Landslide hazard zonation using analytical hierarchy process along National Highway-3 in mid Himalayas of Himachal Pradesh,India

Landslide zonation studies emphasize on preparation of landslide hazard zonation maps considering major instability factors contributing to occurrence of landslides. This paper deals with geographic information system-based landslide hazard zonation in mid Himalayas of Himachal Pradesh from Mandi to Kullu by considering nine relevant instability factors to develop the hazard zonation map. Analytical hierarchy process was applied to assign relative weightages over all ranges of instability factors of the slopes in study area. To generate landslide hazard zonation map, layers in geographic information system were created corresponding to each instability factor. An inventory of existing major landslides in the study area was prepared and combined with the landslide hazard zonation map for validation purpose. The validation of the model was made using area under curve technique and reveals good agreement between the produced hazard map and previous landslide inventory with prediction accuracy of 79.08%. The landslide hazard zonation map was classified by natural break classifier into very low hazard, low hazard, moderate hazard, high hazard and very high landslide hazard classes in geographic information system depending upon the frequency of occurrence of landslides in each class. The resultant hazard zonation map shows that 14.30% of the area lies in very high hazard zone followed by 15.97% in high hazard zone. The proposed model provides the best-fit classification using hierarchical approach for the causative factors of landslides having complex structure. The developed hazard zonation map is useful for landslide preparedness, land-use planning, and social-economic and sustainable development of the region.     

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management

Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments,but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT)model and the K-means cluster algorithm to produce a regional landslide susceptibility map.Yanchang County,a typical landslide-prone area located in northwestern China,was taken as the area of interest to introduce the proposed application procedure.A landslide inventory containing 82 landslides was prepared and subse-quently randomly partitioned into two subsets:training data(70％landslide pixels)and validation data(30％landslide pixels).Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means clus-ter algorithm.The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC)curve)of the proposed model was the highest,reaching 0.88,compared with traditional models(support vector machine(SVM)=0.85,Bayesian network(BN)=0.81,frequency ratio(FR)=0.75,weight of evidence(WOE)=0.76).The landslide frequency ratio and fre-quency density of the high susceptibility zones were 6.76/km2 and 0.88/km2,respectively,which were much higher than those of the low susceptibility zones.The top 20％interval of landslide occurrence probability contained 89％of the historical landslides but only accounted for 10.3％of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without contain-ing more"stable"pixels.Therefore,the obtained susceptibility map is suitable for application to landslide risk management practices.     

Landslide hazard zoning along Himalayan Kaghan Valley of Pakistan��by integration of GPS, GIS, and remote sensing technology

This paper presents a methodology for developing a landslide hazard zonation map by integration of global positioning system (GPS), geographic information system (GIS), and remote sensing (RS) for Western Himalayan Kaghan Valley of Pakistan. The landslides in the study area have been located and mapped by using GPS. Eleven causative factors such as landuse, elevation, geology, rainfall intensity, slope inclination, soil, slope aspect, distances from main road, distances from secondary roads, and distances from main river and those from trunk streams were analyzed for occurrence of landslides. These factors were used with a modified form of pixel-based information value model to obtain landslide hazard zones. The matrix analysis was performed in remote sensing to produce a landslide hazard zonation map. The causative factors with the highest effect of landslide occurrence were landuse, rainfall intensity, distances from main road, distances from secondary roads, and distances from main river and those from trunk streams. In conclusion, we found that landslide occurrence was only in moderate, high, or very high hazard zones, and no landslides were in low or very low hazard zones showing 100% accuracy of our results. The landslide hazard zonation map showed that the current main road of the valley was in the zones of high or very high hazard. Two new safe road routes were suggested by using the GIS technology.     

浙江省永嘉县区域滑坡灾害人口易损性评价和伤亡风险预测

区域滑坡灾害人口易损性及人口伤亡风险预测研究是区域滑坡灾害预警预报工作的一个重要环节,该研究对提高预警预报工作的针对性和有效性具有关键作用.在对浙江省永嘉县有关资料进行分析的基础上,从研究区人口年龄结构、居民对滑坡灾害风险的防范意识、政府对滑坡灾害的重视程度及滑坡灾害预警预报体系的完善程度4个方面评价了研究区人口易损性,并给出了计算人口易损性的公式,据此得到了永嘉县人口易损性分布图.根据永嘉县的实际情况,提出了耕地人口密度的概念.综合人口易损性分布图、人口密度分布图和滑坡灾害易发性预测图得到了研究区受威胁人口伤亡风险预测图,为当地政府职能部门实施滑坡灾害风险的控制和管理提供决策依据.     

