Landslide susceptibility mapping using Bayesian approach in the Sultan Mountains (Akşehir,Turkey)

Landslides cause heavy damage to property and infrastructure, in addition to being responsible for the loss of human lives in many parts of the Turkey. The paper presents GIS-based spatial data analysis for landslide susceptibility mapping in the regions of the Sultan Mountains, West of Akşehir, and central part of Turkey. Landslides occur frequently in the area and seriously affect local living conditions. Therefore, spatial analysis of landslide susceptibility in the Sultan Mountains is important. The relationships between landslide distributions with the 19 landslide affecting parameters were analysed using a Bayesian model. In the study area, 90 landslides were observed. The landslides were randomly subdivided into 80 training landslides and 10 test landslides. A landslide susceptibility map was produced by using the training landslides. The test landslides were used in the accuracy control of the produced landslide susceptibility map. Approximately 9% of the study area was classified as high susceptibility zone. Medium, low and very low susceptibility zones covered 8, 23 and 60% of the study area, respectively. Most of the locations of the observed landslides actually fall into moderate (17.78%) and high (77.78. %) susceptibility zones of the produced landslide susceptibility map. This validates the applicability of proposed methods, approaches and the classification scheme. The high susceptibility zone is along both sides of the Akşehir Fault and at the north-eastern slope of the Sultan Mountains. It was determined that the surface area of the Harlak and Deresenek formations, which have attained lithological characteristics of clayey limestone with a broken and separated base, and where area landslides occur, possesses an elevation of 1,100–1,600 m, a slope gradient of 25°–35° and a slope aspect of 22.5°–157.5° facing slopes.     

Do landslides follow landslides? Insights in path dependency from a multi-temporal landslide inventory

Landslides are a major category of natural disasters, causing loss of lives, livelihoods and property. The critical roles played by triggering (such as extreme rainfall and earthquakes), and intrinsic factors (such as slope steepness, soil properties and lithology) have previously successfully been recognized and quantified using a variety of qualitative, quantitative and hybrid methods in a wide range of study sites. However, available data typically do not allow to investigate the effect that earlier landslides have on intrinsic factors and hence on follow-up landslides. Therefore, existing methods cannot account for the potentially complex susceptibility changes caused by landslide events. In this study, we used a substantially different alternative approach to shed light on the potential effect of earlier landslides using a multi-temporal dataset of landslide occurrence containing 17 time slices. Spatial overlap and the time interval between landslides play key roles in our work. We quantified the degree to which landslides preferentially occur in locations where landslides occurred previously, how long such an effect is noticeable, and how landslides are spatially associated over time. We also investigated whether overlap with previous landslides causes differences in landslide geometric properties. We found that overlap among landslides demonstrates a clear legacy effect (path dependency) that has influence on the landslide affected area. Landslides appear to cause greater susceptibility for follow-up landslides over a period of about 10  years. Follow-up landslides are on average larger and rounder than landslides that do not follow earlier slides. The effect of earlier landslides on follow-up landslides has implications for understanding of the landslides evolution and the assessment of landslide susceptibility.     

Assessment of geo-environmental problems of the Zonguldak province (NW Turkey)

The Zonguldak province is a coastal settlement area that has been suffering from serious natural and human-induced environmental problems sourced by its geology and geomorphology. Since the province locates at the heart of a coal-producing basin, the geo-environmental problems related to mining activities such as esthetic degradation, disposal of mining wastes and subsidence of the abandoned coal galleries are badly affecting every day life in Zonguldak province. Disposal of municipal wastes is also a big problem since only one municipality out of 32 has a sanitary disposal area. The rest of the municipalities dispose their solid wastes to rivers or to the sea. The province has also some health problems, which are pointed out in the literature, related to coal mining and geologic environment. These are cytogenetic damage in peripheral lymphocytes and pheumoconiosis (most commonly seen at coal workers), goiter and cancer. Landslides are the most important hazards in the area since 13% of the total surface of the Zonguldak is affected by landslides. In this study, considering the hazard potential special attention is given to deep landslides and using the stepwise forward conditional logistic regression technique, the landslide susceptibility map for the Zonguldak province is produced. The results showed that the most important independent variables governing the landslides are slope gradient, volcanic, and sedimentary rocks of Eocene and clastic and carbonate units of Cretaceous. The landslide map is used as a base map for the production of geo-hazard reconnaissance map on which areas subjected to other important geo-hazards (flood, earthquake and subsidence) are also shown to provide guidance for both existing settlement areas to take the necessary preventive measures and for new developing settlement areas to avoid the problematic areas.     

