An open dataset for landslides triggered by the 2016 Mw 7.8 Kaikōura earthquake,New Zealand

On November 14, 2016, the northeastern South Island of New Zealand was hit by the magnitude Mw 7.8 Kaikōura earthquake, which is characterized by the most complex rupturing mechanism ever recorded. The widespread landslides triggered by the earthquake make this event a great case study to revisit our current knowledge of earthquake-triggered landslides in terms of factors controlling the spatial distribution of landslides and the rapid assessment of geographic areas affected by widespread landsliding. Although the spatial and size distributions of landslides have already been investigated in the literature, a polygon-based co-seismic landslide inventory with landslide size information is still not available as of June 2021. To address this issue and leverage this large landslide event, we mapped 14,233 landslides over a total area of approximately 14,000 km². We also identified 101 landslide dams and shared them all via an open-access repository. We examined the spatial distribution of co-seismic landslides in relation to lithologic units and seismic and morphometric characteristics. We analyzed the size statistics of these landslides in a comparative manner, by using the five largest co-seismic landslide inventories ever mapped (i.e., Chi-Chi, Denali, Wenchuan, Haiti, and Gorkha). We compared our inventory with respect to these five ones to answer the question of whether the landslides triggered by the 2016 Kaikōura earthquake are less numerous and/or share size characteristics similar to those of other strong co-seismic landslide events. Our findings show that the spatial distribution of the Kaikōura landslide event is not significantly different from those belonging to other extreme landslide events, but the average landslide size generated by the Kaikōura earthquake is relatively larger compared to some other large earthquakes (i.e., Wenchuan and Gorkha).

     

Landslides triggered by slipping-fault-generated earthquake on a plateau: an example of the 14 April 2010, Ms 7.1, Yushu, China earthquake

On 14 April 2010 at 07:49 (Beijing time), a catastrophic earthquake with Ms 7.1 struck Yushu County, Qinghai Province, China. A total of 2,036 landslides were interpreted from aerial photographs and satellite images, verified by selected field checking. These landslides cover about a total area of 1.194 km². The characteristics and failure mechanisms of these landslides are presented in this paper. The spatial distribution of the landslides is evidently strongly controlled by the locations of the main co-seismic surface fault ruptures. The landslides commonly occurred close together. Most of the landslides are small; there were only 275 individual landslide (13.5 % of the total number) surface areas larger than 1,000 m². The landslides are of various types. They are mainly shallow, disrupted landslides, but also include rock falls, deep-seated landslides, liquefaction-induced landslides, and compound landslides. Four types of factors are identified as contributing to failure along with the strong ground shaking: natural excavation of the toes of slopes, which mean erosion of the base of the slope, surface water infiltration into slopes, co-seismic fault slipping at landslide sites, and delayed occurrence of landslides due to snow melt or rainfall infiltration at sites where slopes were weakened by the co-seismic ground shaking. To analyze the spatial distribution of the landslides, the landslide area percentage (LAP) and landslide number density (LND) were compared with peak ground acceleration (PGA), distance from co-seismic main surface fault ruptures, elevation, slope gradient, slope aspect, and lithology. The results show landslide occurrence is strongly controlled by proximity to the main surface fault ruptures, with most landslides occurring within 2.5 km of such ruptures. There is no evident correlation between landslide occurrences and PGA. Both LAP and LND have strongly positive correlations with slope gradient, and additionally, sites at elevations between 3,800 and 4,000 m are relatively susceptible to landslide occurrence; as are slopes with northeast, east, and southeast slope aspects. Q₄ al-pl, N, and T₃ kn ¹ have more concentrated landslide activity than others. This paper provides a detailed inventory map of landslides triggered by the 2010 Yushu earthquake for future seismic landslide hazard analysis and also provides a study case of characteristics, failure mechanisms, and spatial distribution of landslides triggered by slipping-fault generated earthquake on a plateau.     

