Landslide Research at the British Geological Survey:Capture,Storage and Interpretation on a National and Site-Specific Scale

Abstract: Landslide research at the British Geological Survey (BGS) is carried out through a number of activities, including surveying, database development and real-time monitoring of landslides. Landslide mapping across the UK has been carried out since BGS started geological mapping in 1835. Today, BGS geologists use a combination of remote sensing and ground-based investigations to survey landslides. The development of waterproof tablet computers (BGS·SIGMAmobile), with inbuilt GPS and GIS for field data capture provides an accurate and rapid mapping methodology for field surveys. Regional and national mapping of landslides is carried out in conjunction with site-specific monitoring, using terrestrial LiDAR and differential GPS technologies, which BGS has successfully developed for this application. In addition to surface monitoring, BGS is currently developing geophysical ground-imaging systems for landslide monitoring, which provide real-time information on subsurface changes prior to failure events. BGS’s mapping and monitoring activities directly feed into the BGS National Landslide Database, the most extensive source of information on landslides in Great Britain. It currently holds over 14?000 records of landslide events. By combining BGS’s corporate datasets with expert knowledge, BGS has developed a landslide hazard assessment tool, GeoSure, which provides information on the relative landslide hazard susceptibility at national scale.     

New Zealand’s National Landslide Database

A New Zealand Landslide Database has been developed to hold all of New Zealand’s landslide data and provide factual data for use in landslide hazard and risk assessment, including a probabilistic landslide hazard model for New Zealand, which is currently being developed by GNS Science. Design of a national Landslide Database for New Zealand required consideration of existing landslide data stored in a variety of digital formats and future data yet to be collected. Pre-existing landslide datasets were developed and populated with data reflecting the needs of the landslide or hazard project, and the database structures of the time. Bringing these data into a single database required a new structure capable of containing landslide information at a variety of scales and accuracy, with many different attributes. A unified data model was developed to enable the landslide database to be a repository for New Zealand landslides, irrespective of scale and method of capture. Along with landslide locations, the database may contain information on the timing of landslide events, the type of landslide, the triggering event, volume and area data, and impacts (consequences) for each landslide when this information is available. Information from contributing datasets include a variety of sources including aerial photograph interpretation, field reconnaissance and media accounts. There are currently 22,575 landslide records in the database that include point locations, polygons of landslide source and deposit areas, and linear landslide features. Access to all landslide data is provided with a web application accessible via the Internet. This web application has been developed in-house and is based on open-source software such as the underlying relational database (PostGIS) and the map generating Web Map Server (GeoServer). Future work is to develop automated data-upload routines and mobile applications to allow people to report landslides, adopting a consistent framework.     

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.     

Evolution of natural risk: analysing changing landslide hazard in Wellington,Aotearoa/New Zealand

This paper addresses the temporal variation of rainfall-triggered landslide hazard within the broader context of natural risk evolution. Analysis of a sequence of aerial photos covering a period of 60 years allowed the establishment of a record of landsliding for a site in the Wellington region, New Zealand. The data show one very dominant peak in the magnitude of landslide occurrence in the late 1970s, followed by a continuous decrease. Landslide hazard can be expressed by the frequency and magnitude of the landslide events, with the total surface area affected used as a surrogate for magnitude. However, the distinct decline of landslide magnitude through time from the 1980s onwards indicates that landslide hazard may change with time. This possibility is further explored by correlating potential landslide triggering storms with the magnitude of the landslide event, using the ‘Antecedent Soil Water Status’ model in combination with daily rainfall. The relation between magnitudes of rainfall and magnitudes of landslide events is found to be weak, suggesting that a given ‘Critical Water Content’ (antecedent soil water status and rainfall on the day) does not produce similar magnitudes of landsliding. Furthermore, the study shows that reactivation of previous landslides before the peak landslide occurrence of the late 1970s is low, while the situation is reversed after this peak and reactivation in the subsequent years plays a larger role. It is concluded that the pattern of landsliding cannot be explained by the pattern of rainfall and other factors are controlling the variation of landslide hazard in time. A possible explanation is a change of the geomorphological system with time, instigated by a massive period of landsliding (the late 1970s peak). Subsequent sediment exhaustion of source areas resulting from this period appears to alter the system’s subsequent reaction to an external trigger such as rainfall. The study demonstrates that landslide hazard analysis in general should not rely on the integral of the frequency–magnitude relationship only, but should include potential non-linear changes of system settings to increase the understanding of future system behaviour, and therefore hazard and risk.

