Landslide susceptibility assessment of South Pars Special Zone,southwest Iran

This study assesses the landslide susceptibility of the South Pars Special Zone (SPSZ) region that is located in southwest Iran. For this purpose, a combinatorial method containing multi-criteria decision-making, likelihood ratio and fuzzy logic was applied in two levels (regional and local) at three critical zones (northwest, middle and southeast of the project area). The analysis parameters were categorised in seven main triggering factors such as climatology, geomorphology, geology, geo-structure, seismic activity, landslide prone areas and man-made activities which have different classes with multi-agent partnership correlations. Landslide susceptibility maps were prepared for these levels and zones after purified and enriched fuzzy trending runs were performed. According to the results of the risk-ability assessment of the landslide occurrences for SPSZ, the north part of the study area which includes the south edge of the Assalouyeh anticline and the southern part of the Kangan anticline were estimated as high-risk potential areas that were used in landslide hazard mitigation assessment and in land-use planning.     

Probabilistic landslide hazard assessment using Copula modeling technique

A new probabilistic methodology for landslide hazard assessment in regional scale using Copula modeling technique is presented. The current probabilistic landslide hazard analyses are performed under the assumption that landslide hazard elements, such as magnitude, frequency, and location, are independent. In this paper, a general approach is proposed to consider the possible dependence among hazard elements. Part of the Seattle, WA area was selected to evaluate the competence of the presented method. A total of 357 slope failure events and their corresponding topography and geology data were included in the study to develop and test the model. Based on the results, the mean success rates of the presented model in predicting landslide occurrence are 90 % in hazardous area and 12 % in safe locations on average, while these success rates are 63 and 44 % when these hazard elements were treated as mutually independent.     

Landslide hazard and risk assessment: a?case study from the Hlohovec–Sered’ landslide area in south-west Slovakia

Landslide hazard or susceptibility assessment is based on the selection of relevant factors which play a role on the slope instability, and it is assumed that landslides will occur at similar conditions to those in the past. The selected statistical method compares parametric maps with the landslide inventory map, and results are then extrapolated to the entire evaluated territory with a final product of landslide hazard or susceptibility map. Elements at risk are defined and analyzed in relation with landslide hazard, and their vulnerability is thus established. The landslide risk map presents risk scenarios and expected financial losses caused by landslides, and it utilizes prognoses and analyses arising from the landslide hazard map. However, especially the risk scenarios for future in a selected area have a significant importance, the literature generally consists of the landslide susceptibility assessment and papers which attempt to assess and construct the map of the landslide risk are not prevail. In the paper presented herein, landslide hazard and risk assessment using bivariate statistical analysis was applied in the landslide area between Hlohovec and Sered?? cities in the south-western Slovakia, and methodology for the risk assessment was explained in detail.     

一种改进的区域滑坡危险性评价模型及其应用

区域滑坡危险性评价方法还存在许多需要完善和改进的地方。以工程地质类比法为基础,用滑坡的面密度表示滑坡发生的危险性大小,基于线性代数中QR分解理论,提出了一种用高次多项式拟合致险因子与滑坡危险性间关系的算法,并把该算法与层次分析法模型、条件概率模型相融合,建立了一种改进的区域滑坡危险性评价模型。然后,通过在Visual Studio.Net C#环境下借助ArcEngine组件的二次开发实现了该模型。最后选取陕西省麟游县为实验区域,利用上述模型进行了滑坡危险性评价。经实际资料检验表明,该模型具有较高的可信度,可应用于今后的滑坡危险性区域评价工作中。     

Advances in landslide nowcasting: evaluation of a global and regional modeling approach

The increasing availability of remotely sensed data offers a new opportunity to address landslide hazard assessment at larger spatial scales. A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that may experience landslide activity. This system combines a calculation of static landslide susceptibility with satellite-derived rainfall estimates and uses a threshold approach to generate a set of ‘nowcasts’ that classify potentially hazardous areas. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale near real-time landslide hazard assessment efforts, it requires several modifications before it can be fully realized as an operational tool. This study draws upon a prior work’s recommendations to develop a new approach for considering landslide susceptibility and hazard at the regional scale. This case study calculates a regional susceptibility map using remotely sensed and in situ information and a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America. The susceptibility map is evaluated with a regional rainfall intensity–duration triggering threshold and results are compared with the global algorithm framework for the same event. Evaluation of this regional system suggests that this empirically based approach provides one plausible way to approach some of the data and resolution issues identified in the global assessment. The presented methodology is straightforward to implement, improves upon the global approach, and allows for results to be transferable between regions. The results also highlight several remaining challenges, including the empirical nature of the algorithm framework and adequate information for algorithm validation. Conclusions suggest that integrating additional triggering factors such as soil moisture may help to improve algorithm performance accuracy. The regional algorithm scenario represents an important step forward in advancing regional and global-scale landslide hazard assessment.     