Statistical analysis of landslides caused by the Mw 6.9 Yushu,China, earthquake of April 14, 2010

The April 14, 2010 Yushu, China, earthquake (Mw 6.9) triggered a great number of landslides. At least 2,036 co-seismic landslides, with a total coverage area of 1.194 km², were delineated by visual interpretation of aerial photographs and satellite images taken following the earthquake, and verified by field inspection. Based on the mapping results, a statistical analysis of the spatial distribution of these landslides is performed using the landslide area percentage (LAP), defined as the percentage of the area affected by the landslides, and landslide number density (LND), defined as the number of landslides per square kilometer. The purpose is to clarify how the landslides correlate the control factors, which are the elevation, slope angle, slope aspect, slope position, distance from drainages, lithology, distance from the surface rupture, and peak ground acceleration (PGA). The results show that both LAP and LND have strongly positive correlations with slope angle and negative correlations with distance from the surface rupture and distance from drainages. The highest LAP and LPD values are in places of elevations from 3,800 to 4,000 m. The slopes producing landslides are mostly facing toward NE, E, and SE. The geological units of Q₄ al-pl, N, and T₃ kn ¹ have the highest concentrations of co-seismic landslides. No apparent correlations are present between LAP and LND values and PGA. On both sides of the surface rupture, the landslide distributions are almost similar except a few exceptions, likely associated with the nature of the strike-slip seismogenic fault for this event. The bivariate statistical analysis shows that, in descending order, the earthquake-triggered landslide impact factors are distance from surface rupture > slope angle > distance from drainages > lithology > PGA. Besides, as the detailed co-seismic landslides inventories related to strike-slip earthquakes are still few compared with that of thrusting-fault earthquakes, this case study would shed new light on the subject. For instance, the landslide spatial distribution on both sides of the strike-slip seismogenic fault is rather different from that of thrusting-fault earthquakes. It reminds us to take different strategies of measures for prevention and mitigation of landslides induced by earthquakes with different mechanisms.     

Landslides triggered by the 22 July 2013 Minxian–Zhangxian,China, Mw 5.9 earthquake: Inventory compiling and spatial distribution analysis

On July 22, 2013, an earthquake of Ms. 6.6 occurred at the junction area of Minxian and Zhangxian counties, Gansu Province, China. This earthquake triggered many landslides of various types, dominated by small-scale soil falls, slides, and topples on loess scarps. There were also a few deep-seated landslides, large-scale soil avalanches, and fissure-developing slopes. In this paper, an inventory of landslides triggered by this event is prepared based on field investigations and visual interpretation of high-resolution satellite images. The spatial distribution of the landslides is then analyzed. The inventory indicates that at least 2330 landslides were triggered by the earthquake. A correlation statistics of the landslides with topographic, geologic, and earthquake factors is performed based on the GIS platform. The results show that the largest number of landslides and the highest landslide density are at 2400 m–2600 m of absolute elevation, and 200 m–300 m of relative elevation, respectively. The landslide density does not always increase with slope gradient as previously suggested. The slopes most prone to landslides are in S, SW, W, and NW directions. Concave slopes register higher landslide density and larger number of landslides than convex slopes. The largest number of landslides occurs on topographic position with middle slopes, whereas the highest landslide density corresponds to valleys and lower slopes. The underlying bedrocks consisting of conglomerate and sandstone of Lower Paleogene (E^b) register both the largest number and area of landslides and the highest landslide number and area density values. Correlations of landslide number and landslide density with perpendicular- and along-strike distance from the epicenter show an obvious spatial intensifying character of the co-seismic landslides. The spatial pattern of the co-seismic landslides is strongly controlled by a branch of the Lintan-Dangchang fault, which indicates the effect of seismogenic fault on co-seismic landslides. In addition, the area affected by landslides related to the earthquake is compared to the relationship of “area affected by landslides vs. earthquake magnitude” constructed based on earthquakes worldwide, and it is shown that the area affected by landslides triggered by the Minxian–Zhangxian earthquake is larger than that of almost all other events with similar magnitudes.     

