Landslide hazard assessment in the Himalayas (Nepal and Bhutan) based on Earth-Observation data
基于地球观测数据的喜马拉雅山（尼泊尔及不丹）滑坡灾害评估
Engineering Geology, Volume 237, 10 April 2018, Pages 217-228
Christian Ambrosi, Tazio Strozzi, Cristian Scapozza, Urs Wegmüller
摘要：The Himalayan range is a high-risk area where landslides can destroy villages, access roads, and other important infrastructures and cause numerous injuries and deaths each year. Hazard assessment is one of the most important actions in the disaster risk management strategy with a direct impact on land use and land planning. Because of a lack of diffuse field data and mapping, landslide hazard maps are however not available for vast regions of the Himalayas. Earth-Observation (EO) data can support the preparation of landslide hazard maps through the compilation of landslide inventory maps at regional scale by means of satellite photo-interpretation and the assessment of the state of activity of mapped phenomena based on surface displacement rates quantified from satellite SAR interferometry. We compiled landslide inventory maps and landslide hazard maps for two areas in Nepal and Bhutan. For the Lukla region in Nepal, our analysis indicates that 10.5% of the total area of 725 km2 is affected by landslides and 57% of the mapped landslides are classified as active. For the Chomolhari area in Bhutan, 6% of the total area of 620 km2 is affected by landslides and 55% of them are classified as active. For both regions rockslides represent the most mapped phenomena. Landslide hazard assessment over large regions based on EO products represents an important aspect for disaster risk reduction not only in the whole Himalayan region but also in other mountain areas worldwide in absence of detailed landslide inventory maps.
A spatial database for landslides in northern Bavaria: A methodological approach
巴伐利亚北部滑坡空间数据库：方法论
Geomorphology, Volume 306, 1 April 2018, Pages 283-291
Daniel Jäger, Thomas Kreuzer, Martina Wilde, Stefan Bemm, Birgit Terhorst
摘要：Landslide databases provide essential information for hazard modeling, damages on buildings and infrastructure, mitigation, and research needs. This study presents the development of a landslide database system named WISL (Würzburg Information System on Landslides), currently storing detailed landslide data for northern Bavaria, Germany, in order to enable scientific queries as well as comparisons with other regional landslide inventories. WISL is based on free open source software solutions (PostgreSQL, PostGIS) assuring good correspondence of the various softwares and to enable further extensions with specific adaptions of self-developed software. Apart from that, WISL was designed to be particularly compatible for easy communication with other databases. As a central pre-requisite for standardized, homogeneous data acquisition in the field, a customized data sheet for landslide description was compiled. This sheet also serves as an input mask for all data registration procedures in WISL. A variety of “in-database” solutions for landslide analysis provides the necessary scalability for the database, enabling operations at the local server. In its current state, WISL already enables extensive analysis and queries. This paper presents an example analysis of landslides in Oxfordian Limestones in the northeastern Franconian Alb, northern Bavaria. The results reveal widely differing landslides in terms of geometry and size. Further queries related to landslide activity classifies the majority of the landslides as currently inactive, however, they clearly possess a certain potential for remobilization. Along with some active mass movements, a significant percentage of landslides potentially endangers residential areas or infrastructure. The main aspect of future enhancements of the WISL database is related to data extensions in order to increase research possibilities, as well as to transfer the system to other regions and countries.
Assessment of active landslides using field electrical measurements
基于实地电测量的活动滑坡评估
Engineering Geology, Volume 233, 31 January 2018, Pages 146-159
Matthew M. Crawford, L. Sebastian Bryson
摘要：Landslide characterization and hazard assessments require multidisciplinary approaches that connect geologic processes with geotechnical parameters. Preexisting landslide activity, geology and geomorphology, soil strength, and hydrologic conditions are complex factors that affect landslide behavior. Often, the connections among these factors are not made for hazard assessments, forecasting, or slope stability modeling. Therefore, geophysical and geotechnical techniques for landslide investigations are typically assessed independently. This study aims to bring together different techniques to develop a methodology that connects electrical measurements and shear strength. A framework has been developed for using electrical resistivity measurements that will support and facilitate the prediction of shear strength within a slope. In-situ volumetric water content, soil-water potential (suction), and electrical conductivity were measured from two shallow colluvial landslides in Kentucky. Repeated surface electrical resistivity survey measurements were used to characterize the failure zone and lithology, and to compare with the in-situ hydrologic measurements. The data show that subsurface moisture conditions over time can be reflected in the inversions of repeated ER surveys, thus allowing electrical measurements and geotechnical parameters to be correlated. This study demonstrates that electrical resistivity can be used as a tool for landslide monitoring and to assess shear strength. These parameters are pertinent to investigating the stability of landslides that are often triggered or reactivated by rainfall.