证据权法在区域滑坡危险性评价中的应用以贵州省为例

以GIS为技术平台,采用证据权法对研究区进行了滑坡地质灾害危险性分析。综合分析历史滑坡数据及其环境因素和触发因素,数据源主要有地形图、DEM、地质图,选取地层岩性、构造、高程、坡度、坡向、地形起伏度、道路、水系作为危险性评价因子。首先应用ArcGIS软件对数据源进行处理,提取各个评价因子图层,并对每个图层进行分级、缓冲区分析等处理,建立若干证据层。然后将历史灾害点与评价因子进行空间关联分析,计算每个评价因子等级的权重,最后计算出评价单元的危险性指数,并将危险性分为极高危险区、高危险区、中等危险区、低危险区。采用成功率曲线法对证据权法评价精度进行验证,结果表明本次评价的精度为71%。利用历史滑坡数据对评价结果进行验证,结果显示评价结果与实际情况较为吻合,说明证据权可以客观定量地评价各影响因子对滑坡的影响程度,该方法应用于区域地质灾害危险性评价比较有效。     

Linear discriminant analysis to describe the relationship between rainfall and landslides in Bogotá, Colombia

Bogotá is located in the central Andean region of Colombia, which is frequently affected by landslide processes. These processes are mostly triggered during the rainy season in the city. This fact remarks the importance of determining what rain-derived parameters (e.g. intensity, antecedent rain, daily rain) are better related with the occurrence of landslides. For this purpose, the linear discriminant analysis (LDA), a technique derived from multivariate statistics, was used. The application of this type of analysis led to obtain simple mathematical functions that represent the probability of occurrence of landslides in Bogotá. The functions also allow to identify the most relevant variables derived from records of rainfall linked to the generation of landslides. A proof of concept using the proposed methodology was done using historic rainfall data from a 9-km² area of homogenous climatology and geomorphology in the south part of Bogotá. Landslides needed to be grouped for the LDA. Each one of these grouping categories represents landslides that occurred in similar geomorphologic conditions. Another set of events with no landslides was generated synthetically. Results of the proof of concept show that rainfall parameters such as normalized rainfall intensity I _MAP, normalized daily rainfall R _MAP and rainy-days normal RDN have the best statistical correlation with the landslides observed in the zone of analysis.     