滑坡灾害风险评价的关键理论与技术方法

滑坡灾害风险评估主要包括滑坡敏感性分析、危险性评价和风险评估3个不同层次的内容。但是,滑坡地质灾害本身的复杂性和滑坡强度的确定、滑坡发生的时空概率估算、承灾体的易损性时空概率分析等难点问题的存在,无疑阻碍了滑坡风险定量评估的推广和应用。在系统分析国内外滑坡灾害风险评估研究成果的基础上,对滑坡灾害风险评价的技术体系进行了总结,提出了不同层次滑坡灾害的研究内容和相应的评价方法;分析了实现滑坡风险有效评价涉及到的难点问题,并结合降雨和地震诱发的滑坡灾害危险性评价国内外的实践,提出了中国未来滑坡灾害风险评价研究的主要内容和技术方法。     

Integrated use of GIS and remote sensing for monitoring landslides in transportation pavements: the case study of Paphos area in Cyprus

This study considers the impact of landslides on transportation pavements in rural road network of Cyprus using remote sensing and geographical information system (GIS) techniques. Landslides are considered to be one of the most extreme natural hazards worldwide, causing both human losses and severe damages to the transportation network. Risk assessment for monitoring a road network is based on the combination of the probability of landslides occurrence and the extent and severity of the resultant consequences should the disasters (landslides) occur. Factors that can trigger landslide episodes include proximity to active faults, geological formations, fracture zones, degree and high curvature of slopes, water conditions, etc. In this study, the reliability and vulnerability of a rural network are examined. Initially, landslide locations were identified from the interpretation of satellite images. Different geomorphological factors such as aspect, slope, distance from the watershed, lithology, distance from lineaments, topographic curvature, land use and vegetation regime derived from satellite images were selected and incorporated in GIS environment in order to develop a decision support and continuous landslide monitoring system of the area. These parameters were then used in the final landslide hazard assessment model based on the analytic hierarchy process method. The results indicated good correlation between classified high-hazard areas and field-confirmed slope failures. The CA Markov model was also used to predict the landslide hazard zonation map for 2020 and the possible future hazards for transportation pavements. The proposed methodology can be used for areas with similar physiographic conditions all over the Eastern Mediterranean region.     

Mapping of landslide hazard zonation using GIS at Golestan watershed, northeast of Iran

Landslide hazard zonation is essential for planning future developmental activities. At the present study, after the preparation of a landslide inventory of the study area, nine factors as well as sub-data layers of factor class weights were tested for an integrated analysis of landslide hazard in the region. The produced factor maps were weighted with the analytic hierarchy process method and then classified into four classes—negligible, low, moderate, and high. The final produced map for landslide hazard zonation in Golestan watershed revealed that: (1) about 53.85 % of the basin is prone to moderate and high threats of landslides. (2) Landslide events at the Golestan watershed were strongly correlated to the slope angle of the basin. It was observed that the active landslide zones, including moderate to high landslide hazard classes, have a high correlation to slope classes over 30° (R ²?=?0.769). (3) The regions most susceptible to landslide hazard are those located south and southwest of the watershed, which included rock topples, falls, and debris landslides.     

A review of assessing landslide frequency for hazard zoning purposes

The probability of occurrence is one of the key components of the risk equation. To assess this probability in landslide risk analysis, two different approaches have been traditionally used. In the first one, the occurrence of landslides is obtained by computing the probability of failure of a slope (or the reactivation of existing landslides). In the second one, which is the objective of this paper, the probability is obtained by means of the statistical analysis of past landslide events, specifically by the assessment of the past landslide frequency. In its turn, the temporal frequency of landslides may be determined based on the occurrence of landslides or from the recurrence of the landslide triggering events over a regional extent. Hazard assessment using frequency of landslides, which may be taken either individually or collectively, requires complete records of landslide events, which is difficult in some areas. Its main advantage is that it may be easily implemented for zoning. Frequency assessed from the recurrence of landslide triggers, does not require landslide series but it is necessary to establish reliable relations between the trigger, its magnitude and the occurrence of the landslides. The frequency of the landslide triggers can be directly used for landslide zoning. However, because it does not provide information on the spatial distribution of the potential landslides, it has to be combined with landslide susceptibility (spatial probability analysis) to perform landslide hazard zoning. Both the scale of work and availability of data affect the results of the landslide frequency and restrict the spatial resolution of frequency zoning as well. Magnitude–frequency relationships are fundamental elements for the quantitative assessment of both hazard and risk.     

