Spatial distribution analysis and susceptibility mapping of landslides triggered before and after Mw7.8 Gorkha earthquake along Upper Bhote Koshi,Nepal

The 2015 Mw7.8 Gorkha earthquake triggered thousands of landslides of various types scattered over a large area. In the current study, we utilized pre- and post-earthquake high-resolution satellite imagery to compile two landslide inventories before and after earthquake and prepared three landslide susceptibility maps within 404 km² area using frequency ratio (FR) model. From the study, we could map about 519 landslides including 178 pre-earthquake slides and 341 coseismic slides were identified. This study investigated the relationship between landslide occurrence and landslide causative factors, i.e., slope, aspect, altitude, plan curvature, lithology, land use, distance from streams, distance from road, distance from faults, and peak ground acceleration. The analysis showed that the majority of landslides both pre-earthquake and coseismic occurred at slope >30°, preferably in S, SE, and SW directions and within altitude ranging from 1000 to 1500 m and 1500 to 3500 m. Scatter plots between number of landslides per km^?2 (LN) and percentage of landslide area (LA) and causative factors indicate that slope is the most influencing factor followed by lithology and PGA for the landslide formation. Higher landslide susceptibility before earthquake is observed along the road and rivers, whereas landslides after earthquake are triggered at steeper slopes and at higher altitudes. Combined susceptibility map indicates the effect of topography, geology, and land cover in the triggering of landslides in the entire basin. The resultant landslide susceptibility maps are verified through AUC showing success rates of 78, 81, and 77%, respectively. These susceptibility maps are helpful for engineers and planners for future development work in the landslide prone area.     

青藏高原大型深层蠕滑型滑坡变形机制研究进展与展望

大型深层蠕滑型滑坡在青藏高原怒江、澜沧江、金沙江、岷江等地形地貌和地质构造复杂区极为发育,具有规模大、滑带深、渐进变形破坏显著等特点,按照滑坡空间结构主要有后缘洼地蠕滑型、顺层基岩蠕滑型和厚层松散堆积物蠕滑型等3种类型,往往表现为长期蠕滑-间歇性复活-整体滑动.通过梳理大型深层蠕滑型滑坡稳定性影响因素、滑带土工程地质力学性质、地下水渗流场特征与降雨诱发滑坡滞后性以及渐进变形破坏机制和动态稳定性等4个方面的研究进展,提出了3个关键科学问题与4个主要研究方向.建议加强深层滑带土在渗流场-应力场等多场耦合作用下的工程地质力学特性研究、加强剖析滑坡岩土体的非均质渗透特性及地下水分布特征分析,研究不同雨强和历时条件下降雨有效入渗机理,研究大型深层蠕滑型滑坡的降水入渗响应过程和降水诱发滑坡变形的滞后性,提出基于渐进变形破坏的滑坡动态稳定性评价方法,为地质灾害早期判识和综合防范提供理论依据.     

层面倾角对顺层岩质滑坡贡献率研究

顺层岩质滑坡作为滑坡的一种类型,在国内很多省份均有较高的发生频率,造成了较大的经济损失及不良的社会影响。为了研究顺层岩质滑坡发育的规律,依据笔者参与并成功治理的国内81处顺层岩质滑坡建立数据库,利用贡献率法将不同层面倾角区间的顺层岩质滑坡的各种相互关系进行定量化分析,以研究不同层面倾角区间的顺层岩质滑坡的相关性。结果表明,层面倾角为10°～25°的坡体,对顺层岩质滑坡贡献率程度最高;层面倾角为25°～35°的坡体,对顺层岩质滑坡贡献率程度中等;层面倾角为大于35°及小于10°的坡体,对顺层岩质滑坡贡献率程度最低。所得分析结论与实际情况吻合较好,能很好地为以后国内顺层岩质滑坡的研究及治理提供借鉴参考     

多级旋转黄土滑坡基本类型及特征分析

多级旋转黄土滑坡因其分布密集、继发性强、滑体结构难以区分而成为我国黄土高原最为复杂的滑坡灾害类型.本文在引入多级旋转滑坡的定义的基础上,通过野外详细调查和工程勘察等手段,研究我国黄土高原地区典型的多级旋转黄土滑坡的基本类型、特征和成因.提出了金台型多级旋转黄土滑坡和黑方台型多级旋转黄土滑坡2种滑坡模式和滑坡结构特征,其...     

