APPLICATION OF LOGISTIC REGRESSION MODEL FOR HAZARD ASSESSMENT OF EARTHQUAKE-TRIGGERED LANDSLIDES: A CASE STUDY OF 2017 JIUZHAIGOU(CHINA)MS7.0 EVENT

The M_S7.0 Jiuzhaigou earthquake in Sichuan Province of 8 August 2017 triggered a large number of landslides. A comprehensive and objective panorama of these landslides is of great significance for understanding the mechanism, intensity, spatial pattern and law of these coseismic landslides, recovery and reconstruction of earthquake affected area, as well as prevention and mitigation of landslide hazard. The main aim of this paper is to present the use of remote sensing images, GIS technology and Logistic Regression(LR)model for earthquake triggered landslide hazard mapping related to the 2017 Jiuzhaigou earthquake. On the basis of a scene post-earthquake Geoeye-1 satellite image(0.5m resolution), we delineated 4834 co-seismic landslides with an area of 9.63km². The ten factors were selected as the influencing factors for earthquake triggered landslide hazard mapping of Jiuzhaigou earthquake, including elevation, slope angle, aspect, horizontal distance to fault, vertical distance to fault, distance to epicenter, distance to roads, distance to rivers, TPI index, and lithology. Both landsliding and non-landsliding samples were needed for LR model. Centroids of the 4834 initial landslide polygons were extracted for landslide samples and the 4832 non-landslide points were randomly selected from the landslide-free area. All samples(4834 landslide sites and 4832 non-landslide sites)were randomly divided into the training set(6767 samples)and validation set(2899 samples). The logistic regression model was used to carry out the landslide hazard assessment of the Jiuzhaigou earthquake and the results show that the landslide hazard assessment map based on LR model is very consistent with the actual landslide distribution. The areas of Wuhuahai-Xiamo, Huohuahai and Inter Continental Hotel of Jiuzhai-Ruyiba are high hazard areas. In order to quantitatively evaluate the prediction results, the trained model calculated with the training set was evaluated by training set and validation set as the input of the model to get the output results of the two sets. The ROC curve was used to evaluate the accuracy of the model. The ROC curve for LR model was drawn and the AUC values were calculated. The evaluation result shows good prediction accuracy. The AUC values for the training and validation data set are 0.91 and 0.89, respectively. On the whole, more than 78.5% of the landslides in the study area are concentrated in the high and extremely high hazard zones. Landslide point density and landslide area density increase very rapidly as the level of hazard increases. This paper provides a scientific reference for earthquake landslides, disaster prevention and mitigation in the earthquake area.     

基于Newmark模型的概率地震滑坡危险性分析方法研究

本文以天水地区为研究区,结合地震潜在震源区模型和Newmark位移预测方程,采用概率地震危险性分析方法,计算了该地区50年超越概率10%水平下的Newmark位移。同时,根据天水地区50年超越概率10%下的阿里亚斯烈度,并结合Newmark位移与阿里亚斯烈度的关系式,计算了天水地区在遭受50年超越概率10%下的阿里亚斯烈度影响时,潜在滑坡体产生的Newmark位移分布。通过比较上述两种方法得到的天水地区不同Newmark位移的分布特征,本文认为二者虽然存在较大差异,但其空间分布特征均能反映天水地区每个场点处的相对滑坡危险性。对滑坡危险性水平进行分区的结果显示,天水地区60%以上的区域具有高地震滑坡危险性,50%以上的区域具有甚高地震滑坡危险性。本文的研究结果可以作为天水地区地震危险性及风险评估的参考资料,也可以作为天水地区城市规划、土地使用规划、地震应急准备以及其它公共政策制定的参考资料。      

汶川地震滑坡危险性评价——以武都区和文县为例

利用GIS技术详细研究汶川地震在甘肃省陇南市武都区和文县触发的滑坡地质灾害的分布规律及其与地震烈度、地形坡度、断层、高程、地层岩性的相关关系,采用基于GIS的加权信息量模型的崩塌滑坡危险性评价方法,对研究区的地震滑坡危险性进行学科分析。结果表明：极高危险区在高程上主要分布在集水高程区,高度危险区主要沿白水江、白龙江等主干河流两侧极高易发区的边界向两侧扩展,轻度和极轻度危险区面积占比较小,主要分布在低烈度、活动断裂不发育、人类活动微弱的高海拔地区,另外国道G215沿极高危险性区域分布明显;利用危险性等级分区结果统计人口公里格网数据,得到武都区和文县潜在影响人口,发现研究区约78万人将受到地震滑坡灾害的潜在影响。     

GIS‐based regional landslide susceptibility mapping: a case study in southern California