A review of statistically-based landslide susceptibility models
基于统计方法的滑坡易发性模型综述
Earth-Science Reviews, Volume 180, May 2018, Pages 60-91
Paola Reichenbach, Mauro Rossi, Bruce D. Malamud, Monika Mihir, Fausto Guzzetti
摘要：In this paper, we do a critical review of statistical methods for landslide susceptibility modelling and associated terrain zonations. Landslide susceptibility is the likelihood of a landslide occurring in an area depending on local terrain conditions, estimating “where” landslides are likely to occur. Since the first attempts to assess landslide susceptibility in the mid-1970s, hundreds of papers have been published using a variety of approaches and methods in different geological and climatic settings. Here, we critically review the statistically-based landslide susceptibility assessment literature by systematically searching for and then compiling an extensive database of 565 peer-review articles from 1983 to 2016. For each article in the literature database, we noted 31 categories/sub-categories of information including study region/extent, landslide type/number, inventory type and period covered, statistical model used, including variable types, model fit/prediction performance evaluation method, and strategy used to assess the model uncertainty. We present graphical visualisations and discussions of commonalities and differences found as a function of region and time, revealing a significant heterogeneity of thematic data types and scales, modelling approaches, and model evaluation criteria. We found that the range of thematic data types used for susceptibility assessment has not changed significantly with time, and that for a number of studies the geomorphological significance of the thematic data used is poorly justified. We also found that the most common statistical methods for landslide susceptibility modelling include logistic regression, neural network analysis, data-overlay, index-based and weight of evidence analyses, with an increasing preference towards machine learning methods in the recent years. Although an increasing number of studies in recent years have assessed the model performance, in terms of model fit and prediction performance, only a handful of studies have evaluated the model uncertainty. Adopting a Susceptibility Quality Level index, we found that the quality of published models has improved over the years, but top-quality assessments remain rare. We identified a clear geographical bias in susceptibility study locations, with many studies in China, India, Italy and Turkey, and only a few in Africa, South America and Oceania. Based on previous literature reviews, the analysis of the information collected in the literature database, and our own experience on the subject, we provide recommendations for the preparation, evaluation, and use of landslide susceptibility models and associated terrain zonations.
From landslide susceptibility to landslide frequency: A territory-wide study in Hong Kong
从滑坡易发性到滑坡频率：香港全域研究
Engineering Geology, In press, accepted manuscript, Available online 3 May 2018
Florence W.Y. Ko, Frankie L.C. Lo
摘要：Rain-induced shallow landslide is the major type of landslide that happens on natural terrain in Hong Kong due to its high seasonal rainfall and deep weathering soil profile. The Geotechnical Engineering Office has been in a leading role to steer the risk management of natural terrain landslides in Hong Kong. Recently, the territory-wide rainfall-based landslide susceptibility model (in terms of landslide density per year) has been developed to predict the number of natural terrain landslides that may occur in an anticipated rainfall event. Subsequently, the storm-based landslide density has been transformed to the annual landslide frequency to compile the territory-wide landslide frequency map by incorporating the mean annual frequency of occurrence of different probable rainfall scenarios. The annual rainfall frequency of a particular rainfall scenario is derived from its return period, determined based on the abundant real-time rainfall data at a five-minute interval from 110 automatic raingauges across Hong Kong at an average density of 10 km2/gauge. The transformation is discussed in this paper, together with the evaluation of the performance of the landslide frequency map. In addition, the potential applications of the map in Hong Kong and the pitfalls of the common evaluation methods are highlighted.
