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1.
Landslide hazard zonation mapping at regional level of a large area provides a broad trend of landslide potential zones. A macro level landslide hazard zonation for a small area may provide a better insight into the landslide hazards. The main objective of the present work was to carry out macro landslide hazard zonation mapping on 1：50,000 scale in an area where regional level zonation mapping was conducted earlier. In the previous work the regional landslide hazard zonation maps of Srinagar- Rudraprayag area of Garhwal Himalaya in the state of Uttarakhand were prepared using subjective and objective approaches. In the present work the landslide hazard zonation mapping at macro level was carried out in a small area using a Landslide Hazard Evaluation Factor rating scheme. The hazard zonation map produced by using this technique classifies the area into relative hazard classes in which the high hazard zones well correspond with high frequency of landslides. The results of this map when compared with the regional zonation maps prepared earlier show that application of the present technique identified more details of the hazard zones, which are broadly shown in the earlier zonation maps. 相似文献
2.
Landslides are the most common natural disaster in hilly terrain which causes changes in landscape and damage to life and property. The main objective of the present study was to carry out landslide hazard zonation mapping on 1：50,000 scale along ghat road section of Kolli hills using a Landslide Hazard Evaluation Factor（LHEF） rating scheme. The landslide hazard zonation map has been prepared by overlaying the terrain evaluation maps with facet map of the study area. The terrain evaluation maps include lithology, structure, slope morphometry, relative relief, land use and land cover and hydrogeological condition. The LHEF rating scheme and the Total Estimated Hazard（TEHD） were calculated as per the Bureau of Indian Standard（BIS） guidelines（IS： 14496（Part-2） 1998） for the purpose of preparation of Landslide Hazard Zonation（LHZ） map in mountainous terrains. The correction due to triggering factors such as seismicity, rainfall and anthropogenic activities were also incorporated with Total Estimated Hazard to get final corrected TEHD. The landslide hazard zonation map was classified as the high, moderate and low hazard zones along the ghat road section based on corrected TEHD. 相似文献
3.
Rudraprayag in Garhwal Himalayan division is one of the most vulnerable districts to landslides in India. Heavy rainfall, steep slope and developmental activities are important factors for the occurrence of landslides in the district. Therefore, specific assessment of landslide susceptibility and its accuracy at regional level is essential for disaster management and proper land use planning. The article evaluates effectiveness of frequency ratio, fuzzy logic and logistic regression models for assessing landslide susceptibility in Rudraprayag district of Uttarakhand state, India. A landslide inventory map was prepared and verified by field data. Fourteen landslide parameters and generated inventory map were utilized to prepare landslide susceptibility maps through frequency ratio, fuzzy logic and logistic regression models. Landslide susceptibility maps generated through these models were classified into very high, high, medium, low and very low categories using natural breaks classification. Receiver operating characteristics (ROC) curve, spatially agreed area approach and seed cell area index (SCAI) method were used to validate the landslide models. Validation results revealed that fuzzy logic model was found to be more effective in assessing landslide susceptibility in the study area. The landslide susceptibility map generated through fuzzy logic model can be best utilized for landslide disaster management and effective land use planning. 相似文献
4.
Uncertainty analysis on zonation maps of debris flow hazard in Yunnan Province, China 总被引：1，自引：0，他引：1
LIU Xi-lin 《中国地理科学(英文版)》2000,10(2):138-143
lINTRODUCTIONDebrisflowisoneofthesixprimarynaturalhaz-ards,whichinfluencesthedevelopmentofnationalso-cietyandeconomyinChina.Itsseverityissecondarytoflood,draught,earthquake,typhoon,butstrongerthanbiologicalhazards.Morethan3ooOodebrisflowcreeksarescatteredihthewholemountainousarea,andes-PeciallyconcentratedinsouthwestofChina.DebrisFlowInformationSystem(DFIS)operatedbytheInsti-tuteofMountainHazardsandEnvironmentoftheChi-neseAcademyofScienceshasalreadyestablishedadatabaseandcataloguec… 相似文献
5.
《山地科学学报》2015,(4)
A detailed landslide susceptibility map was produced in the Youfang catchment using logistic regression method with datasets developed for a geographic information system(GIS).Known as one of the most landslide-prone areas in China, the Youfang catchment of Longnan mountain region,which lies in the transitional area among QinghaiTibet Plateau, loess Plateau and Sichuan Basin, was selected as a representative case to evaluate the frequency and distribution of landslides.Statistical relationships for landslide susceptibility assessment were developed using landslide and landslide causative factor databases.Logistic regression(LR)was used to create the landslide susceptibility maps based on a series of available data sources: landslide inventory; distance to drainage systems, faults and roads; slope angle and aspect; topographic elevation and topographical wetness index, and land use.The quality of the landslide susceptibility map produced in this paper was validated and the result can be used fordesigning protective and mitigation measures against landslide hazards.The landslide susceptibility map is expected to provide a fundamental tool for landslide hazards assessment and risk management in the Youfang catchment. 相似文献
6.