Susceptibility assessments of the Wenchuan earthquake-triggered landslides in Longnan using logistic regression

In this study a Wenchuan earthquake-induced landslide susceptibility assessment was carried out in the Longnan area in northwestern China using a GIS-based logistic regression model. This region has frequently been affected by landslides in the past, and was intensively affected by the 5.12 Wenchuan earthquake which received considerable international attention. The data used for this study consist of the landslides triggered by the Wenchuan earthquake and a landslide pre-disposing factor database. Information regarding the landslide causative factors came from additional data sources, such as a digital elevation model (DEM) with a 30 × 30 m² resolution, orthophotos, geological and land-use maps, precipitation records, and information on peak ground acceleration data from the 2008 earthquake. The statistical analysis of the relationship between the Wenchuan earthquake-triggered landslides and pre-disposing factors showed the great influence of lithological and topographical conditions on slope failures. The quality of susceptibility mapping was validated by splitting the study area into training and validation sections. The prediction capability analysis demonstrated that the landslide susceptibility map could be used for land planning as well as emergency planning by local authorities.     

http://www.sciencedirect.com/science/article/pii/S167498711400022X

The governing factors that influence landslide occurrences are complicated by the different soil conditions at various sites.To resolve the problem,this study focused on spatial information technology to collect data and information on geology.GIS,remote sensing and digital elevation model(DEM) were used in combination to extract the attribute values of the surface material in the vast study area of SheiPa National Park,Taiwan.The factors influencing landslides were collected and quantification values computed.The major soil component of loam and gravel in the Shei-Pa area resulted in different landslide problems.The major factors were successfully extracted from the influencing factors.Finally,the discrete rough set(DRS) classifier was used as a tool to find the threshold of each attribute contributing to landslide occurrence,based upon the knowledge database.This rule-based knowledge database provides an effective and urgent system to manage landslides.NDVI(Normalized Difference Vegetation Index),VI(Vegetation Index),elevation,and distance from the road are the four major influencing factors for landslide occurrence.The landslide hazard potential diagrams(landslide susceptibility maps) were drawn and a rational accuracy rate of landslide was calculated.This study thus offers a systematic solution to the investigation of landslide disasters.     

Inclusion of earthquake strong ground motion in a geographic information system-based landslide susceptibility zonation in Garhwal Himalayas

Garhwal Himalayas are seismically very active and simultaneously suffering from landslide hazards. Landslides are one of the most frequent natural hazards in Himalayas causing damages worth more than one billion US$ and around 200 deaths every year. Thus, it is of paramount importance to identify the landslide causative factors to study them carefully and rank them as per their influence on the occurrence of landslides. The difference image of GIS-derived landslide susceptibility zonation maps prepared for pre- and post-Chamoli earthquake shows the effect of seismic shaking on the occurrence of landslides in the Garhwal Himalaya. An attempt has been made to incorporate seismic shaking parameters in terms of peak ground acceleration with other static landslide causative factors to produce landslide susceptibility zonation map in geographic information system environment. In this paper, probabilistic seismic hazard analysis has been carried out to calculate peak ground acceleration values at different time periods for estimating seismic shaking conditions in the study area. Further, these values are used as one of the causative factors of landslides in the study area and it is observed that it refines the preparation of landslide susceptibility zonation map in seismically active areas like Garhwal Himalayas.     

逻辑回归模型在玉树地震滑坡危险性评价中的应用与检验

2010年4月14日07时49分(北京时间),青海省玉树县发生了Ms7.1级大地震。作者基于高分辨率遥感影像解译与现场调查验证的方法,圈定了2036处本次地震诱发滑坡。这些滑坡受地震地表破裂控制强烈,规模相对较小,常常密集成片分布。滑坡类型多样,以崩塌型滑坡为主,还包括滑动型、流滑型、碎屑流型、复合型等类型的滑坡。本文基于地理信息系统(GIS)与遥感(RS)技术,应用逻辑回归模型开展玉树地震滑坡危险性评价,并对结果合理性进行检验。应用GIS技术建立玉树地震滑坡灾害及相关滑坡影响因子空间数据库,选择高程、斜坡坡度、斜坡坡向、斜坡曲率、与水系距离、坡位、断裂、地层岩性、归一化植被指数(NDVI)、公路、同震地表破裂、地震动峰值加速度(PGA)共12个因子作为玉树地震滑坡影响因子,在GIS平台下将这些因子专题图层栅格化。应用逻辑回归模型得到每个因子分级的回归系数,然后建立滑坡危险性指数分布图。利用玉树地震滑坡空间分布图对滑坡危险性指数图进行检验,正确率达到83.21%。滑坡危险性分级结果表明,在占研究区总面积4.97%的"很高危险度"的较小范围内,实际发育滑坡数量为766个,占总滑坡面积的比例高达37.62%,表明地震滑坡危险性评价结果良好。不同危险性级别的滑坡点密度统计结果表明,滑坡点密度随着危险性级别的升高而非常迅速的升高。     