Inclusion of earthquake strong ground motion in a geographic information system-based landslide susceptibility zonation in Garhwal Himalayas

Garhwal Himalayas are seismically very active and simultaneously suffering from landslide hazards. Landslides are one of the most frequent natural hazards in Himalayas causing damages worth more than one billion US$ and around 200 deaths every year. Thus, it is of paramount importance to identify the landslide causative factors to study them carefully and rank them as per their influence on the occurrence of landslides. The difference image of GIS-derived landslide susceptibility zonation maps prepared for pre- and post-Chamoli earthquake shows the effect of seismic shaking on the occurrence of landslides in the Garhwal Himalaya. An attempt has been made to incorporate seismic shaking parameters in terms of peak ground acceleration with other static landslide causative factors to produce landslide susceptibility zonation map in geographic information system environment. In this paper, probabilistic seismic hazard analysis has been carried out to calculate peak ground acceleration values at different time periods for estimating seismic shaking conditions in the study area. Further, these values are used as one of the causative factors of landslides in the study area and it is observed that it refines the preparation of landslide susceptibility zonation map in seismically active areas like Garhwal Himalayas.     

中国地震滑坡危险性评估及其对国土空间规划的影响研究

中国是世界上地震滑坡灾害最为严重的国家之一.考虑地质构造、地形地貌、地层岩性、河流、地震动参数等6类影响因素,针对50年超越概率10％的抗震设防水准,分别开展了基于信息量模型和Newmark模型的地震滑坡危险性评估.基于最不利原则对两项结果进行地震滑坡危险性综合分区,揭示了中国地震滑坡高危险区集中在南北构造带、青藏高原...     

Landslide susceptibility zonation of the Chamoli region, Garhwal Himalayas, using logistic regression model

A remote sensing and Geographic Information System-based study has been carried out for landslide susceptibility zonation in the Chamoli region, part of Garhwal Himalayas. Logistic regression has been applied to correlate the presence of landslides with independent physical factors including slope, aspect, relative relief, land use/cover, lithology, lineament, and drainage density. Coefficients of the categories of each factor have been obtained and used to assess the landslide probability value to ultimately categorize the area into various landslide susceptibility zones; very low, low, moderate, high, and very high. The results show that 71.13% of observed landslides fall in 21.96% of predicted very high and high susceptibility zone, which in fact should be the case. Furthermore, lineament first buffer category (0–500 m) and the east and south aspects are the most influential in causing landslides in the region.     

The performance evaluation of information value,density area,LNRF, and frequency ratio methods for landslide zonation at Miandarband area,Kermanshah Province,Iran

Landslide is one of the natural disasters which causes a lot of annual damage directly or indirectly in the world. Many planned areas, especially in hilly regions, are prone to different types of landslides; therefore, landslide susceptibility maps become an urgent issue, so that landslide damages and impact can be minimized. The best method for studying landslides, which has long been of interest to researchers, is hazard zonation. In this method, due to the affecting factors in landslide occurrence, study areas are classified into areas with low to very high risk. Different methods have been developed for this purpose. In this paper, the four bivariate statistical methods namely information value, density area, LNRF, and frequency ratio are used to investigate the hazard zonation of landslide in Miandarband located north of the Kermanshah Province. The density ratio (D _r) and Qs values for information value, density area, frequency ratio, and LNRF methods used in this study were calculated to be 2.245312, 0.98146; 2.857816, 1.071185; 2.858085, 0.783945; and 2.418375, 1.070928, respectively. The results indicate that although there are minor differences, the frequency ratio method compared to the density area method that was used for the study of landslide zonation presents better results.     

基于逻辑回归模型和确定性系数的崩滑流危险性区划

崩滑流是崩塌、滑坡和泥石流地质灾害的总称。本文根据逻辑回归模型和贵州省崩滑流地质灾害发生的确定性系数CF,统计贵州省内崩滑流发生概率与其影响因子之间的函数关系; 并利用GIS技术编制贵州省崩滑流地质灾害危险性区划图。首先根据影响因子子集中已发崩滑流灾害面积和影响因子子集面积来计算崩滑流地质灾害发生的确定性系数CF; 其次将灾害是否发生作为因变量,影响因子子集发生崩滑流地质灾害的确定性系数CF作为自变量,应用逻辑回归模型统计分析它们之间的函数关系; 然后利用GIS技术计算研究区内各独立属性单元发生崩滑流地质灾害的概率p,按p值10等分标准将研究区划分为10个危险性等级区,并绘制贵州省崩滑流地质灾害危险性区划图; 最后用已发崩滑流地质灾害的分布数据来检验危险性区划的效果。研究结果表明:本文根据逻辑回归模型和崩滑流地质灾害发生的确定性系数CF,将贵州省分为Ⅰ～Ⅹ的10个崩滑流地质灾害危险性等级区与实际情况基本符合,能够良好地反映贵州省境内发生崩滑流地质灾害的难易程度。     

