal of research on co-seismic landslide susceptibility assessment, but there is still a lack of an evaluation method that considers the activity state of the landslide itself. Therefore, this paper establishes a new susceptibility evaluation model that superimposes the active landslide state based on previous susceptibility evaluation models. Based on a multi-phase landslide database, the probabilistic approach was used to evaluate landslide susceptibility in the Miansi town over many years. We chose the elevation, slope, aspect, and distance from the channel as trigger factors and then used the probability comprehensive discrimination method to calculate the probability of landslide occurrence. Then, the susceptibility results of each period were calculated by superposition with the activity rate. The results show that between 2008 and 2014, the proportion of areas with low landslide susceptibility in the study area was the largest, and the proportionof areas with the highest susceptibility was minimal. The landslide area with highest susceptibility gradually decreased from 2014 to 2017. However, in 2017, 15.06% of the area was still with high susceptibility, and relevant disaster prevention and reduction measures should be taken in these areas. The larger area under the receiver operating characteristic curve(AUC) indicates that the results of the landslide susceptibility assessment in this study are more objective and reliable than those of previous models. The difference in the AUC values over many years shows that the accuracy of the evaluation results of this model is not constant, and a greater number of landslides or higher landslide activity corresponds to a higher accuracy of the evaluation results.  相似文献   

17.
Guizhou Karst Plateau is located at the center of the karst region in Asia, where landslides are a typical disaster. Affected by the local karst environment, the landslides in this region have their own characteristics. In this study, 3975 landslide records from inventories of the Guizhou karst plateau are studied. The geographical detector method is used to detect the dominant casual factor and predominant multi-factor combinations for the local landslides. The results show that landslides are prone to areas on slopes between 10° and 35°, of clay rock, in close proximity to gullies, and especially in areas of moderate vegetation, dryland, and mild rocky desertification. Continuous precipitation over 10 days has a great effect on landslide occurrence. Compared with the individual factors, the impact of two-factor interaction has greater explanatory power for landslide volume. The volume of earthquake-induced landslides is predominantly controlled by the interactions of faults and slopes, while that of humaninduced landslides is affected by the interactions of land cover and hydrological conditions. For rainfallinduced landslides, the dominant interactions vary in different regions. In the central karst basin, the interactions between faults and precipitation can explain over 90% of the variations in landslide volumes. In the southern hilly karst region, the interactions between lithology and slope can explain over 71% of the variations in landslide volume and those between fault and land-use can explain 50% of the variations of the landslide volumes in the northeastern mountainous karst region.  相似文献   

18.
Tibetan Plateau is known as the roof of the world. Due to the continuous uplift of the Tibetan Plateau, many active fault zones are present. These active fault zones such as the Anninghe fault zone have a significant influence on the formation of special geomorphology and the distribution of geological hazards at the eastern edge of the Tibetan Plateau. The Anninghe fault zone is a key part of the Y-shaped fault pattern in the Sichuan-Yunnan block of China. In this paper, high-resolution topographic data, multitemporal remote sensing images, numerical calculations, seismic records, and comprehensive field investigations were employed to study the landslide distribution along the active part of the Anninghe. The influence of active faults on the lithology, rock mass structures and slope stress fields were also studied. The results show that the faults within the Anninghe fault zone have damaged the structure and integrity of the slope rock mass, reduced the mechanical strength of the rock mass and controlled the slope failure modes. The faults have also controlled the stress field, the distribution of the plastic strain zone and the maximum shear strain zone of the slope, thus have promoted the formation and evolution of landslides. We find that the studied landslides are linearly distributed along the Anninghe fault zone, and more than 80% of these landslides are within 2-3 km of the fault rupture zone. Moreover, the Anninghe fault zone provides abundant substance for landslides or debris flows. This paper presents four types of sliding mode control of the Anninghe fault zone, e.g., constituting the whole landslide body, controlling the lateral boundary of the landslide, controlling the crown of the landslide, and constituting the toe of the landslide. The results presented merit close attention as a valuable reference source for local infrastructure planning and engineering projects.  相似文献   

19.
利用湟源台四分量钻孔应变观测的分钟值、1 sps、10 sps和100 sps四种不同采样率的观测数据,通过自检分析、同震应变阶分析和频谱分析等方法研究青海玛多M7.4地震同震变化特征。研究结果表明,分钟采样记录的地震波信息缺失严重,用分钟采样数据进行地震波初动、同震变化幅度等研究将会得到信度较低的结论;采样率越高,记录应变地震波信息的能力越强,但100 sps采样和10 sps采样结果相差不大,10 sps采样已能记录到比较全面的应变地震波信息;同震应变阶的变化性质和变化幅度与采样率无关;未来布设四分量钻孔应变仪时,建议应将采样率至少提高至1 sps。  相似文献   

20.
China-Pakistan Economic Corridor(CPEC)is a framework of regional connectivity,which will not only benefit China and Pakistan but will have positive impact on Iran,Afghanistan,India,Central Asian Republic,and the region.The surrounding area in CPEC is prone to frequent disruption by geological hazards mainly landslides in northern Pakistan.Comprehensive landslide inventory and susceptibility assessment are rarely available to utilize for landslide mitigation strategies.This study aims to utilize the high-resolution satellite images to develop a comprehensive landslide inventory and subsequently develop landslide susceptibility maps using multiple techniques.The very high-resolution(VHR)satellite images are utilized to develop a landslide inventory using the visual image classification techniques,historic records and field observations.A total of 1632 landslides are mapped in the area.Four statistical models i.e.,frequency ratio,artificial neural network,weights of evidence and logistic regression were used for landslide susceptibility modeling by comparing the landslide inventory with the topographic parameters,geological features,drainage and road network.The developed landslides susceptibility maps were verified using the area under curve(AUC)method.The prediction power of the model was assessed by the prediction rate curve.The success rate curves show 93%,92.8%,92.7%and 87.4%accuracy of susceptibility maps for frequency ratio,artificial neural network,weights of evidence and logistic regression,respectively.The developed landslide inventory and susceptibility maps can be used for land use planning and landslide mitigation strategies.  相似文献   

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