Cost-sensitive rainfall thresholds for shallow landslides

The risk management of rainfall-induced landslides requires reliable rainfall thresholds to issue early warning alerts. The practical application of these thresholds often leads to misclassifications, either false negative or false positive, which induce costs for the society. Since missed-alarm (false negative) and false-alarm (false positive) cost may be significantly different, it is necessary to find an optimal threshold that accounts for and minimises such costs, tuning the false-alarm and missed-alarm rates. In this paper, we propose a new methodology to develop cost-sensitive rainfall thresholds, and we also analyse several factors that produce uncertainty, such as the accuracy of rainfall intensity values at landslide location, the time of occurrence, the minimum rainfall amount to define the non-triggering event, and the variability of cost scenarios. Starting from a detailed mapping of landslides that occurred during five large-scale rainfall events in the Italian Central Alps, we first developed rainfall threshold curves with a ROC-based approach by using both rain gauge and bias-adjusted weather radar data. Then, based on a reference cost scenario in which we quantified several cost items for both missed alarms and false alarms, we developed cost-sensitive rainfall threshold curves by using cost-curve approach (Drummond and Holte 2000). Finally, we studied the sensitivity of cost items. The study confirms how important is the information regarding rainfall intensity at the landslide site for the development of rainfall thresholds. Although the use of bias-corrected radar strongly improves these values, a large uncertainty related to the exact time of landslide occurrence still remains, negatively affecting the analysis. Accounting for the different missed-alarm and false-alarm misclassification costs is important because different combinations of these costs make an increase or decrease of the rainfall thresholds convenient. In our reference cost scenario, the most convenient threshold is lower than ROC-based thresholds because it seeks to minimise the number of missed alarms, whereas the missed-alarm costs are almost seven times greater than false-alarm costs. However, for different cost scenarios, threshold may vary significantly, as much as half an order of magnitude.

     

Three decades of landslide activity in western Nepal: new insights into trends and climate drivers

In recent decades, landslide disasters in the Himalayas, as in other mountain regions, are widely reported to have increased. While some studies have suggested a link to increasing heavy rainfall under a warmer climate, others pointed to anthropogenic influences on slope stability, and increasing exposure of people and assets located in harm’s way. A lack of sufficiently high-resolution regional landslide inventories, both spatially and temporally, has prevented any robust consensus so far. Focusing on Far-Western Nepal, we draw on remote sensing techniques to create a regional inventory of 26,350 single landslide events, of which 8778 date to the period 1992–2018. These events serve as a basis for the analyses of landslide frequency relationships and trends in relation to precipitation and temperature datasets. Results show a strong correlation between the annual number of shallow landslides and the accumulated monsoon precipitation (r = 0.74). Furthermore, warm and dry monsoons followed by especially rainy monsoons produce the highest incidence of shallow landslides (r = 0.77). However, we find strong spatial variability in the strength of these relationships, which is linked to recent demographic development in the region. This highlights the role of anthropogenic drivers, and in particular road cutting and land-use change, in amplifying the seasonal monsoon influence on slope stability. In parallel, the absence of any long-term trends in landslide activity, despite widely reported increase in landslide disasters, points strongly to increasing exposure of people and infrastructure as the main driver of landslide disasters in this region of Nepal. By contrast, no climate change signal is evident from the data.

     

An InSAR and depth-integrated coupled model for potential landslide hazard assessment

Assessing the hazard of potential landslides is crucial for developing mitigation strategies for landslide disasters. However, accurate assessment of landslide hazard is limited by the lack of landslide inventory maps and difficulty in determining landslide run-out distance. To address these issues, this study developed a novel method combining the InSAR technique with a depth-integrated model. Within this new framework, potential landslides are identified through InSAR and their potential impact areas are subsequently estimated using the depth-integrated model. To evaluate its capability, the proposed method was applied to a landslide event that occurred on November 3, 2018 in Baige village, Tibet, China. The simulated results show that the area with a probability of more than 50% to be affected by landslides matched the real trimlines of the landslide and that the accuracy of the proposed method reached 85.65%. Furthermore, the main deposit characteristics, such as the location of maximum deposit thickness and the main deposit area, could be captured by the proposed method. Potential landslides in the Baige region were also identified and evaluated. The results indicate that in the event of landslides, the collapsed mass has a high probability to block the Jinsha River. It is therefore necessary to implement field monitoring and prepare hazard mitigation strategies in advance. This study provides new insights for regional-scale landslide hazard management and further contributes to the implementation of landslide risk assessment and reduction activities.