A Landslide Hazard Assessment and Vulnerability Appraisal Procedure: Vunguvungu/Banga Catchment,Northern Malawi

Landslides are a common phenomenon in parts of Malawi. A number of historical landslides have been documented, and are summarised here. This paper examines the occurrence of landslides in the Rumphi district of northern Malawi, concentrating on the catchment of the Vunguvungu and Banga rivers. This is an area of deeply weathered biotitic gneiss and muscovite schist, with deep, sandy soils, comparatively steep slopes and a rainfall in excess of 1,500 mm per annum. These factors, in association with changing land use patterns, have contributed to the landslide vulnerability of the area. The investigation focuses, as a case study, on the Banga landslide of 1997 for which data are available, and which occurred after unseasonal rain. A unique combination of natural and human induced factors is proposed in explaining the occurrence of landslides. The paper concludes by proposing an elementary vulnerability appraisal procedure for the catchment and by discussing the potential risk of landslides in this area.     

Numerical Modeling of the Seasonal Dynamic Characteristics of the Koxkar Glacier,in West Tianshan,China

Landslides commonly occurs in hilly areas and causes an enormous loss iof life and property every year. National highway-1D (NH-1D) is the only road link between the two districts (Kargil and Leh) of Ladakh region that connects these districts with Kashmir valley. The landslide failure record of the recent past along this sector of the highway is not available. The present study documents landslide susceptible zones and records occurrence of 60 landslides during the last 4 years showing an increasing trend in the occurrence of landslides over these years in this sector. The landslide susceptibility zonation map has been prepared based on the numerical rating of ten major factors viz. slope morphometry, lithology, structure, relative relief, land cover, landuse, rainfall, hydrological conditions, landslide incidences and Slope Erosion, categorised the area in different zones of instability based on the intensity of susceptibility. The landslide susceptibility map of the area encompassing 73.03 km² is divided into 150 facets. Out of the total of 150 facets, 85 facets fall in low susceptibility zone covering 43.56 km2 which constitute about 59.65% of the total area under investigation with a record of 5 landslides; 40 facets fall in the moderate susceptibility zone covering 16.94km² which constitutes about 23.19% of the study area with a record of 20 landslides; and 25 facets fall in the high susceptibility zone covering 12.53 km² which constitute about 17.15% of the study area with a record of 35 landslides. Most of the facets which fall in HSZ are attributed to slope modification for road widening.     

Assessing landslide exposure in areas with limited landslide information

Landslide risk assessment is often a difficult task due to the lack of temporal data on landslides and triggering events (frequency), run-out distance, landslide magnitude and vulnerability. The probability of occurrence of landslides is often very difficult to predict, as well as the expected magnitude of events, due to the limited data availability on past landslide activity. In this paper, a qualitative procedure for assessing the exposure of elements at risk is presented for an area of the Apulia region (Italy) where no temporal information on landslide occurrence is available. Given these limitations in data availability, it was not possible to produce a reliable landslide hazard map and, consequently, a risk map. The qualitative analysis was carried out using the spatial multi-criteria evaluation method in a global information system. A landslide susceptibility composite index map and four asset index maps (physical, social, economic and environmental) were generated separately through a hierarchical procedure of standardising and weighting. The four asset index maps were combined in order to obtain a qualitative weighted assets map, which, combined with the landslide susceptibility composite index map, has provided the final qualitative landslide exposure map. The resulting map represents the spatial distribution of the exposure level in the study area; this information could be used in a preliminary stage of regional planning. In order to demonstrate how such an exposure map could be used in a basic risk assessment, a quantification of the economic losses at municipal level was carried out, and the temporal probability of landslides was estimated, on the basis of the expert knowledge. Although the proposed methodology for the exposure assessment did not consider the landslide run-out and vulnerability quantification, the results obtained allow to rank the municipalities in terms of increasing exposure and risk level and, consequently, to identify the priorities for designing appropriate landslide risk mitigation plans.     