Recognition of large scale deep-seated landslides in forest areas of Taiwan using high resolution topography

Large deep-seated landslides can be reactivated during intense events, and they can evolve into destructive failures. They are generally difficult to recognize in the field, especially when they develop in densely forested areas. A detailed and constantly updated inventory map of such phenomena, and the recognition of their topographic signatures is absolutely a key tool for landslide risk mitigation.The aim of this work is to test in forested areas, the performance of the new automatic and objective methodology developed by Tarolli et al. (2012) for geomorphic features extraction (landslide crowns) from high resolution topography (LiDAR derived Digital Terrain Models – DTMs). The methodology is based on the detection of landslides through the use of thresholds obtained by the statistical analysis of variability of landform curvature. The study was conducted in a high-risk area located in the central-south Taiwan, where an accurate field survey on landsliding processes and a high-quality set of airborne laser scanner elevation data are available. The area has been chosen because some of the deep-seated landslides are located near human infrastructures and their reactivation is highly dangerous. Thanks to LiDAR’s capability to detect the bare ground elevation data in forested areas, it was possible to recognize in detail landslide features also in remote regions difficult to access. The results, if compared with the previous work of Tarolli et al. (2012), mainly focused on shallow landslides, and in a not forested area, indicate that for deep-seated landslides, where the crowns are more evident, and they are present at large scale, the tested methodology performs better (higher quality index). The method can be used to interactively assist the interpreter/user on the task of deep-seated landslide hazard mapping, and risk assessment planning of such regions.     

Probabilistic landslide hazard assessment using homogeneous susceptible units (HSU) along a national highway corridor in the northern Himalayas, India

The increased socio-economic significance of landslides has resulted in the application of statistical methods to assess their hazard, particularly at medium scales. These models evaluate where, when and what size landslides are expected. The method presented in this study evaluates the landslide hazard on the basis of homogenous susceptible units (HSU). HSU are derived from a landslide susceptibility map that is a combination of landslide occurrences and geo-environmental factors, using an automated segmentation procedure. To divide the landslide susceptibility map into HSU, we apply a region-growing segmentation algorithm that results in segments with statistically independent spatial probability values. Independence is tested using Moran’s I and a weighted variance method. For each HSU, we obtain the landslide frequency from the multi-temporal data. Temporal and size probabilities are calculated using a Poisson model and an inverse-gamma model, respectively. The methodology is tested in a landslide-prone national highway corridor in the northern Himalayas, India. Our study demonstrates that HSU can replace the commonly used terrain mapping units for combining three probabilities for landslide hazard assessment. A quantitative estimate of landslide hazard is obtained as a joint probability of landslide size, of landslide temporal occurrence for each HSU for different time periods and for different sizes.     

Spatial distribution of landslides induced by the 2004 Mid-Niigata prefecture earthquake,Japan

On October 23, 2004, an earthquake with a moment magnitude of 6.8 occurred in the Chuetsu area of Niigata prefecture in Japan. This earthquake is known as the 2004 Mid-Niigata prefecture earthquake; the event was followed by severe aftershocks and caused many types of landslides such as surficial slides, shallow slides, and deep slides. A large number of landslides occurred in the upland village of Yamakoshi, destroying the entire village; in addition, a huge number of houses collapsed in Kawaguchi town. This study investigates the correlations between each type of landslide and the bedding plane orientation and dip, and other geomorphologic conditions. The landslide occurrence ratio (LOR) is used as an index to determine the correlation between the 2004 Mid-Niigata prefecture earthquake-induced landslides and the slope angle, slope aspect, rock type, and bedding plane orientation and dip. This work also proposes a methodology to determine the geometric alignment between the topography and the orientation of geological bedding planes. The method provides an efficient means of estimating the topography/bedding plane relationship over large areas.     