     

Critical shallow and deep hydrologic conditions associated with widespread landslides during a series of storms between February and April 2018 in Pittsburgh and vicinity,western Pennsylvania,USA

The potential for widespread landslides is generally increased when extraordinary wet periods occur during times of elevated subsurface hydrologic conditions. A series of storms in early 2018 in Pittsburgh, Pennsylvania, overlapped with a period of increased shallow soil moisture and rising bedrock groundwater levels resulting from seasonally diminished evapotranspiration and induced widespread landslides in the region. Most of the landslides were shallow slope failures in colluvium, landslide deposits, and/or fill. However, deep-seated landslide activity also occurred and corresponded with record cumulative precipitation from late February to April and bedrock groundwater levels rising to an annual high. Landslides blocked or damaged roads, adversely affected multiple houses, disrupted electrical service, crushed vehicles, and resulted in considerable economic losses. The initial landslides occurred during or immediately after a rare period of three successive days of heavy rain that began on February 14. Subsequent landslides between late February and April were induced by multiday storms with smaller rainfall totals. As shallow soil moisture at a monitoring site rose above a volumetric water content of 32%, the mean rainfall intensities necessary to induce slope failure in colluvium and other surficial deposits decreased. Deep-seated landslide movement occurred in the region mostly when the groundwater level in a bedrock observation well was shallower than 1.7 m. The availability of hydrologic and landslide movement monitoring data during this extraordinary series of storms highlighted the evolution of the landslide hazard with changing moisture conditions and yielded insights into potential hydrologic criteria for anticipating future widespread landslides in the region.

     

A GIS method for landslide inventory and susceptibility mapping in the Río El Estado watershed,Pico de Orizaba volcano,México

In volcanic terrains, dormant stratovolcanoes are very common and can trigger landslides and debris flows continually along stream systems, thereby affecting human settlements and economic activities. It is important to assess their potential impact and damage through the use of landslide inventory maps and landslide models. In Mexico, numerous geographic information systems (GIS)-based applications have been used to represent and assess slope stability. However, there is no practical and standardized landslide mapping methodology under a GIS. This work provides an overview of the ongoing research project from the Institute of Geography at the National Autonomous University of Mexico that seeks to conduct a multi-temporal landslide inventory and produce a landslide susceptibility map by using GIS. The Río El Estado watershed on the southwestern flank of Pico de Orizaba volcano, the highest mountain in Mexico, is selected as a study area. The geologic and geomorphologic factors in combination with high seasonal precipitation, high degree of weathering, and steep slopes predispose the study area to landslides. The method encompasses two main levels of analysis to assess landslide susceptibility. First, the project aims to derive a landslide inventory map from a representative sample of landslides using aerial orthophotographs and field work. Next, the landslide susceptibility is modelled by using multiple logistic regression implemented in a GIS platform. The technique and its implementation of each level in a GISs-based technology is presented and discussed.     

Using multiresolution and multitemporal satellite data for post-disaster landslide inventory in the Republic of Serbia

This paper focuses on a specific event-based landslide inventory compiled after the May 2014 heavy rainfall episode in Serbia as a part of the post-disaster recovery actions. The inventory was completed for a total of 23 affected municipalities, and the municipality of Krupanj was selected as the location for a more detailed study. Three sources of data collection and analysis were used: a visual analysis of the post-event very high and high (VHR-HR) resolution images (Pléiades, WorldView-2 and SPOT 6), semi-automatic landslide recognition in pre- and post-event coarse resolution images (Landsat 8) and a landslide mapping field campaign. The results suggest that the visual and semi-automated analyses significantly contributed to the quality of the final inventory, including the associated planning strategies for conducting future field campaigns (as a final stage of the inventorying process), all the more so because the field-based and image-based inventories were focused on different types of landslides. In the most affected municipalities that had very high resolution satellite image coverage (19.52% of the whole study area), the density of the recognized landslides was approximately three times higher than that in those municipalities without satellite image coverage (where only field data were available). The total number of field-mapped landslides for the 23 municipalities was 1785, while image-based inventories, which were available only for the municipalities with satellite image coverage (77.43% of the study area), showed 1298 landslide records. The semi-automated landslide inventory in the test area (Krupanj municipality), which was based on coarse resolution multitemporal images (Landsat 8), counted 490 landslide instances and was in agreement with the visual analysis of the higher resolution images, with an overlap of approximately 40%. These results justify the use of preliminary inventorying via satellite image analysis and suggest a considerable potential use for preliminary visual and semi-automated landslide inventorying as an important supplement to field mapping.     