Regional landslide-hazard assessment for Seattle, Washington, USA

Landslides are a widespread, frequent, and costly hazard in Seattle and the Puget Sound area of Washington State, USA. Shallow earth slides triggered by heavy rainfall are the most common type of landslide in the area; many transform into debris flows and cause significant property damage or disrupt transportation. Large rotational and translational slides, though less common, also cause serious property damage. The hundreds of landslides that occurred during the winters of 1995–96 and 1996–97 stimulated renewed interest by Puget Sound communities in identifying landslide-prone areas and taking actions to reduce future landslide losses. Informal partnerships between the U.S. Geological Survey (USGS), the City of Seattle, and private consultants are focusing on the problem of identifying and mapping areas of landslide hazard as well as characterizing temporal aspects of the hazard. We have developed GIS-based methods to map the probability of landslide occurrence as well as empirical rainfall thresholds and physically based methods to forecast times of landslide occurrence. Our methods for mapping landslide hazard zones began with field studies and physically based models to assess relative slope stability, including the effects of material properties, seasonal groundwater levels, and rainfall infiltration. We have analyzed the correlation between historic landslide occurrence and relative slope stability to map the degree of landslide hazard. The City of Seattle is using results of the USGS studies in storm preparedness planning for emergency access and response, planning for development or redevelopment of hillsides, and municipal facility planning and prioritization. Methods we have developed could be applied elsewhere to suit local needs and available data.     

Diagnosis of landslide risk for individual buildings: insights from Prahova Subcarpathians,Romania

The aim of this study is to quantify the landslide risk for individual buildings using spatial data in a GIS environment. A landslide-prone area from Prahova Rivers’ Subcarpathian Valley was chosen because of its associated landslide hazards and its impact upon human settlements and activities. The bivariate landslide susceptibility index (LSI) was applied to calculate the spatial probability of landslides occurrence. The Landslide Susceptibility Index map was produced by numerically adding the weighted thematic maps for slope gradient and aspect, water table, soil texture, lithology, built environment and land use. Validation curves were obtained using the random-split strategy for two combinations of variables: (a) all seven variables and (b) three variables which showed highest individual success rates with respect to landslides occurrences (slope gradient, water table and land use). The principal pre-disposing factors were found to be slope steepness and groundwater table. Vulnerability was established as the degree of loss to individual buildings resulting from a potential damaging landslide with a given return period in an area. Risk was calculated by multiplying the spatial probability of landslides by the vulnerability for each building and summing up the losses for the selected return period.     

基于有效降雨强度和逻辑回归的降雨型 滑坡预测模型

以湖南省张家界市桑植县为研究区,在全面分析近30年降雨及滑坡数据的基础上,对滑坡及滑坡数量与降雨因子的关系开展了统计分析研究。首先确定了区域最佳有效降雨衰减系数,同时分别按滑坡规模、坡度、厚度大小统计了降雨与历史滑坡信息,得出有效降雨强度（I）与持续时间（D）散点图,由此确定各不同概率下诱发滑坡的区域有效降雨强度阈值,并进行了滑坡灾害危险性等级划分。进而,利用部分样本数据进行逻辑回归分析,得到了该研究区的滑坡发生概率预测方程,并给出了降雨强度临界值定量表达式,最后选用实际降雨诱发滑坡事件与未诱发滑坡事件进行对比验证。结果表明,文章所建立的滑坡预测模型准确性较高,预测情况与实际情况比较吻合。     

Comparison of results of BIS and GSI guidelines on macrolevel landslide hazard zonation — A case study along highway from Bhalukpong to Bomdila,West Kameng district,Arunachal Pradesh

This paper compares the findings of macrolevel landslide hazard zonation carried out along the highway from Bhalukpong to Bomdila, West Kameng district, Arunachal Pradesh following GSI and BIS guidelines. The map resulted from the GSI guideline shows that 69.31% of the faceted area falls under the Low Hazard Zone (LHZ) while 17.69%, 7.31%, 5.03% and 0.65% of the area are in Moderate Hazard Zone (MHZ), High Hazard Zone (HHZ), Very Low Hazard Zone (VLHZ) and Very High Hazard Zone (VHHZ) respectively. Correlation between the landslide incidences and different hazard zones reveals that maximum failure percentage is in VHHZ and it is followed by HHZ, MHZ and LHZ. The second map resulting from BIS guideline reveals that 45.77% of the faceted area falls under MHZ while 41.39%, 11.52% and 1.29% of the area are in HHZ, LHZ and VHHZ respectively. Not a single facet falls in VLHZ.With regard to failure percentage VHHZ experiences 50%, while that of HHZ, MMH and LHZ is roughly 11.5% each. In the study area, the landslide hazard zonation map resulting from GSI guideline broadly conforms to field condition. It may be due to the fact that the study area is along the road corridor where slope cutting and landslides are very common and GSI guideline considers both the slope cutting and landslide parameters, while it is not so in the case of BIS guidelines. However, a final conclusion can be drawn after carrying out such studies in different geological settings.