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.     

风险评估在西五路滑坡评价中的应用

分析了滑坡灾害风险评估的基本方法,通过西五路工程实例介绍滑坡灾害风险评估的基本步骤:(1)全面勘察该地区地理地质环境,包括滑坡各项性质及该地区地面设施和人员分布。(2)进行危险性和易损性分析,包括计算滑坡稳定性和滑坡失稳概率。(3)在危险性和易损性分析基础上进行期望损失分析。     

一种基于多源遥感的滑坡防灾技术框架及其工程应用

我国是世界上受滑坡影响最大的国家之一,也投入了大量的人力物力开展区域性滑坡隐患探测工作.近年的政府工作表明,80%的滑坡发生在已圈定的隐患点范围外,80%的滑坡发生在防灾减灾工作条件相对薄弱的边远农村地区.为了解决这个困境,亟需:（1）厘清不同类型滑坡宜选用的广域探测技术,解决滑坡隐患广域探测的漏检问题;（2）突破社区协同滑坡防灾的难题,助力滑坡隐患探测和风险评估.本文将滑坡隐患分为4类:斜坡变形区、复活历史变形破坏区、稳定历史变形破坏区和潜在斜坡变形区,以便充分发挥多源遥感数据和技术的优势;进而提出一种“滑坡隐患广域探测-单体滑坡隐患风险评估-社区协同防灾”的多源遥感滑坡防灾技术框架.以青藏高原交通工程关键区段约10 000 km2区域作为研究区,协同社区（如设计和建设单位）共识别出滑坡隐患263处,其中斜坡变形区249处,复活历史变形破坏区5处,稳定历史变形破坏区9处,并针对3个典型滑坡隐患进行风险定量评估和社区协同防灾.该多源遥感技术框架将有助于提高社区滑坡防灾的能力,也将直接服务于青藏高原交通工程的建设与运维.      

基于SBAS-InSAR技术的成汶高速汶川段滑坡易发区选线研究

西南山区地质构造复杂导致大量的滑坡分布.为了科学有效的指导西南山区道路选线,提前规避地质灾害高风险,滑坡灾害早期识别必不可少.合成孔径雷达干涉测量(interferometric synthetic aperture radar,InSAR)技术因其全天候、多时相等特点被广泛应用于滑坡灾害的早期识别中.收集了87景Sentinel-1A降轨数据,利用差分干涉测量短基线集时序分析(small baseline subset interferometric synthetic aperture radar,SBAS-InSAR)技术对成汶高速路汶川段进行形变区的识别与分析,结果显示共识别出10处,经野外复核均为处于持续变形中的滑坡,有较好的一致性.根据早期识别结果,对3个比选方案进行综合对比分析,确定方案B为最优选择.SBAS-InSAR技术能有效识别山区公路潜在滑坡隐患区,为山区公路的准确选线提供科学依据.      

Seismic-event-based methodology to obtain earthquake-induced translational landslide regional hazard maps

A seismic-event-based methodology to generate earthquake-induced translational landslide maps using Newmark method is proposed. The steps are: (1) to construct a GIS-based geotechnical database; (2) to identify those areas that are susceptible to the occurrence of translational landslides based on available geological information; (3) to compute a static safety factor; (4) to compute the critical acceleration that defines the threshold acceleration required to cause a displacement; (5) to characterize the seismic hazard as a set of stochastic events, collectively exhaustive and mutually exclusive, that fully describes the hazard spatial distribution and annual frequency of occurrence (in accordance with the earthquake location, depth and magnitude) with the appropriate ground-motion prediction equations; (6) to compute the Newmark displacement; and finally, (7) to carry out a probabilistic translational landslide hazard analysis to estimate an exceedance rate of a given displacement. This methodology is applied to Mexico, and maps for return periods of 150 and 500 years are presented. Results shown in maps are estimations of where translational landslides may occur and should be useful to carry out local studies to elaborate recommendations of site specific hazard reduction plans as well as to calculate insurance rates. In addition, these results are useful to identify civil protection actions, risk management at regional and local level, and land use planning, as well as for promoting more detailed vulnerability and risk studies at different scales.     

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.     