Integration of statistical and heuristic approaches for landslide risk analysis: a case of volcanic mountains in West Java Province,Indonesia

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.     

空间三维滑坡敏感性分区工具及其应用

对于滑坡敏感性分区目前有三种方法:定性法、统计法和基于岩土定量模型的确定性方法。定性法基于对滑坡敏感性或灾害评估的人为判断;统计法用一个来源于结合了权重因子的预测函数或指标;而确定性法,或者说是物理定量模型法以质量、能量和动量守恒定律为基础。二维确定性模型广泛用于土木工程设计,而无限边坡模型(一维)也用于滑坡灾害分区的确定性模型。文中提出了一个新的基于GIS(地理信息系统)的滑坡敏感性分区系统,这个系统可用于从复杂地形中确认可能的危险三维(3-D)滑坡体。所有与滑坡相关的空间数据(矢量或栅格数据)都被集成到这个系统中。通过把研究区域划分为边坡单元并假定初始滑动面是椭球的下半部分,并使用Monte Carlo随机搜索法,三维滑坡稳定性分析中的三维最危险滑面是三维安全系数最小的地方。使用近似方法假定有效凝聚力、有效摩擦角和三维安全系数服从正态分布,可以计算出滑坡失稳概率。3DSlopeGIS是一个计算机程序,它内嵌了GIS Developer kit(ArcObjects of ESRI)来实现GIS空间分析功能和有效的数据管理。应用此工具可以解决所有的三维边坡空间数据解问题。通过使用空间分析、数据管理和GIS的可视化功能来处理复杂的边坡数据,三维边坡稳定性问题很容易用一个友好的可视化图形界面来解决。将3DSlopeGIS系统应用到3个滑坡敏感性分区的实例中:第一个是一个城市规划项目,第二个是预测以往滑坡灾害对临近区域可能的影响,第三个则是沿着国家主干道的滑坡分区。基于足够次数的Monte Carlo模拟法,可以确认可能的最危险滑坡体。这在以往的传统边坡稳定性分析中是不可能的。     

基于斜坡单元的山区城镇滑坡灾害易发性评价：以康定为例

山区地质灾害易发性评价对城镇地质灾害风险管理具有重要意义。本文以康定市为例,以斜坡单元为最小评价单元,选取高程、坡度、坡向、曲率、工程地质岩组、距道路距离、距断裂距离、距水系距离和斜坡结构等9个滑坡影响因子,根据各因子滑坡面积比曲线与证据权值曲线的突变点,划分滑坡影响因子二级状态,并对各影响因子进行相关性分析,剔除相关性较高的距道路距离因子,在此基础上,采用证据权模型进行滑坡易发性评价。对已有治理工程的斜坡单元,本文尝试利用折减系数法对其易发性进行进一步评价。结合现场调查,将研究区滑坡易发性程度划分为：极高易发、高易发、中等易发、低易发。评价结果表明,自然工况下极高易发区主要位于康定市炉城镇以及研究区北侧二道桥村一带,高易发区主要位于雅拉河、折多河与瓦斯沟河谷两侧,对治理工程所在的斜坡单元进行折减后,极高易发区面积由11.21%降至8.42%,滑坡比率由4.03降低至2.3,研究结果符合实际情况,模型精度达77.8%。评价结果较好地反映了康定市区的滑坡易发性分布情况,可为城镇精细化评价提供一定的参考依据。     

RS与GIS支持下的汶川县城周边地质灾害危险性评价

地质灾害危险性评价是防灾减灾工作的重要依据。本文以汶川县城周边64 km2为例,应用遥感信息提取技术与GIS空间分析方法,根据IKONOS遥感图像和地形图及野外调查资料,提取了崩塌和滑坡易发性评价因子,采用信息量法确定了因子分值,计算了崩塌和滑坡易发性,并分别提出崩塌和滑坡的危险性计算方法,形成了汶川地区崩塌和滑坡危险性分区图。研究结果表明:新的崩塌和滑坡危险性评价方法能够反映区内地质灾害危险程度,该方法可行,结果合理,这为中、大比例尺区域范围内地质灾害危险性研究提供了有益的思路。     