Landslides induced by a low magnitude seismic sequence at continental interiors: a case study of the Santa Rosa Canyon,northeastern Mexico

Landslides caused by a low magnitude earthquake swarm (2.8?≤?M?≤?3.6) in 2012 were documented at the Santa Rosa Canyon in northeastern Mexico. Disrupted landslides from falls and slides, in both rocks and soils, were identified based on fieldwork and high-resolution satellite imagery along stream banks from natural cliffs and along the road cut in the epicentral area. Most of the landslides occurred on slopes greater than 40°, where geological features played a key role in triggering slope instabilities. The maximum distance limit for disrupted slides from the epicentral area was 7 km. The area affected by landslides during the early stage of the seismic sequence (July through August 2012) was 90 km². Landslide identification was limited in some areas by the resolution of the satellite imagery and dense cloud coverage. Both the epicentral distance and the area affected by landslides are above the global bounds reported in literature. The final landslide inventory is the first documented case of earthquake-induced landslides in northeastern Mexico.     

Spatio-temporal evolution of mass wasting after the 2008 M<Subscript>w</Subscript> 7.9 Wenchuan earthquake revealed by a detailed multi-temporal inventory

Strong earthquakes in mountainous areas can trigger a large number of landslides that generate deposits of loose and unconsolidated debris across the landscape. These deposits can be easily remobilised by rainfalls, with their movement frequently evolving into catastrophic debris flows and avalanches. This has been the fate of many of the 200,000 co-seismic deposits generated by the 2008 M_w 7.9 Wenchuan earthquake in Sichuan, China. Here we present one of the first studies on the post-seismic patterns of landsliding through a detailed multi-temporal inventory that covers a large portion of the epicentral area (462.5 km²). We quantify changes of size-frequency distribution, active volumes and type of movement. We analyse the possible factors controlling landslide activity and we discuss the significance of mapping uncertainties. We observe that the total number of active landslides decreased with time significantly (from 9189 in 2008 to 221 in 2015), and that post-seismic remobilisations soon after the earthquake (2008–2011) occurred stochastically with respect to the size of the co-seismic deposits. Subsequently (2013–2015), landslide rates remained higher in larger deposits than in smaller ones, particularly in proximity to the drainage network, with channelised flows becoming comparatively more frequent than hillslope slides. However, most of the co-seismic debris remained along the hillslopes and are largely stabilised, urging to rethink the way we believe that seismic activity affects the erosion patterns in mountain ranges.     

川藏铁路通麦至鲁朗段地质构造对滑坡的控制作用分析

藏东南的喜马拉雅东构造结地区作为青藏高原隆升最快的地区之一,复杂的地质背景条件决定了该区工程地质问题的复杂性和特殊性,并孕育了多种地质灾害。文章通过遥感解译、无人机测绘以及野外现场调查,详细分析了喜马拉雅东构造结北西侧通麦至鲁朗段已有滑坡的发育特征,总结了地质构造对滑坡的控制作用,结果表明：（1）构造演化形成的高陡斜坡为滑坡形成提供地形条件,滑坡后缘的断裂破碎带,为雨水入渗提供通道,形成滑坡边界;（2）斜坡岩体中发育的贯通性构造节理为滑坡提供滑动条件和物质基础;（3）地震震动对岩体结构造成直接破坏,并诱发同震滑坡。多种构造作用的耦合造成了川藏铁路通麦至鲁朗段滑坡的高易发性,相关结果可为铁路修建过程的边坡灾害管控提供参考和支撑。     

Regional mapping and characterisation of old landslides in hilly regions using LiDAR-based imagery in Southern Flanders

Analysis of LiDAR-derived imagery led to the discovery of more than 330 pre-Holocene to recent landslides in Southern Flanders (4850 km²). The morphology of three landslides, including the 266.5 ha deep-seated gravitational slope deformation in Alden Biesen, was investigated in more detail. The analysis of the morphological and topographical characteristics (width–length relation, frequency–area distribution and topographical threshold) of the landslides revealed important differences compared to the characteristics reported in other landslide studies, and helped understanding possible landslide triggering mechanisms. Especially the possibility of a seismic origin of the landslides was investigated. Finally, a heuristic model for region-wide landslide susceptibility mapping was successfully tested. The susceptibility model and map allow prediction of future landslide locations and contribute to better understanding the role of individual causal factors on landslide location and spatial density. The results suggest that landslides on low-gradient, soil-mantled hills are a more important contributor to landscape evolution of hilly areas than was hitherto thought. The morphology of all hilly regions of Flanders is clearly marked by landslide processes and higher landslide densities often coincide with the presence of quaternary active faults. This study further shows that high-resolution topographical data such as LiDAR significantly contributes to a better detection of old, previously unknown landslides.     