基于SBAS-InSAR技术的深切割高山峡谷区滑坡灾害早期识别

近年来,高山峡谷区滑坡灾害频频发生,给人民生命和财产安全带来严重威胁。针对多数学者利用SAR单轨道数据对高山峡谷区滑坡进行早期识别,存在SAR成像几何畸变造成部分滑坡不能识别、识别结果不全面等问题。为全面准确的对高山峡谷区滑坡隐患进行早期识别,文章采用SBAS-InSAR技术,以东川小江沿线两侧深切割高山峡谷区为研究区,通过升降轨SAR数据结合互补的方式进行滑坡灾害隐患识别,引入高分辨率光学影像等作为辅助识别,最终共识别出18处滑坡灾害体,其中5处为高风险潜在滑坡,并对三类典型潜在滑坡进行分析。分析结果表明:利用升降轨SAR数据结合互补的方式,能有效避免SAR单轨道数据在高山峡谷地区产生的几何畸变问题,同时,该方法能更为准确全面地对高山峡谷区滑坡隐患进行早期识别,为防灾减灾事业及政府部门决策提供一种有效的手段。     

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.     

ICL Latin-American Network: on the road to landslide reduction capacity building

There is a clear need for integrated research on landslide disaster risk. Landslide disasters have major impacts in developing countries due to the increasing social vulnerability of both rural and urban communities. In recent decades, landslide disasters in Latin America triggered by both precipitation and earthquakes have also increased considerably. Thus, scientific contributions based on integrated risk research are quite urgent for improving the knowledge base for reducing the vulnerability of exposed communities to landslides. Thus, there is a parallel necessity to promote capacity building for young scientists in Latin America by considering the shift of disaster paradigm to recognize the “unnaturalness” of disasters. Under such a framework, there are particular goals to be pursued including: (1) Development of landslide regional networks with a commitment for understanding risk as a socially constructed process; (2) Engagement of young scientists in integrated landslide risk research; (3) Inducing a scientific multi- and transdisciplinary approach for integrated landslide risk research; (4) Development and implementation of capacity building; (5) Contributing to the dissemination and application of common methodologies on landslide disasters investigations; and (6) Strengthening collaboration on integrated landslide disaster risk research in Latin America. In this paper, we present one of the main activities of the ICL Latin-American network in terms of capacity building carried out in 2013; to that end, the first international workshop on forensic investigations of disasters associated with landslides was held in the University of Sciences and Arts of Chiapas in the city of Tuxtla Gutierrez, Chiapas, Mexico, from June 26th to July 4th, 2013.     

强震条件下高速滑坡的空间分布特征研究

5.12汶川地震引发了大量的滑坡灾害,本文以汶川地震极重灾区涉及的四川12县市为研究区域。通过详细的现场调查研究,对强震条件下的典型高速滑坡的空间分布特征进行了综合分析。从区域上看,高速滑坡明显呈带状沿龙门山断裂带展布,并主要受北川映秀断裂控制。此外,本文还对研究区域内典型高速滑坡的滑程、剪出口高程、滑坡前后缘高差等几何要素的空间分布规律做了分析研究。     

Data Mining for Landslide Genetic Mechanism Analysis in the Yunnan Province of China

Landslide susceptibility analysis based on the strong ability of data mining of Geographic Information System (GIS) has become a hot topic in international landslide research. This paper used optimized decision tree and GIS databases to analyze the sensitivity in the northwest mountain areas of Yunnan province of China, and then discussed the formation mechanism of the landslide happened in the area. The translational landslide located in the area with an average gradient less than or equal to 28.7° was reclassified as a higher level 3 sensitive area than before according to the normalized different fault index (NDFI). The results showed that the data mining based on GIS 3D space–time information database can help to find the unique topography, geology hydrology and the other typical spatial information of some special typed of landslides such as translational landslides, thus it can illustrate the relationship between the landslides and their sensitivity factors. The improved landslide susceptibility analysis will provide a new method for identifying the genetic mechanism of landslide, and play an important role in the government regional planning and disaster prevention measures.