Bailongjiang watershed in southern Gansu province, China, is one of the most landslide-prone regions in China, characterized by very high frequency of landslide occurrence. In order to predict the landslide occurrence, a comprehensive map of landslide susceptibility is required which may be significantly helpful in reducing loss of property and human life. In this study, an integrated model of information value method and logistic regression is proposed by using their merits at maximum and overcoming their weaknesses, which may enhance precision and accuracy of landslide susceptibility assessment. A detailed and reliable landslide inventory with 1587 landslides was prepared and randomly divided into two groups, (i) training dataset and (ii) testing dataset. Eight distinct landslide conditioning factors including lithology, slope gradient, aspect, elevation, distance to drainages, distance to faults, distance to roads and vegetation coverage were selected for landslide susceptibility mapping. The produced landslide susceptibility maps were validated by the success rate and prediction rate curves. The validation results show that the success rate and the prediction rate of the integrated model are 81.7 % and 84.6 %, respectively, which indicate that the proposed integrated method is reliable to produce an accurate landslide susceptibility map and the results may be used for landslides management and mitigation. 相似文献
7.
基于信息量模型和数据标准化的滑坡易发性评价 总被引：1，自引：0，他引：1
本文以北川曲山-擂鼓片区为研究区,将坡度、坡向、高程、地层、距断层的距离、距水系的距离和距道路的距离作为该区域滑坡易发性评价因子。采用信息量模型计算了各项评价因子的信息量值,并运用4种标准化模型对信息量值进行标准化处理。各评价因子的权重由层次分析法（AHP）确定。在GIS中将权重值和各评价因子的标准化信息量值,进行叠加计算得到区域滑坡总信息量值,并基于自然断点法对其进行重分类,将研究区划分为极高易发区、高易发区、中易发区、低易发区和极低易发区5级易发区。将基于4种标准化模型和信息量模型得到的滑坡易发性评价结果进行了对比分析,结果表明：基于最值标准化信息量模型的滑坡易发性评价结果的ROC曲线下面积AUC值为0.807,高于其余模型的AUC值,说明最值标准化信息量模型的滑坡易发性评价效果最好。极高易发区面积占研究区面积的20.03%,离断层和水系较近,主要分布地层为寒武系、志留系和三迭系。研究结果可为区内滑坡风险评价和灾害防治提供参考。 相似文献
8.
基于遥感(RS)和地理信息系统(GIS)技术,采用多层次分析(AHP)法,以北京密云水库上游部分库区为研究对象,根据库区实际情况,选取植被覆盖率、土壤类型、坡度、高程、降雨量、土地利用六种影响滑坡灾害发生的因素作为评价因子,对区域滑坡风险进行分析。同时,在ArcGIS的空间分析环境中运行权重叠加,将研究区域划分成无危险区、低危险区、中危险区、高危险区和极危险区。结果表明,研究区域内大部分地区比较稳定,最易发生滑坡的区域主要集中在密云水库东北部的河谷、山谷地带,呈零星状分布。 相似文献
9.
By using the landslide risk evaluating model and the advantages of GIS technology in image processing and space analysis, the relative landslide hazard and risk evaluating system of the new county site of Badong is built up. The system is mainly consisted of four subsystems: Information management subsystem, hazard assessment subsystem, vulnerability evaluation subsystem and risk prediction subsystem. In the system, landslide hazard assessment, vulnerability evaluation, risk predictions are carried out automatically based on irregular units. At last the landslide hazard and risk map of the study area is compiled. During the whole procedure, Matter-Element Model, Artificial Neural Network, and Information Model are used as assessment models. This system provides an effective way for the landslide hazard information management and risk prediction of each district in the Reservoir of Three Gorge Project. The result of the assessment can be a gist and ensure for the land planning and the emigration project in Badong. 相似文献
10.
Rainfall induced landslides are a common threat to the communities living on dangerous hill-slopes in Chittagong Metropolitan Area, Bangladesh. Extreme population pressure, indiscriminate hill cutting, increased precipitation events due to global warming and associated unplanned urbanization in the hills are exaggerating landslide events. The aim of this article is to prepare a scientifically accurate landslide susceptibility map by combining landslide initiation and runout maps. Land cover, slope, soil permeability, surface geology, precipitation, aspect, and distance to hill cut, road cut, drainage and stream network factor maps were selected by conditional independence test. The locations of 56 landslides were collected by field surveying. A weight of evidence (WoE) method was applied to calculate the positive (presence of landslides) and negative (absence of landslides) factor weights. A combination of analytical hierarchical process (AHP) and fuzzy membership standardization (weighs from 0 to 1) was applied for performing a spatial multi-criteria evaluation. Expert opinion guided the decision rule for AHP. The Flow-R tool that allows modeling landslide runout from the initiation sources was applied. The flow direction was calculated using the modified Holmgren’s algorithm. The AHP landslide initiation and runout susceptibility maps were used to prepare a combined landslide susceptibility map. The relative operating characteristic curve was used for model validation purpose. The accuracy of WoE, AHP, and combined susceptibility map was calculated 96%, 97%, and 98%, respectively. 相似文献
11.