Slope failures on the flanks of the western Canary Islands

Landslides have been a key process in the evolution of the western Canary Islands. The younger and more volcanically active Canary Islands, El Hierro, La Palma and Tenerife, show the clearest evidence of recent landslide activity. The evidence includes landslide scars on the island flanks, debris deposits on the lower island slopes, and volcaniclastic turbidites on the floor of the adjacent ocean basins. At least 14 large landslides have occurred on the flanks of the El Hierro, La Palma and Tenerife, the majority of these in the last 1 million years, with the youngest, on the northwest flank of El Hierro, as recent as 15 thousand years in age. Older landslides undoubtedly occurred, but are difficult to quantify because the evidence is buried beneath younger volcanic rocks and sediments. Landslides on the Canary Island flanks can be categorised as debris avalanches, slumps or debris flows. Debris avalanches are long runout catastrophic failures which typically affect only the superficial part of the island volcanic sequence, up to a maximum thickness of 1 to 2 km. They are the commonest type of landslide mapped. In contrast, slumps move short distances and are deep-rooted landslides which may affect the entire thickness of the volcanic edifice. Debris flows are defined as landslides which primarily affect the sedimentary cover of the submarine island flanks. Some landslides are complex events involving more than one of the above end-member processes.Individual debris avalanches have volumes in the range of 50–500 km³, cover several thousand km² of seafloor, and have runout distances of up to 130 km from source. Overall, debris avalanche deposits account for about 10% of the total volcanic edifices of the small, relatively young islands of El Hierro and La Palma. Some parameters, such as deposit volumes and landslide ages, are difficult to quantify. The key characteristics of debris avalanches include a relatively narrow headwall and chute above 3000 m water depth on the island flanks, broadening into a depositional lobe below 3000 m. Debris avalanche deposits have a typically blocky morphology, with individual blocks up to a kilometre or more in diameter. However, considerable variation exists between different avalanche deposits. At one extreme, the El Golfo debris avalanche on El Hierro has few large blocks scattered randomly across the avalanche surface. At the other, Icod on the north flank of Tenerife has much more numerous but smaller blocks over most of its surface, with a few very large blocks confined to the margins of the deposit. Icod also exhibits flow structures (longitudinal shears and pressure ridges) that are absent in El Golfo. The primary controls on the block structure and distribution are inferred to be related to the nature of the landslide material and to flow processes. Observations in experimental debris flows show that the differences between the El Golfo and Icod landslide deposits are probably controlled by the greater proportion of fine grained material in the Icod landslide. This, in turn, relates to the nature of the failed volcanic rocks, which are almost entirely basalt on El Hierro but include a much greater proportion of pyroclastic deposits on Tenerife.Landslide occurrence appears to be primarily controlled by the locations of volcanic rift zones on the islands, with landslides propagating perpendicular to the rift orientation. However, this does not explain the uneven distribution of landslides on some islands which seems to indicate that unstable flanks are a ‘weakness’ that can be carried forward during island development. This may occur because certain island flanks are steeper, extend to greater water depths or are less buttressed by the surrounding topography, and because volcanic production following a landslide my be concentrated in the landslide scar, thus focussing subsequent landslide potential in this area. Landslides are primarily a result of volcanic construction to a point where the mass of volcanic products fails under its own weight. Although the actual triggering factors are poorly understood, they may include or be influenced by dyke intrusion, pore pressure changes related to intrusion, seismicity or sealevel/climate changes. A possible relationship between caldera collapse and landsliding on Tenerife is not, in our interpretation, supported by the available evidence.     

万(州)-梁(平)高速公路K34～K59段滑坡成因分析

万(州)-梁(平)高速公路K34-K59段滑坡十分发育，是重庆境内滑坡灾害最为严重的一段。该区地质条件复杂，岩体中缓倾角结构面、软化夹层发育，在外界因素触发下，即可形成岩层向临空面松弛滑移的依附面。1999年12月-2003年9月，该路段发生滑坡灾害23处，增加工程投资2亿多元，对高速公路的建设造成很大的危害和威胁，并拖延了工期，给国民经济建设带来严重的影响和损失。文章依据工程地质勘察结果，从该滑坡的地质环境及变形特征分析，对其形成机制做了深入研究，为今后类似滑坡的防治提供参考。近年来，在高等级公路的建设中，线形要求严格，在山区及丘陵地区往往需要采用开挖方式通过，由于建设中的不合理工程活动，新滑坡的产生以及老滑坡的复活可能性大增。致使滑坡灾害日趋严重。通过对影响岩质路堑边坡稳定性因素分析，说明了这些影响因素与边坡稳定性的关系。文章认为特殊的地质构造及易滑地层的广泛分布，是滑坡大量出现的地质基础。大量降雨入渗，不合理的人为工程是滑坡的诱发因素。各种情况表明，在今后一定时期内，人类活动可能成为滑坡的主要影响因素。     