     

单体滑坡灾害风险简易评价研究

按照灾害风险评价的一般框架,定性定量相结合,运用破坏概率、滑坡强度、承灾因子、遭遇特征与易损程度等5项指标,尝试提出单体滑坡灾害风险简易评价模型,并结合防治规划,提出了滑坡灾害风险管理对策建议。采用云南新平县滑坡灾害调查数据,开展了实例校验,结果表明,该模型基本反映了滑坡灾害的相对风险水平,可为现阶段管理提供更加明确的分级依据。同时,以期抛砖引玉,讨论险情调查与风险调查之间的关系。     

Impact of event landslides on road networks: a statistical analysis of two Italian case studies

Despite abundant information on landslides, and on landslide hazard and risk, in Italy, little is known on the direct impact of event landslides on road networks and on the related economic costs. We investigated the physical and economic damage caused by two rainfall-induced landslide events in Central and Southern Italy, to obtain road restoration cost statistics. Using a GIS-based method, we exploited road maps and landslide event inventory maps to compute different metrics that quantify the impact of the landslide events on the natural landscape and on the road networks, by road type. The maps were used with cost data obtained from multiple sources, including local authorities, and specific legislation, to evaluate statistically the unit cost per metre of damaged road and the unit cost per square metre of damaging landslide, separately for main and secondary roads. The obtained unit costs showed large variations which we attribute to the different road types in the two study areas and to the different abundance of landslides. Our work confirms the long-standing conundrum of obtaining accurate landslide damage data and outlines the need for reliable, standardized methods to evaluate landslide damage and associated restoration costs that regional and local administrations can use rapidly in the aftermath of a landslide event. We conclude recommending that common standardized procedures to collect landslide cost data following each landslide event are established, in Italy and elsewhere. This will allow for more accurate and reliable evaluations of the economic costs of landslide events.     

Landslide susceptibility mapping using rough sets and back-propagation neural networks in the Three Gorges, China

In the Three Gorges of China, there are frequent landslides, and the potential risk of landslides is tremendous. An efficient and accurate method of generating landslide susceptibility maps is very important to mitigate the loss of lives and properties caused by these landslides. This paper presents landslide susceptibility mapping on the Zigui-Badong of the Three Gorges, using rough sets and back-propagation neural networks (BPNNs). Landslide locations were obtained from a landslide inventory map, supported by field surveys. Twenty-two landslide-related factors were extracted from the 1:10,000-scale topographic maps, 1:50,000-scale geological maps, Landsat ETM + satellite images with a spatial resolution of 28.5 m, and HJ-A satellite images with a spatial resolution of 30 m. Twelve key environmental factors were selected as independent variables using the rough set and correlation coefficient analysis, including elevation, slope, profile curvature, catchment aspect, catchment height, distance from drainage, engineering rock group, distance from faults, slope structure, land cover, topographic wetness index, and normalized difference vegetation index. The initial, three-layered, and four-layered BPNN were trained and then used to map landslide susceptibility, respectively. To evaluate the models, the susceptibility maps were validated by comparing with the existing landslide locations according to the area under the curve. The four-layered BPNN outperforms the other two models with the best accuracy of 91.53 %. Approximately 91.37 % of landslides were classified as high and very high landslide-prone areas. The validation results show sufficient agreement between the obtained susceptibility maps and the existing landslide locations.     

Landslide vulnerability and risk assessment for multi-hazard scenarios using airborne laser scanning data (LiDAR)

Landslide hazard, vulnerability, and risk-zoning maps are considered in the decision-making process that involves land use/land cover (LULC) planning in disaster-prone areas. The accuracy of these analyses is directly related to the quality of spatial data needed and methods employed to obtain such data. In this study, we produced a landslide inventory map that depicts 164 landslide locations using high-resolution airborne laser scanning data. The landslide inventory data were randomly divided into a training dataset: 70 % for training the models and 30 % for validation. In the initial step, a susceptibility map was developed using logistic regression approach in which weights were assigned to every conditioning factor. A high-resolution airborne laser scanning data (LiDAR) was used to derive the landslide conditioning factors for the spatial prediction of landslide hazard areas. The resultant susceptibility was validated using the area under the curve method. The validation result showed 86.22 and 84.87 % success and prediction rates, respectively. In the second stage, a landslide hazard map was produced using precipitation data for 15 years. The precipitation maps were subsequently prepared and show two main categories (two temporal probabilities) for the study area (the average for any day in a year and abnormal intensity recorded in any day for 15 years) and three return periods (15-, 10-, and 5-year periods). Hazard assessment was performed for the entire study area. In the third step, an element at risk map was prepared using LULC, which was considered in the vulnerability assessment. A vulnerability map was derived according to the following criteria: cost, time required for reconstruction, relative risk of landslide, risk to population, and general effect to certain damage. These criteria were applied only on the LULC of the study area because of lack of data on the population and building footprint and types. Finally, risk maps were produced using the derived vulnerability and hazard information. Thereafter, a risk analysis was conducted. The LULC map was cross-matched with the results of the hazard maps for the return period, and the losses were aggregated for the LULC. Then, the losses were calculated for the three return periods. The map of the risk areas may assist planners in overall landslide hazard management.     