Putting science into practice: the Second World Landslide Forum,Rome, 3–9 October, 2011

The World Landslide Forum is a triennial mainstream conference aimed at gathering scientists, stakeholders, policy makers and industry members dealing with the management of landslide risk. The First World Landslide Forum, organised by the International Consortium of Landslides, UNESCO, WMO, FAO, UNISDR, UNU, UNEP, IBRD, UNDP, ICSU, WFEO, KU and the Japan Landslide Society, was held in 2008 at the United Nations University, Tokyo. The First World Landslide Forum adopted the 2008 Tokyo Declaration ‘Strengthening the International Programme on Landslides with UNISDR’. The numerous recent disasters due to landslides show that there is an urgent need to translate science into practical applications to assist communities, governments and disaster-relief organisations avert and mitigate future landslide disasters. For this reason, the explicit theme of the Second World Landslide Forum, being organised for Rome, Italy, for 3–9 October 2011, is to connect landslide scientists with landslide stakeholders in a special landslide forum to align future innovations in landslide science and technology with the future needs of humanity and the environment.     

基于多期DEM和滑坡强度的滑坡风险评估

滑坡危险性定量评估是滑坡风险评估中的关键和难点,也是当前国际风险管理研究中的热点问题.以滑坡密集分布的黑方台南塬为研究区,以32处典型滑坡为研究对象,依据多期三维数字高程模型(DEM),提出了一种基于强度的滑坡危险性定量评估技术方法.根据多期三维地形信息的解译及野外调查,编制多期滑坡分布图,计算滑坡活动的频率.利用GIS技术,利用滑坡体积与速度的乘积计算滑坡强度.将滑坡危险性定义为滑坡频率和滑坡强度的乘积,同时调查和分析了黑方台地区各类承灾体的类型、价值及其在相应滑坡强度下的易损性,在此基础上开展了单体滑坡风险评估和黑方台南塬滑坡风险区划.     

An integrated approach for evaluating the effectiveness of landslide risk reduction in unplanned communities in the Caribbean

Despite the recognition of the need for mitigation approaches to landslide risk in developing countries, the delivery of ‘on-the-ground’ measures is rarely undertaken. With respect to other ‘natural’ hazards, it is widely reported that mitigation can pay. However, the lack of such an evidence base in relation to landslides in developing countries hinders advocacy amongst decision makers for expenditure on ex-ante measures. This research addresses these limitations directly by developing and applying an integrated risk assessment and cost–benefit analysis of physical landslide mitigation measures implemented in an unplanned community in the Eastern Caribbean. In order to quantify the level of landslide risk reduction achieved, landslide hazard and vulnerability were modelled (before and after the intervention), and project costs, direct and indirect benefits were monetised. It is shown that the probability of landslide occurrence has been substantially reduced by implementing surface-water drainage measures and that the benefits of the project outweigh the costs by a ratio of 2.7–1. This paper adds to the evidence base that ‘mitigation pays’ with respect to landslide risk in the most vulnerable communities—thus strengthening the argument for ex-ante measures. This integrated project evaluation methodology should be suitable for adoption as part of the community-based landslide mitigation project cycle, and it is hoped that this resource, and the results of this study, will stimulate further such programmes.     