延川县滑坡灾害发育特征和分布规律研究

延川县滑坡灾害以中小型黄土滑坡为主,滑坡外形具有明显的圈椅状。滑坡沿河流两侧呈条带状分布,灾害多形成于降雨集中的6~9月份。     

Utilizing crowdsourcing to enhance the mitigation and management of landslides

Landslides are mainly triggered by earthquakes and rainfall and have poor temporal predictability. Landslides pose significant threats to settlements and infrastructure in mountainous regions around the world. To mitigate this natural hazard, a new paradigm of landslide mitigation and management is required. Increasing smartphone ownership around the world, especially in developing countries, offers scientists an opportunity to embrace crowdsourcing so as to improve landslide research. This paper presents a new landslide information system (LIS) comprising a smartphone app and an administrative interface and database. The mobile app has been published for both iPhone and Android platforms. The interface of the smartphone app is powered by the highly-customizable Google Maps platform, which is overlaid with real-time landslide data. Users can choose between visualizing “known sites” and “contribution” of landslide data. The visualization option shows published landslides and areas that are susceptible. Users can contribute their GPS coordinates and multimedia to enhance landslide reports. A comparison with similar systems, potential applications, and challenges of using smartphone technology for mitigating landslides are also discussed.     

Spatiotemporal modelling of rainfall-induced landslides using machine learning

Landslides - Natural terrain landslides are mainly triggered by rainstorms in Hong Kong, which pose great threats to life and property. To mitigate landslide risk, building a prediction model which...     

Landslide databases in the Geological Surveys of Europe

Landslides are one of the most widespread geohazards in Europe, producing significant social and economic impacts. Rapid population growth in urban areas throughout many countries in Europe and extreme climatic scenarios can considerably increase landslide risk in the near future. Variability exists between European countries in both the statutory treatment of landslide risk and the use of official assessment guidelines. This suggests that a European Landslides Directive that provides a common legal framework for dealing with landslides is necessary. With this long-term goal in mind, this work analyzes the landslide databases from the Geological Surveys of Europe focusing on their interoperability and completeness. The same landslide classification could be used for the 849,543 landslide records from the Geological Surveys, from which 36% are slides, 10% are falls, 20% are flows, 11% are complex slides, and 24% either remain unclassified or correspond to another typology. Most of them are mapped with the same symbol at a scale of 1:25,000 or greater, providing the necessary information to elaborate European-scale susceptibility maps for each landslide type. A landslide density map was produced for the available records from the Geological Surveys (LANDEN map) showing, for the first time, 210,544 km² landslide-prone areas and 23,681 administrative areas where the Geological Surveys from Europe have recorded landslides. The comparison of this map with the European landslide susceptibility map (ELSUS 1000 v1) is successful for most of the territory (69.7%) showing certain variability between countries. This comparison also permitted the identification of 0.98 Mkm² (28.9%) of landslide-susceptible areas without records from the Geological Surveys, which have been used to evaluate the landslide database completeness. The estimated completeness of the landslide databases (LDBs) from the Geological Surveys is 17%, varying between 1 and 55%. This variability is due to the different landslide strategies adopted by each country. In some of them, landslide mapping is systematic; others only record damaging landslides, whereas in others, landslide maps are only available for certain regions or local areas. Moreover, in most of the countries, LDBs from the Geological Surveys co-exist with others owned by a variety of public institutions producing LDBs at variable scales and formats. Hence, a greater coordination effort should be made by all the institutions working in landslide mapping to increase data integration and harmonization.     

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.     

Threat from above! Assessing the risk from the Tonghua high-locality landslide in Sichuan,China

Landslides - In tectonically active steep mountain belts, such as those in west Sichuan in China, frequent landslide disasters can occur during the rainy season. High-locality landslides often...     