基于简化 Newmark位移模型的区域地震滑坡危险性快速评估以汶川MS 8.0级地震为例

以汶川MS8.0级地震重灾区的11县市为例,初步提出了基于简化Newmark位移模型的地震滑坡危险性应急快速评估方法。利用汶川地震即时地震动参数、工程地质岩性经验分组及地形坡度数据,借助ArcGIS空间数据建模工具编制了地震滑坡危险性快速评估流程模块。计算了区域浅表层饱和岩土体斜坡的静态安全系数Fs、临界加速度ac,并借此分析了地震滑坡易发性。利用经验式获得了汶川地震Arias强度和区域滑坡位移DN分布,实现了汶川地震重灾区地震滑坡危险性的快速评估,为应急救灾决策提供了参考。通过对比评估结果和震后滑坡调查成果,可知数十处灾难性滑坡绝大部分位于-高危险区的龙门山主中央断裂带两侧约20km地带中,显示了评估方法的可靠性; 同时,分析指出了空间数据精度及更新不足导致局部评估结果欠佳的局限性,并提出了改进建议。     

Landslide susceptibility zonation mapping and its validation in part of Garhwal Lesser Himalaya, India, using binary logistic regression analysis and receiver operating characteristic curve method

A landslide susceptibility zonation (LSZ) map helps to understand the spatial distribution of slope failure probability in an area and hence it is useful for effective landslide hazard mitigation measures. Such maps can be generated using qualitative or quantitative approaches. The present study is an attempt to utilise a multivariate statistical method called binary logistic regression (BLR) analysis for LSZ mapping in part of the Garhwal Lesser Himalaya, India, lying close to the Main Boundary Thrust (MBT). This method gives the freedom to use categorical and continuous predictor variables together in a regression analysis. Geographic Information System has been used for preparing the database on causal factors of slope instability and landslide locations as well as for carrying out the spatial modelling of landslide susceptibility. A forward stepwise logistic regression analysis using maximum likelihood estimation method has been used in the regression. The constant and the coefficients of the predictor variables retained by the regression model have been used to calculate the probability of slope failure for the entire study area. The predictive logistic regression model has been validated by receiver operating characteristic curve analysis, which has given 91.7% accuracy for the developed BLR model.     

秦岭中部太白县地质灾害发育特征及危险性评估

以陕西省太白县为例,分析了秦岭中部山区地质灾害形成的地质环境条件,重点指出在植被茂密山区,异常强降雨及农耕、建房、修路和矿山开采4种人类工程活动对地质灾害的关键诱发作用。对崩塌、滑坡、泥石流和不稳定斜坡4类典型地质灾害进行了亚类细分和发育特征分析,并总结指出了地质灾害区域宏观分布特征。筛选了9种关键的地质灾害影响和诱发因素,基于将集中调查区指示的地质灾害发育规律,外推应用于全区地质灾害评估的思路,利用信息量模型对太白县全区进行了地质灾害危险性定量评估,结果显示高危险区主要集中分布在县域北部人口聚居的盆地区,以及南部河流与公路沿线地段。定量检验显示,危险性评估结果与地质灾害的实际分布十分吻合,表明基于信息量模型的地质灾害危险性评估方法能够很好地适用于秦岭腹地山区。     

Landslide temporal analysis and susceptibility assessment as bases for landslide mitigation, Machu Picchu, Peru

Multi-temporal landslide occurrence information acquired through aerial photo interpretation and field mapping was used to assess occurrence frequencies on the slopes around the UNESCO cultural world heritage site of Machu Picchu, Peru. This showed that the coarse time resolution of the historical landslide information may lead to inaccurate interpretations regarding landslide occurrence frequencies in some parts of the study area. In addition, the assumption that the past landslide frequency can be used to describe the future landslide occurrence was not proved in the study area. Thereafter, unique conditional analyses were undertaken to assess landslide susceptibility using a limited number of preparatory factor maps. It showed that large majority of the Inca City is located on least susceptible areas within the region. The results of the susceptibility assessment combined with landslide occurrence frequencies may serve as a basis for the landslide hazard mitigation in the studied area. For these purposes, pixel-based susceptibility maps were generalized into expert-defined landslide management units. These units provide site managers with easily understandable and applicable hence reliable information about future landslide occurrences. An approach describing usage of the resulting susceptibility maps for onsite mitigation purposes was described with respect to the needs of Machu Picchu site managers.     