《山地科学学报》2020,(3)
This work was to generate landslide susceptibility maps for the Three Gorges Reservoir(TGR) area, China by using different machine learning models. Three advanced machine learning methods, namely, gradient boosting decision tree(GBDT), random forest(RF) and information value(InV) models, were used, and the performances were assessed and compared. In total, 202 landslides were mapped by using a series of field surveys, aerial photographs, and reviews of historical and bibliographical data. Nine causative factors were then considered in landslide susceptibility map generation by using the GBDT, RF and InV models. All of the maps of the causative factors were resampled to a resolution of 28.5 m. Of the 486289 pixels in the area,28526 pixels were landslide pixels, and 457763 pixels were non-landslide pixels. Finally, landslide susceptibility maps were generated by using the three machine learning models, and their performances were assessed through receiver operating characteristic(ROC) curves, the sensitivity, specificity,overall accuracy(OA), and kappa coefficient(KAPPA). The results showed that the GBDT, RF and In V models in overall produced reasonable accurate landslide susceptibility maps. Among these three methods, the GBDT method outperforms the other two machine learning methods, which can provide strong technical support for producing landslide susceptibility maps in TGR. 相似文献
12.
Huiming TANG Yiping WU 《东北亚地学研究》2006,9(2):124-130
By using the landslide risk evaluating model and the advantages of GIS technology in image processing and space analysis, the relative landslide hazard and risk evaluating system of the new county site of Badong is built up. The system is mainly consisted of four subsystems： Information management subsystem, hazard as- sessment subsystem, vulnerability evaluation subsystem and risk prediction subsystem. In the system, landslide hazard assessment, vulnerability evaluation, risk predictions are carried out automatically based on irregular units. At last the landslide hazard and risk map of the study area is compiled. During the whole procedure, Matter-Element Model, Artificial Neural Network, ancl Information Model are used as assessment models. This system provides an effective way for the landslide hazard information management and risk prediction of each district in the Reservoir of Three Gorge Project. The result of the assessment can be a gist and ensure for the land planning and the emigration project in Badong. 相似文献
13.
Franny G. Murillo-García Mauro Rossi Francesca Ardizzone Federica Fiorucci Irasema Alcántara-Ayala 《山地科学学报》2017,14(7):1241-1261
In this paper, an attempt to analyse landslide hazard and vulnerability in the municipality of Pahuatlán, Puebla, Mexico, is presented. In order to estimate landslide hazard, the susceptibility,magnitude(area-velocity ratio) and landslide frequency of the area of interest were produced based on information derived from a geomorphological landslide inventory; the latter was generated by using very high resolution satellite stereo pairs along with information derived from other sources(Google Earth,aerial photographs and historical information).Estimations of landslide susceptibility were determined by combining four statistical techniques:(i) logistic regression,(ii) quadratic discriminant analysis,(iii) linear discriminant analysis, and(iv)neuronal networks. A Digital Elevation Model(DEM)of 10 m spatial resolution was used to extract the slope angle, aspect, curvature, elevation and relief.These factors, in addition to land cover, lithology anddistance to faults, were used as explanatory variables for the susceptibility models. Additionally, a Poisson model was used to estimate landslide temporal frequency, at the same time as landslide magnitude was obtained by using the relationship between landslide area and the velocity of movements. Then,due to the complexity of evaluating it, vulnerability of population was analysed by applying the Spatial Approach to Vulnerability Assessment(SAVE) model which considered levels of exposure, sensitivity and lack of resilience. Results were expressed on maps on which different spatial patterns of levels of landslide hazard and vulnerability were found for the inhabited areas. It is noteworthy that the lack of optimal methodologies to estimate and quantify vulnerability is more notorious than that of hazard assessments.Consequently, levels of uncertainty linked to landslide risk assessment remain a challenge to be addressed. 相似文献
14.