甘肃黄土台塬区农业过量灌溉引起的滑坡灾害

黄土台塬区过量农业灌溉可引起严重的滑坡灾害。其中以甘肃省永靖县黑方台提灌区的滑坡灾害最为典型。黑方台黄土台塬自20世纪60年代开始农业提水灌溉，受其独特的地质地貌控制，在灌溉水大量入渗的诱发下，滑坡灾害十分严重。主要有黄土滑坡和黄土一基岩滑坡两种类型，分别具有高速远程和低速近程滑动的特点。过量灌溉引发的滑坡灾害具有滞后性、群发性和频发性等显著特征，且在季节分布上主要集中在冻融期(3月)和雨季(7月)。实践表明，对过量灌溉引发的滑坡灾害应以预防为主，治理为辅。改变灌溉方式和采取包括工程治理措施、排水措施、生物措施在内的综合治理措施是行之有效的防治措施。     

The assessment of landslide susceptibility mapping using random forest and decision tree methods in the Three Gorges Reservoir area,China

Landslide susceptibility mapping is an indispensable prerequisite for landslide prevention and reduction. At present, research into landslide susceptibility mapping has begun to combine machine learning with remote sensing and geographic information system (GIS) techniques. The random forest model is a new integrated classification method, but its application to landslide susceptibility mapping remains limited. Landslides represent a serious threat to the lives and property of people living in the Zigui–Badong area in the Three Gorges region of China, as well as to the operation of the Three Gorges Reservoir. However, the geological structure of this region is complex, involving steep mountains and deep valleys. The purpose of the current study is to produce a landslide susceptibility map of the Zigui–Badong area using a random forest model, multisource data, GIS, and remote sensing data. In total, 300 pre-existing landslide locations were obtained from a landslide inventory map. These landslides were identified using visual interpretation of high-resolution remote sensing images, topographic and geologic data, and extensive field surveys. The occurrence of landslides is closely related to a series of environmental parameters. Topographic, geologic, Landsat-8 image, raining data, and seismic data were used as the primary data sources to extract the geo-environmental factors influencing landslides. Thirty-four layers of causative factors were prepared as predictor variables, which can mainly be categorized as topographic, geological, hydrological, land cover, and environmental trigger parameters. The random forest method is an ensemble classification technique that extends diversity among the classification trees by resampling the data with replacement and randomly changing the predictive variable sets during the different tree induction processes. A random forest model was adopted to calculate the quantitative relationships between the landslide-conditioning factors and the landslide inventory map and then generate a landslide susceptibility map. The analytical results were compared with known landslide locations in terms of area under the receiver operating characteristic curve. The random forest model has an area ratio of 86.10%. In contrast to the random forest (whole factors, WF), random forest (12 major factors, 12F), decision tree (WF), decision tree (12F), the final result shows that random forest (12F) has a higher prediction accuracy. Meanwhile, the random forest models have higher prediction accuracy than the decision tree model. Subsequently, the landslide susceptibility map was classified into five classes (very low, low, moderate, high, and very high). The results demonstrate that the random forest model achieved a reasonable accuracy in landslide susceptibility mapping. The landslide hazard zone information will be useful for general development planning and landslide risk management.     

Centrifuge modelling of landslides and landslide hazard mitigation: A review

Landslides are serious geohazards that occur under a variety of climatic conditions and can cause many casualties and significant economic losses. Centrifuge modelling, as a representative type of physical modelling, provides a realistic simulation of the stress level in a small-scale model and has been applied over the last 50 years to develop a better understanding of landslides. With recent developments in this technology, the application of centrifuge modelling in landslide science has significantly increased. Here, we present an overview of physical models that can capture landslide processes during centrifuge modelling. This review focuses on (i) the experimental principles and considerations, (ii) landslide models subjected to various triggering factors, including centrifugal acceleration, rainfall, earthquakes, water level changes, thawing permafrost, excavation, external loading and miscellaneous conditions, and (iii) different methods for mitigating landslides modelled in centrifuge, such as the application of nails, piles, geotextiles, vegetation, etc. The behaviors of all the centrifuge models are discussed, with emphasis on the deformation and failure mechanisms and experimental techniques. Based on this review, we provide a best-practice methodology for preparing a centrifuge landslide test and propose further efforts in terms of the seven aspects of model materials, testing design and equipment, measurement methods, scaling laws, full-scale test applications, landslide early warning, and 3D modelling to better understand the complex behaviour of landslides.     