Landslide susceptibility assessment using the bivariate statistical analysis and the index of entropy in the Sibiciu Basin (Romania)

The Sibiciu Basin is located in Romania between the Buzău Mountains and the Buzau Subcarpathians (Curvature Carpathians and Subcarpathians). The geology of the basin consists of Paleogene flysch deposits represented by an alternation of sandstones, marls, clays and schists and Neogene deposits represented by marls, clays and sands. The area is affected by different types of landslides (shallow, medium-deep and deep-seated failures). In Romania, in the last decades, direct and indirect methods have been applied for landslide susceptibility assessment. The most utilized before 2000 were based on qualitative approaches. This study evaluates the landslide susceptibility in the Sibiciu Basin using a bivariate statistical analysis and an index of entropy. A landslide inventory map was prepared, and a susceptibility estimate was assessed based on the following parameters which influence the landslide occurrence: slope angle, slope aspect, curvature, lithology and land use. The landslide susceptibility map was divided into five classes showing very low to very high landslide susceptibility areas.     

Quantifying geomorphic evolution of earthquake-triggered landslides and their relation to active normal faults. An example from the Gulf of Corinth, Greece

Photogrammetric analysis of aerial photographs is used to investigate morphological changes in two large landslides located adjacent to the active Marathias normal fault along the Gulf of Corinth, Greece. This E–W trending fault intersects at almost right angles a series of west-verging and east-dipping thrust faults, and has a clear geomorphic expression. The fault's structural signature, such as the trace length, displacement, segmentation, and scarp freshness resembles other normal faults within the Gulf of Corinth. Along this fault we mapped a series of landslides that are mainly concentrated at the near tip areas. Two of them are hosted in the damage zone formed by the intersecting normal and reverse faults. The Marathias and Sergoula landslides show a significant geomorphic evolution on aerial photographs from 1945 to 1991.

Evolution of landslides in the study area appears to be correlated with two earthquake clusters that drive mass wasting in the order of 10⁶ m³, significant drainage adjustment, and triggering of post-landslide river incision. We infer the following process sequence for these presumably earthquake-triggered landslides in the region: eroded material in Marathias landslide and reactivation of movement within the main body of the Sergoula landslide were observed in 1969 aerial photographs. Both landslides are deep-seated rotational rockslides. Obstruction or abandonment of channels due to the landslides establishes river incision and a dramatic increase of the rate of fan-delta progradation in the order of 1 m/yr. These large landslides are related to strong (M > 6.5) earthquakes concentrated along faults, and their reactivation period is almost a century, based on seismological or paleoseismological analyses.     

Machine Learning Feature Selection Methods for Landslide Susceptibility Mapping

This paper explores the use of adaptive support vector machines, random forests and AdaBoost for landslide susceptibility mapping in three separated regions of Canton Vaud, Switzerland, based on a set of geological, hydrological and morphological features. The feature selection properties of the three algorithms are studied to analyze the relevance of features in controlling the spatial distribution of landslides. The elimination of irrelevant features gives simpler, lower dimensional models while keeping the classification performance high. An object-based sampling procedure is considered to reduce the spatial autocorrelation of data and to estimate more reliably generalization skills when applying the model to predict the occurrence of new unknown landslides. The accuracy of the models, the relevance of features and the quality of landslide susceptibility maps were found to be high in the regions characterized by shallow landslides and low in the ones with deep-seated landslides. Despite providing similar skill, random forests and AdaBoost were found to be more efficient in performing feature selection than adaptive support vector machines. The results of this study reveal the strengths of the classification algorithms, but evidence: (1) the need for relying on more than one method for the identification of relevant variables; (2) the weakness of the adaptive scaling algorithm when used with landslide data; and (3) the lack of additional features which characterize the spatial distribution of deep-seated landslides.     