Manifestation of remote sensing data and GIS on landslide hazard analysis using spatial-based statistical models

This paper presents landslide hazard analysis at Cameron area, Malaysia, using a geographic information system (GIS) and remote sensing data. Landslide locations were identified from interpretation of aerial photographs and field surveys. Topographical and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. The factors chosen that influence landslide occurrence are topographic slope, topographic aspect, topographic curvature, and distance to rivers, all from the topographic database; lithology and distance to faults were taken from the geologic database; land cover from TM satellite image; the vegetation index value was taken from Landsat images; and precipitation distribution from meteorological data. Landslide hazard area was analyzed and mapped using the landslide occurrence factors by frequency ratio and bivariate logistic regression models. The results of the analysis were verified using the landslide location data and compared with the probabilistic models. The validation results showed that the frequency ratio model (accuracy is 89.25%) is better in prediction of landslide than bivariate logistic regression (accuracy is 85.73%) model.     

西藏帕里河2004-06-22滑坡卫星监测

2004-06-22滑坡位于我国西藏自治区的最西端,中印边界附近的帕里河流域中部。以多时相高分辨率卫星图像为信息源,以Orbview立体像对制作的高精度DEM为地理控制,采用数字滑坡技术研究和监测该滑坡自滑坡前至2007年7月的活动。遥感解译表明,滑坡前该处为由弧形裂缝与山体分割的滑前危岩,2004-06-22发生的堵河事件为一高速顺层基岩滑坡,基于RS+GIS求得滑坡体积为63。7万m3。遥感监测显示自2004年9月至2007年7月共35个月内,滑坡边界及滑面各细部均没有明显变化,期间该处未见发生过任何新的滑坡活动。该滑坡是一次在新构造活动强烈的高山峡谷区自然形成的重力侵蚀活动过程,能量释放充分,近期除原滑体四周有一些泄荷及调整活动外不会有大的活动。     

The 2010 Yushu earthquake triggered landslide hazard mapping using GIS and weight of evidence modeling

The Yushu County, Qinghai Province, China, April 14, 2010, earthquake triggered thousands of landslides in a zone between 96°20′32.9″E and 97°10′8.9″E, and 32°52′6.7″N and 33°19′47.9″N. This study examines the use of geographic information system (GIS) technology and Bayesian statistics in creating a suitable landslide hazard-zone map of good predictive power. A total of 2,036 landslides were interpreted from high-resolution aerial photographs and multi-source satellite images pre- and post-earthquake, and verified by selected field checking before a final landslide-inventory map of the study area could be established using GIS software. The 2,036 landslides were randomly partitioned into two subsets: a training dataset, which contains 80 % (1,628 landslides), for training the model; and a testing dataset 20 % (408 landslides). Twelve earthquake triggered landslide associated controlling parameters, such as elevation, slope gradient, slope aspect, slope curvature, topographic position, distance from main surface ruptures, peak ground acceleration, distance from roads, normalized difference vegetation index, distance from drainages, lithology, and distance from all faults were obtained from variety of data sources. Landslide hazard indices were calculated using the weight of evidence model. The landslide hazard map was compared with training data and testing data to obtain the success rate and predictive rate of the model, respectively. The validation results showed satisfactory agreement between the hazard map and the existing landslide distribution data. The success rate is 80.607 %, and the predictive rate is 78.855 %. The resulting landslide hazard map showed five classes of landslide hazard, i.e., very high, high, moderate, low and very low. The landslide hazard evaluation map should be useful for environmental recovery planning and reconstruction work.     