汶川八级地震滑坡特征分析

汶川地震诱发的15000多处滑坡明显受地震断裂控制,主要沿龙门山主中央断裂带和后山断裂带展布,沿龙门山主中央断裂带汶川映秀安县高川北川陈家坝平武南坝一线,滑坡面密度大于50%以上,最大可达70%。沿断裂带形成了大量的松动山体,在暴雨期间极易发生滑坡、泥石流灾害,对灾后重建构成严重威胁。据初步调查,汶川地震触发的体积最大的滑坡是位于主中央断裂带上的安县高川大光包滑坡,滑动距离长4500m,滑坡堆积体长2800m,宽1700~2200m,最大厚度达580m,若以平均厚度200m计,体积达11亿m3为我国已发生的单体滑坡之最。与常见滑坡明显不同的是,汶川地震极震区滑坡的滑床往往不具连续完整的滑面,剪出口滑坡特征不明显,呈现明显的尖点突起或边缘突出特征,反映出上部滑体被地震力振动解体,甚至抛掷后与下部滑床边缘发生撞击。以阶型滑坡、凸型滑坡、勺型崩滑、座落型（振胀型）滑坡和巨大滚石5种类型最为典型。根据强震地面运动纪录和大量实例调查表明,在汶川地震极震区,触发滑坡的地震竖向力作用是非常明显的,大量滑坡经历了初始斜坡（风化碎裂岩体）地震抛掷撞击崩裂高速滑流的作用过程。     

Assessment of lithology and geomorphic control on slope instability in Raigad district,Maharashtra

Landslides are common along western slopes of Sahyadri ranges and isolated hills of coastal plains in Konkan region of Maharashtra. Numerous landslides with low magnitude is an important characteristic of slope failures in this region. Though the magnitude of landslides in this region is low, they result in huge losses in terms of property damage and even loss of lives especially those occur along major communication routes. Present paper deals with the spatial distribution of landslides in Raigad district, Maharashtra based on the historical landslide records and field investigations. The landslide occurrence and its relationship with the rainfall has been assessed to determine the role of rainfall, lithology and geomorphology in slope failures. The results of the study revealed that the concentration of landslides in Raigad district is observed in the south and south-eastern hilly tracts of the district. It is observed that the landslide process in this study area is also influenced by geo-environmental factors such as slope, aspect, structure, drainage, roads etc.     

Landslide susceptibility mapping for a landslide-prone area (Findikli,NE of Turkey) by likelihood-frequency ratio and weighted linear combination models

Landslides are very common natural problems in the Black Sea Region of Turkey due to the steep topography, improper use of land cover and adverse climatic conditions for landslides. In the western part of region, many studies have been carried out especially in the last decade for landslide susceptibility mapping using different evaluation methods such as deterministic approach, landslide distribution, qualitative, statistical and distribution-free analyses. The purpose of this study is to produce landslide susceptibility maps of a landslide-prone area (Findikli district, Rize) located at the eastern part of the Black Sea Region of Turkey by likelihood frequency ratio (LRM) model and weighted linear combination (WLC) model and to compare the results obtained. For this purpose, landslide inventory map of the area were prepared for the years of 1983 and 1995 by detailed field surveys and aerial-photography studies. Slope angle, slope aspect, lithology, distance from drainage lines, distance from roads and the land-cover of the study area are considered as the landslide-conditioning parameters. The differences between the susceptibility maps derived by the LRM and the WLC models are relatively minor when broad-based classifications are taken into account. However, the WLC map showed more details but the other map produced by LRM model produced weak results. The reason for this result is considered to be the fact that the majority of pixels in the LRM map have high values than the WLC-derived susceptibility map. In order to validate the two susceptibility maps, both of them were compared with the landslide inventory map. Although the landslides do not exist in the very high susceptibility class of the both maps, 79% of the landslides fall into the high and very high susceptibility zones of the WLC map while this is 49% for the LRM map. This shows that the WLC model exhibited higher performance than the LRM model.