地质灾害威胁着山区人民生命财产安全, 进行地质灾害易发性评价有助于山区城镇进行规划与建设时规避灾害风险。以川东南古蔺县为例, 基于ArcGIS空间分析获取了研究区高程、坡度、岩性、斜坡结构、植被指数、距断层距离和距道路距离7个评价因子, 采用信息量模型分别对滑坡和崩塌灾害进行易发性评价后, 进一步利用ArcGIS单元统计功能对比了滑坡和崩塌易发性的信息量值, 选取相对更大的信息量值作为该栅格的最终信息量值, 绘制了研究区综合地质灾害易发性图, 利用自然断点法将古蔺县按信息量值的大小划分为极低、低、中、高和极高易发区。结果表明: 地质灾害主要分布在断层和道路附近, 断层和人类工程活动是造成研究区地质灾害频发的主要原因; 高易发区与极高易发区面积之和为1 315.62 km2, 占全区总面积的41.32%;预测模型性能经ROC曲线检验, AUC值为0.812 5, 说明栅格最大值法预测的古蔺县综合地灾易发性效果良好。 相似文献
15.
《山地科学学报》2015,(6)
Ethiopia has a mountainous landscape which can be divided into the Northwestern and Southeastern plateaus by the Main Ethiopian Rift and Afar Depression. Debre Sina area is located in Central Ethiopia along the escarpment where landslide problem is frequent due to steep slope, complex geology, rift tectonics, heavy rainfall and seismicity. In order to tackle this problem, preparing a landslide susceptibility map is very important. For this, GISbased frequency ratio(FR) and logistic regression(LR) models have been applied using landslide inventory and the nine landslide factors(i.e. lithology, land use, distance from river fault, slope, aspect, elevation, curvature and annual rainfall). Database construction, weighting each factor classes or factors, preparing susceptibility map and validation were the major steps to be undertaken. Both models require a rasterized landslide inventory and landslide factor maps. The former was classified into training and validation landslides. Using FR model, weights for each factor classes were calculated and assigned so that all the weighted factor maps can be added to produce a landslide susceptibility map. In the case of LR model, the entire study area is firstly divided into landslide and non-landslide areas using the training landslides. Then, these areas are changed into landslide and non-landslide points so as to extract the FR maps of the nine landslide factors. Then a linear relationship is established between training landslides and landslide factors in SPSS. Based on this relationship, the final landslide susceptibility map is prepared using LR equation. The success-rate and prediction-rate of FR model were 74.8% and 73.5%, while in case of LR model these were 75.7% and 74.5% respectively. A close similarity in the prediction and validation rates showed that the model is acceptable. Accuracy of LR model is slightly better in predicting the landslide susceptibility of the area compared to FR model. 相似文献
16.
Landslide susceptibility map delineates the potential zones for landslides occurrence. The paper presents a statistical approach through spatial data analysis in GIS for landslide susceptibility mapping in parts of Sikkim Himalaya. Six important causative factors for landslide occurrences were selected and corresponding thematic data layers were prepared in GIS. Topographic maps,satellite image,field data and published maps constitute the input data for thematic layer preparation. Numerical weights for different categories of these factors were determined based on a statistical approach and the weighted thematic layers were integrated in GIS environment to generate the landslide susceptibility map of the area. The landslide susceptibility map classifies the area into five different landslide susceptible zones i.e.,very high,high,moderate,low and very low. This map was validated using the existing landslide distribution in the area. 相似文献
17.
Landslide Susceptibility Mapping along Bhalubang–Shiwapur Area of Mid-Western Nepal Using Frequency Ratio and Conditional Probability Models 总被引：3，自引：3，他引：0
Amar Deep Regmi Kohki Yoshida Hamid Reza Pourghasemi Megh Raj DhitaL Biswajeet Pradhan 《山地科学学报》2014,11(5):1266-1285
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
18.
19.
Dynamic assessment of rainfall-induced shallow landslide hazard 总被引：1，自引：1，他引：0
The assessment of rainfall-induced shallow landslide hazards is a significant issue in the Three Gorges Reservoir area in China due to the rapid development of land in the past two decades. In this study, a probabilistic analysis method that combines TRIGRS and the point-estimate method for evaluating the hazards of shallow landslides have been proposed under the condition of rainfall over a large area. TRIGRS provides the transient infiltration model to analyze the pore water pressure during a rainfall. The point-estimate method is used to analyze the uncertainty of the soil parameters, which is performed in the geographic information system (GIS). In this paper, we use this method to evaluate the hazards of shallow landslides in Badong County, Three Gorges Reservoir, under two different types of rainfall intensity, and the results are compared with the field investigation. The results showed that the distribution of the hazard map is consistent with the observed landslides. To some extent, the distribution of the hazard map reflects the spatial and temporal distribution of the shallow landslide caused by rainfall. 相似文献
20.
There are many factors influencing landslide occurrence. The key for landslide control is to confirm the regional landslide hazard factors. The Cameron Highlands of Malaysia was selected as the study area. By bivariate statistical analysis method with GIS software the authors analyzed the relationships among landslides and environmental factors such as lithology, geomorphy, elevation, road and land use. Distance Evaluation Model was developed with Landslide Density （LD）. And the assessment of landslide hazard of Cameron Highlands was performed. The result shows that the model has higher prediction precision. 相似文献