时序InSAR技术三峡库区藕塘滑坡稳定性监测与状态更新

坡体表面形变是表征坡体稳定性的重要信息,因此,非常有必要对滑坡多发区域进行时序常规变形监测.近年来,星载合成孔径雷达数据由于其覆盖范围大、形变监测精度高的特点,被越来越多的用于山区滑坡识别与探测.首先介绍了联合分布式目标与点目标的时序InSAR方法,并将该方法应用于分析覆盖三峡藕塘滑坡的2007年至2011年的19景ALOS PALSAR数据和2015年至2018年的47景Sentinel-1数据,提取了数据覆盖时间段内的藕塘地区的变形速率.发现相比于2007年至2011年,2015年至2018年新增三处不稳定斜坡.进一步对滑坡的时序变形分析表明,降雨和水位变化是坡体稳定性最大的两个影响因素.实验证明时序InSAR方法可以作为常规形变手段来识别与监测三峡库区等地区潜在的滑坡,为防灾减灾提供支持与依据.      

The Hattian Bala rock avalanche and associated landslides triggered by the Kashmir Earthquake of 8 October 2005

The Kashmir Earthquake of the 8 October killed an estimated 87 350 people, 25 500 through co-seismic landslides. The largest landslide associated with the earthquake was the 68 × 10⁶ m³ Hattian Bala rock avalanche that destroyed a village and killed around 1000 people. The deposit blocks the valley to a depth of 130 m impounding a lake that reached the dam-crest in April 2007. An outburst flood now threatens a major settlement 3 km downstream. A series of space images reveals landslide clusters in the rock avalanche source area prior to the earthquake. The images also reveal a large slow-moving landslide with its toe in the lake, failure of this landslide may induce dam failure through overtopping and scour. Eighty five landslides in the Hattian Bala catchment predate the shaking of 8 October 2005, a further 73 are co-seismic with the main shock, and 21 postdate it in the period up to October 2006. Landslide magnitude–frequency distribution plots derived from satellite images allow an assessment of the contribution of seismically triggered events as compared to background rates of activity.     

Investigation of failure prediction of open-pit coal mine landslides containing complex geological structures using the inverse velocity method

The prediction of time to slope failure (TOF) is one of the most pivotal concerns for both geological risk researchers and practitioners. Conventional inverse velocity method (IVM), based on the analysis of displacement monitoring data, has become an effective method to solve this problem because it is easy to perform and the prediction results are generally acceptable. Practically, some limitations like random instrumental noise, environmental noise, and measurement error are ubiquitous factors hampered the reliability of the prediction. In this work, traditional IVM method and modified IVM with three different filters are respectively detected on velocity time series from an landslide event in an open-pit coal mine with the propose of improving, in retrospect, the accuracy of failure predictions. Simultaneously, the effects of noise on the appraisal of IVM graphics are also assessed and explanation. The results demonstrate that the sliding process of landslides can be divided into three signature stages based on the IVM. Noteworthily, the slope failure critical point occurs at the end of the progressive stage and generally coincides with a major acceleration event in which almost integrity of the slope is lost, transitioning to a linear trend ever since. Additionally, the short-term smoothing filter (SSF) and long-term smoothing filter (LSF) models can provide more accuracy and useful information about the probable failure time. Finally, with the intention of enhancing the feasible use of the method and supporting pre-determined response plans, two-level alert procedures combing SSF and LSF are proposed.

Graphical abstract

     

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\     

Deformation characteristics of a large landslide reactivated by human activity in Wanyuan city,Sichuan Province,China

With the rapid urbanization, an increasing number of landslides have been induced by human activities. In this study, a typical human-induced landslide known as the Maobazi landslide, which was triggered by foundation pit excavation in Sichuan Province, China, was analyzed. An emergency investigation was carried out to detect the basic deformation characteristics, followed by implementations of multiple monitoring schemes and emergency control measures to monitor and control reactivated deposits. The reactivated deposits depicted rapid deformations with a maximum deformation exceeding 140 mm from July to September before the emergency control measures were completed. The reactivated deposits gradually settled and were finally controlled in 2019. The results showed that the 2019 Maobazi landslide was a large; reactivated landslide with a scale reached to 520 Mm³, which could result in catastrophic consequences if it slipped down to nearby residential areas.

     

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.