澜沧江拉金神谷滑坡成灾机理分析

涉水型古滑坡是西南水电工程区常见的灾害类型,揭示这类滑坡的成灾机理有助于降低链式灾害发生风险概率。以云南省德钦县燕门乡拉金神谷古滑坡为例,基于野外地质调查、InSAR监测和数值模拟研究,结合滑坡区工程地质条件,分析了滑坡的变形特征和破坏演化全过程。研究结果表明: ①拉金神谷滑坡成灾过程为前缘局部变形阶段→后缘拉裂阶段→滑坡—堰塞湖阶段→堰塞湖溃决阶段; ②库水位上升和降雨共同作用是诱发滑坡大变形的直接原因; ③若该滑坡的地质环境条件持续恶化,发生滑坡堵溃型链式灾害的风险很高。通过对拉金神谷古滑坡的成灾机理研究,提出了引入InSAR等监测调查技术手段开展类似涉水古滑坡排查的地质灾害早期识别建议,这对防范类似的高位链式地质灾害具有重要实践意义。     

综合统计模型和物理模型的地质灾害精细评估——以福建省龙山社区为例

地质灾害易发性和危险性评价对象相同但评价内容有差异,即两者表达地质灾害的时间、空间和强度信息各有不同。本文将崩塌滑坡易发性中的统计模型和危险性评价中的物理模型进行结合,综合统计模型客观预测空间位置信息的优点以及物理模型模拟包含地质灾害发生机制的优势,弥补了区域统计模型无法预测灾害强度信息的不足,也对物理模型模拟的空间位置进行了有效的控制和修正,进而完成区域崩塌滑坡的易发性和危险性等级综合分析,实现对区域崩塌滑坡潜在高风险位置的精细评估。本文以福建省福鼎市龙山社区为例,利用野外获取的高清影像、地形、钻孔和地质灾害等数据,通过综合统计模型评价和物理模型危险性评估,完成潜在高风险位置的精细化分析。研究结果表明:需要进行重点排查治理的区域约占社区附近山体总面积的26.92%;研究区域内需要进行集中排查与治理的区域有5个,其中3个区域需要进行重点治理,其潜在高风险区域与野外地质灾害调查区域隐患点吻合;5个高风险区域直接对180幢左右楼房（约360余户居民）的安全构成威胁,该评估将野外调研中划定的大范围高风险区域精细化处理,并验证了该评价方法体系的可行性。该评价方法体系为区域崩塌滑坡地质灾害精细化排查和治理提供了工作思路和指导。     

Generation of a landslide risk index map for Cuba using spatial multi-criteria evaluation

This paper explains the procedure for the generation of a landslide risk index map at national level in Cuba, using a semi-quantitative model with ten indicator maps and a cell size of 90 × 90 m. The model was designed and implemented using spatial multi-criteria evaluation techniques in a GIS system. Each indicator was processed, analysed and standardised according to its contribution to hazard and vulnerability. The indicators were weighted using direct, pairwise comparison and rank-ordering weighting methods, and weights were combined to obtain the final landslide risk index map. The results were analysed per physiographic region and administrative units at provincial and municipal levels. The Sierra Maestra mountain system was found to have the largest concentration of high landslide risk index values while the Nipe–Cristal–Baracoa system has the highest absolute values, although they are more dispersed. The results obtained allow designing an appropriated landslide risk mitigation plan at national level and to link the information to the national hurricane early warning system, allowing also warning and evacuation for landslide-prone areas.     

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.