Exploring the magnitude–frequency distribution: a cellular automata model for landslides

Landslide magnitude–frequency curves allow for the probabilistic characterization of regional landslide hazard. There is evidence that landslides exhibit self-organized criticality including the tendency to follow a power law over part of the magnitude–frequency distribution. Landslide distributions, however, also typically exhibit poor agreement with the power law at smaller sizes in a flattening of the slope known as rollover. Understanding the basis for this difference is critical if we are to accurately predict landslide hazard, risk or landscape denudation over large areas. One possible argument is that the magnitude–frequency distribution is dominated by physiographic controls whereby landslides tend to a larger size, and larger landslides are landscape limited according to a power law. We explore the physiographic argument using first a simple deterministic model and then a cellular automata model for watersheds in coastal British Columbia. The results compare favorably to actual landslide data: modeled landslides bifurcate at local elevation highs, deposit mass preferentially where the local slopes decrease, find routes in confined valley or channel networks, and, when sufficiently large, overwhelm the local topography. The magnitude–frequency distribution of both the actual landslides and the cellular automata model follow a power law for magnitudes higher than 10,000–20,000 m² and show a flattening of the slope for smaller magnitudes. Based on the results of both models, we argue that magnitude–frequency distributions, including both the rollover and the power law components, are a result of actual physiographic limitations related to slope, slope distance, and the distribution of mass within landslides. The cellular automata model uses simple empirically based rules that can be gathered for regions worldwide.     

Probabilistic landslide hazards and risk mapping on Penang Island, Malaysia

This paper deals with landslide hazards and risk analysis of Penang Island, Malaysia using Geographic Information System (GIS) and remote sensing data. Landslide locations in the study area were identified from interpretations of aerial photographs and field surveys. Topographical/geological data and satellite images were collected and processed using GIS and image processing tools. There are ten landslide inducing parameters which are considered for landslide hazard analysis. These parameters are topographic slope, aspect, curvature and distance from drainage, all derived from the topographic database; geology and distance from lineament, derived from the geologic database; landuse from Landsat satellite images; soil from the soil database; precipitation amount, derived from the rainfall database; and the vegetation index value from SPOT satellite images. Landslide susceptibility was analyzed using landslide-occurrence factors employing the probability-frequency ratio model. The results of the analysis were verified using the landslide location data and compared with the probabilistic model. The accuracy observed was 80.03%. The qualitative landslide hazard analysis was carried out using the frequency ratio model through the map overlay analysis in GIS environment. The accuracy of hazard map was 86.41%. Further, risk analysis was done by studying the landslide hazard map and damageable objects at risk. This information could be used to estimate the risk to population, property and existing infrastructure like transportation network.     

Landslide activity as a geoindicator in Italy: significance and new perspectives from remote sensing

Landslide activity responds to rapid environmental changes and represents a relevant geoindicator in mountainous or hilly areas. This paper discusses the socio-economic relevance of landslide hazard in Italy and the problems encountered in establishing relationships between landslide frequency, climate and vegetation changes at different time scales. Landslides blocking a river channel have been carefully taken into account because they are usually characterized by high intensities (with regard to the involved masses and movement velocities) and their occurrences are often datable via radiocarbon dating. This is due to the recovery of organic matter in the landslide dammed lakes. For these reasons they can be considered important geoindicators in the wider category of slope failures. The marked effects of the anthropogenic activity on slope instability processes in the last 50 years are discussed with reference to two case histories: the Chianti hills in Tuscany and the Cinque Terre National Park in Liguria. Finally, two novel techniques of remote sensing are proposed as tools for a systematic monitoring of slope instability at different time and spatial scales. Both techniques are based on the interferometric synthetic aperture radar (SAR) technology and differ on the type of platform (satellite and ground-based) used to acquire data.     

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 statistical approach to landslide risk modelling at basin scale: from landslide susceptibility to quantitative risk assessment

A procedure for landslide risk assessment is presented. The underlying hypothesis is that statistical relationships between past landslide occurrences and conditioning variables can be used to develop landslide susceptibility, hazard and risk models. The latter require also data on past damages. Landslides occurred during the last 50 years and subsequent damages were analysed. Landslide susceptibility models were obtained by means of Spatial Data Analysis techniques and independently validated. Scenarios defined on the basis of past landslide frequency and magnitude were used to transform susceptibility into quantitative hazard models. To assess vulnerability, a detailed inventory of exposed elements (infrastructures, buildings, land resources) was carried out. Vulnerability values (0–1) were obtained by comparing damages experienced in the past by each type of element with its actual value. Quantitative risk models, with a monetary meaning, were obtained for each element by integrating landslide hazard and vulnerability models. Landslide risk models showing the expected losses for the next 50 years were thus obtained for the different scenarios. Risk values obtained are not precise predictions of future losses but rather a means to identify areas where damages are likely to be greater and require priority for mitigation actions.     