Deep-seated gravitational slope deformations triggered by extreme rainfall and agricultural practices (eastern Michoacan,Mexico)

The study of deep-seated gravitational slope deformations (DSGSD) in Mexico is scarce; therefore, their localization and causes are highly overlooked. The present paper examines the characterization of the DSGSD of Jungapeo and Las Pilas in eastern Michoacan state, currently active and endangering their inhabitants. An integrated study, including detailed lithology, morpho-structural inventories, analysis of land use, and pluviometric regime, was performed and complemented with differential global positioning system monitoring networks. Both landslides developed over highly weathered volcano-sedimentary rocks. On the one hand, the Jungapeo landslide has an estimated volume of 990,455 m³ with steady decreasing velocity rates from 41 to 15 cm/month in the first monitoring period to 13–3 cm/month in the last one. On the other hand, the Las Pilas landslide estimated volume is about 1,082,467 m³ with a stable velocity rate of 1.3 to 0.1 cm/month. Despite the multi-storeyed style of activity, two behaviors of instability were distinguished: slow deformation and secondary landslide stages. The conditioning factors for slow deformation in both DSGSD are the combination of weathered lithology with clay- and sand-rich content, and the shift toward intensive monoculture. The triggering factor is related to excess water produced by an inefficient flood-irrigation system that also generates an atypical acceleration behavior in both landslides during the dry season. The DSGSD activity thus predisposes the generation of tension cracks and secondary scarps from which the collateral landslides are triggered by atypical rainfall, such as that of 2010.     

Pre-conditioning factors and susceptibility assessments of Wenchuan earthquake landslide at the Zhouqu segment of Bailongjiang basin, China

In this study, we present a landslide susceptibility assessment carried out after the devastating 2008 Wenchuan earthquake. For the Zhouqu segment in the Bailongjiang basin in north-western China landslide susceptibility was computed by a logistic regression method. This region has been experiencing landslides for a long time, and numerous additional slope failures were triggered by the 2008 Wenchuan earthquake. The data used for this study consists of slope failures attributed to the 2008 earthquake, the 878 post Wenchuan earthquake landslides and collapses inventory build up by combination the field investigation, monoscopic manual interpretation, image classification and texture analysis using SPOT 5 and ALOS remote-sensing image data. All data derived from remote sensing images are validated during field investigations. The landslide pre-disposing factor database was constructed. A digital elevation model (DEM) with a 30 × 30 m resolution, orthophotos, geological and land-use maps and information on peak ground acceleration data from the 2008 earthquake is used. The statistical analysis of the relation between Wencuan earthquake-triggered landslides and pre-disposing factors show the great influence of lithological and topographical conditions for earthquake-triggered slope failures. The quality of susceptibility mapping was validated by splitting the study area into a training and validation set. The prediction capability analysis showed that the landslide susceptibility map could be used for land planning as well as emergency planning by local authorities in this region.     

Controlling parameter analyses and hazard mapping for earthquake-triggered landslides: an example from a square region in Beichuan County, Sichuan Province, China

On May 12, 2008, at 1428 hours (Beijing time), a catastrophic earthquake, with a magnitude of Ms 8.0, struck the Sichuan Province, China. About 200,000 landslides, as a secondary geological hazard associated with the earthquake, were triggered over a broad area. These landslides were of almost all types such as shallow, disrupted landslides, rock falls, deep-seated landslides, and rock avalanches. Some of these landslides damaged and destroyed large part of some towns, blocked roads, dammed rivers, and caused other serious damages. The purpose of this study is to detect correlations between landslide occurrence and the surface rupture plane, ground shaking conditions (measured by peak ground acceleration, PGA), lithology, slope gradient, slope aspect, topographic position, and distance from drainages by using two indices, landslide area percentage (LAP) and the landslide number density (LND), based on geographic information system (GIS) technology and statistical analysis method in a square region (study area) of Beichuan County, Sichuan Province, China. There were 5,096 landslides related with the earthquake which were delineated by visual interpretation and selected field checking throughout the study area. The total area (horizontal projection) of the 5,096 landslides is about 41.103 km². The LAP, which is defined as the percentage of the plane area affected by landslides, was 10.276 %, and the LND, means the number of landslides per square kilometers, was 12.74 landslides/km². Statistical analysis results show that both LAP and LND have a positive correlation with slope gradient and a negative correlation with distance from the surface rupture. However, the correlation between the occurrence of landslides with PGA, topographic position, and distance from drainages are uncertain, or has just a little positive correlation. The correlation between landslide and slope aspect also shows the effect of the directivity of the seismic wave. The Zbq formation had the most concentrated landslide activity with the LND value of 21.78 landslides/km _, ² and the ∈₁ q Gr. geological units had the highest LAP value. Furthermore, weight index (W _i) model is performed with a GIS platform to derive landslide hazard index map. The success rate of the model was 71.615 % and, thus, it was valid. In addition, comparison of five landslide controlling parameters’ influence on landslide occurrences was also carried out.     

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.