汶川震区成兰铁路关键段多尺度滑坡危险性评估

以穿越汶川震区的成兰铁路龙门山关键段为例, 探索提出了强震扰动背景下重大工程场区多尺度滑坡危险性评估方法。利用信息量模型反演评估了汶川地震诱发的同震滑坡空间分布特征, 以此为前提开展了区域和局地两种空间尺度的滑坡危险性预测评估。在区域廊带尺度上, 分别利用可能最大降雨量预测方法和信息量模型, 进行了日超越概率10%的最大降雨量时空分布预测及其诱发滑坡的危险性评估; 同时, 结合地震危险性区划成果, 开展了50年超越概率10%的基本地震动诱发滑坡的危险性评估。在局地场站尺度上, 利用基于崩塌运动过程模拟的Rockfall Analyst软件, 开展了柿子园大桥周边崩塌运动学特征(Runout)模拟和危险性评估。滑坡和崩塌危险性评估的结果分别为铁路规划选线和场站防护设计提供了不同尺度的地质安全依据。      

Kriging法在区域滑坡危险性评价中的应用

区域滑坡危险性评价是进行区域滑坡风险性研究的基础.由于滑坡演变机制的复杂性,使得目前基于独立分析各因素对滑坡影响的“白箱”型评价模式具有一定风险性,同时这类评价方法要求对滑坡演变和研究区地质地理背景进行非常细致的监测和调查.为了克服这些问题,文章提出了一种基于Kriging插值理论的“黑箱”型评价方法.在利用该方法对历史滑坡点的规模进行评价的基础上,利用Kriging插值法获取研究区的滑坡危险性区划,并以四川省苍溪县为例,验证了运用该方法进行区域滑坡危险性评价的可行性.     

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.     

Population amount risk assessment of extreme precipitation-induced landslides based on integrated machine learning model and scenario simulation

In this study, the future landslide population amount risk (LPAR) is assessed based on integrated machine learning models (MLMs) and scenario simulation techniques in Shuicheng County, China. Firstly, multiple MLMs were selected and hyperparameters were optimized, and the generated 11 models were cross-integrated to select the best model to calculate landslide susceptibility; by calculating precipitation for different extreme precipitation recurrence periods and combining the susceptibility results to assess the landslide hazard. Using the town as the basic unit, the exposure and vulnerability of the future landslide population under different Shared Socioeconomic Pathways (SSPs) scenarios in each town were assessed, and then combined with the hazard to estimate the LPAR in 2050. The results showed that the integrated model with the optimized random forest model as the combination strategy had the best comprehensive performance in susceptibility assessment. The distribution of hazard classes is similar to susceptibility, and with an increase in precipitation, the low-hazard area and high-hazard decrease and shift to medium-hazard and very high-hazard classes. The high-risk areas for future landslide populations in Shuicheng County are mainly concentrated in the three southwestern towns with high vulnerability, whereas the northern towns of Baohua and Qinglin are at the lowest risk class. The LPAR increased with the intensity of extreme precipitation. The LPAR differs significantly among the SSPs scenarios, with the lowest in the “fossil-fueled development (SSP5)” scenario and the highest in the “regional rivalry (SSP3)” scenario. In summary, the landslide susceptibility model based on integrated machine learning proposed in this study has a high predictive capability. The results of future LPAR assessment can provide theoretical guidance for relevant departments to cope with future socioeconomic development challenges and make corresponding disaster prevention and mitigation plans to prevent landslide risks from a developmental perspective.     

Regional assessment of landslide impact in the Three Gorges area, China, using ASTER data: Wushan-Zigui

This paper is focussed on the hazard impact of landslides in the Three Gorges, and represents the progression of our ongoing study on regional land instability assessment in the Three Gorges area using imagery data from the Advanced Spaceborne Thermal Emission Radiometer (ASTER). The key development here is the establishment of a model that integrates land instability with several factors that can relate hazard to human life, such as slope failures occurring in proximity to built-up areas and roads, and areas of high landslide risk along the bank of Yangtze and its major tributaries. The method correctly identifies some of the known destructive landslides in the region, like Qianjiangping and Huangtupo, as belonging to areas of potentially high landslide impact. Our results suggest that several population centres, including the towns of Wushan and Badong, are rated at high landslide hazard levels. This study highlights the importance of differentiating between landslide types within susceptibility assessment, and identifies those locations in the Three Gorges where the probability of landslide occurrence with negative impact to life and property is greatest.     

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.