Application of Dempster-Shafer theory of evidence to GIS-based landslide susceptibility analysis

GIS-based spatial data integration tasks for predictive geological applications, such as landslide susceptibility analysis, have been regarded as one of the primary geological application issues of GIS. An efficient framework for proper representation and integration is required for this kind of application. This paper presents a data integration framework based on the Dempster-Shafer theory of evidence for landslide susceptibility mapping with multiple geospatial data. A data-driven information representation approach based on spatial association between known landslide occurrences and input geospatial data layers is used to assign mass functions. After defining mass functions for multiple geospatial data layers, Dempster’s rule of combination is applied to obtain a series of combined mass functions. Landslide susceptibility mapping using multiple geospatial data sets from Jangheung in Korea was conducted to illustrate the application of this methodology. The results of the case study indicated that the proposed methodology efficiently represented and integrated multiple data sets and showed better prediction capability than that of a traditional logistic regression model.     

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.     

滑坡灾害空间区划及GIS应用研究

滑坡灾害空间区划研究是当前国内外滑坡领域的重要研究方向之一。虽然滑坡灾害的发生具有随机性的特点 ,但其发生的区域性和重复性特点则是区域滑坡分布与发生的总体规律。从减灾与土地规划的角度 ,开展滑坡灾害空间区划研究具有十分重要的理论和实际意义。文中重点探讨了滑坡灾害空间区划的理论体系、灾害风险评估的基本术语定义及GIS制图的基本原理 ,采用MAPGIS软件为平台及其二次开发的滑坡灾害信息分析系统 ,在中国滑坡重灾害的汉江流域开展了灾害危险性空间区划应用研究。     

滑坡灾害空间预测研究

介绍了滑坡灾害空间预测的常用理论和方法、研究特点和适用范围，指出了区域滑坡空间预测、单体斜坡稳定性预测和滑坡灾害风险研究的发展趋势；以三峡库区巴东县黄土坡区斜坡稳定性区划为例，用神经网络模型和信息量模型两种方法进行了斜坡稳定性预测，取得了满意的效果。     

Spatial data for landslide susceptibility, hazard, and vulnerability assessment: An overview

The aim of this paper is to discuss a number of issues related to the use of spatial information for landslide susceptibility, hazard, and vulnerability assessment. The paper centers around the types of spatial data needed for each of these components, and the methods for obtaining them. A number of concepts are illustrated using an extensive spatial data set for the city of Tegucigalpa in Honduras. The paper intends to supplement the information given in the “Guidelines for Landslide Susceptibility, Hazard and Risk Zoning for Land Use Planning” by the Joint ISSMGE, ISRM and IAEG Technical Committee on Landslides and Engineered Slopes (JTC-1). The last few decades have shown a very fast development in the application of digital tools such as Geographic Information Systems, Digital Image Processing, Digital Photogrammetry and Global Positioning Systems. Landslide inventory databases are becoming available to more countries and several are now also available through the internet. A comprehensive landslide inventory is a must in order to be able to quantify both landslide hazard and risk. With respect to the environmental factors used in landslide hazard assessment, there is a tendency to utilize those data layers that are easily obtainable from Digital Elevation Models and satellite imagery, whereas less emphasis is on those data layers that require detailed field investigations. A review is given of the trends in collecting spatial information on environmental factors with a focus on Digital Elevation Models, geology and soils, geomorphology, land use and elements at risk.