Landslides threaten lives and property throughout the United States, causing in excess of $2 billion in damages and 25–50 deaths annually. In regions subjected to urban expansion caused by population growth and/or increased storm intensities caused by changing climate patterns, the economic and society costs of landslides will continue to rise. Using a geographic information system (GIS), this paper develops and implements a multivariate statistical approach for mapping landslide susceptibility. The presented susceptibility maps are intended to help in the design of hazard mitigation and land development policies at regional scales. The paper presents (a) a GIS‐based multivariate statistical approach for mapping landslide susceptibility, (b) several dimensionless landslide susceptibility indexes developed to quantify and weight the influence of individual categories for given potential risk factors on landslides and (c) a case study in southern California, which uses 11 111 seismic landslide scars collected from previous efforts and 5389 landslide scars newly digitized from local geologic maps. In the case study, seven potential risk factors were selected to map landslide susceptibility. Ground slope and event precipitation were the most important factors, followed by land cover, surface curvature, proximity to fault, elevation and proximity to coastline. The developed landslide susceptibility maps show that areas classified as having high or very high susceptibilities contained 71% of the digitized landslide scars and 90% of the seismic landslide scars while only occupying 26% of the total study area. These areas mostly have ground slopes higher than 46% and 2‐year, 6‐hour precipitation greater than 51 mm. Only 12% of digitized landslides and less than 1% of recorded seismic landslides were located in areas classified as low or very low susceptibility, while occupying 42% of the total study region. These areas mostly have slopes less than 27% and 2‐year, 6‐hour precipitation less than 41 mm. Copyright © 2007 John Wiley & Sons, Ltd.     

潜在地震滑坡危险区区划方法

不同地区地震活动的强度和频率是不同的.基于地震危险性分析的地震滑坡危险研究在综合了地震烈度、位置、复发时间等因素的基础上,考虑了地震动峰值加速度时空分布的特点,可以有效地应用于潜在地震滑坡危险区区划.以汶川地震灾区为研究对象,根据研究区的地质构造、地震活动特点等划分出灾区的潜在震源区,对该区进行地震危险性分析,并在此基础上采用综合指标法做出基于地震危险性分析的地震滑坡危险性区划.所得地震滑坡危险性区划按照滑坡危险程度分为高危险、较高危险、较低危险和低危险四级,表示未来一段时间内研究区在遭受一定超越概率水平的地震动作用下,不同地区地震滑坡发生的可能程度. 本文给出的地震滑坡危险性区划结果中,汶川地震滑坡崩塌较发育的汶川、北川、茂县等部分区域均处于高危险或较高危险区域;在对具有较高DEM精度的北川擂鼓镇地区所作的地震滑坡危险性区划中,汶川地震中实际发生的地震滑坡灾害与地震滑坡危险区划结果表现出较好的一致性.对区域范围而言,基于地震危险性分析的地震滑坡区划,可为初期阶段的土地规划使用及重大工程选址提供参考.     

数值模拟在地震小区划滑坡灾害评价中的应用

工程场地地震安全性评价、特别是在地震小区划工作中,对地震滑坡的评价通常采用定性分析方法,因此,对其影响范围未给出定量的评价结果。本文以吕梁新城地震小区划滑坡评价为例,通过对该区的地质条件、地貌特征的研究,针对具有典型特征的剖面,选取地震力、内聚力、摩擦角作为影响因子,采用离散单元法(DEM)对潜在滑坡体的稳定性进行了数值模拟计算,得到了可能失稳的滑坡体潜在滑动的影响范围。并在此基础上通过对已知滑坡与潜在滑坡剖面结构特征的类比,对整个研究区内滑坡体的影响范围进行了评价。研究结果可为吕梁新城的规划提供依据,也可为同类工程中地震滑坡灾害的定量评价提供参考。     

GIS支持下的地震诱发滑坡危险区预测研究

为了满足对地震诱发滑坡危险区预测的不断增长的迫切要求，灾害评价成为帮助决策过程重要的基础工具之一。即使地震滑坡危险性各组份的评价很困难，但地理信息可辅助提出这种灾害制图的有关方法。描述了用于地理信息系统识别和定量计算不同地震滑坡危险区的技术方法，确定了地震烈度、地形坡度、岩土体类型和现存滑坡密度共4个因子参与的地震诱发滑坡危险性分析。在ARC／INFO DRID支持下，进行叠合分析，由此编制了云南省地震诱发滑坡危险区预测图。由地貌学家提出的地震诱发滑坡预测为规划和工程师提供了对区域规划和建筑工程有价值的技术方法。     

An open-accessed inventory of landslides triggered by the MS 6.8 Luding earthquake,China on September 5, 2022

This study constructs a preliminary inventory of landslides triggered by the M_S 6.8 Luding earthquake based on field investigation and human-computer interaction visual interpretation on optical satellite images. The results show that this earthquake triggered at least 5 007 landslides, with a total landslide area of 17.36 ?km², of which the smallest landslide area is 65 ?m² and the largest landslide area reaches 120 747 ?m², with an average landslide area of about 3 500 ?m². The obtained landslides are concentrated in the IX intensity zone and the northeast side of the seismogenic fault, and the area density and point density of landslides are 13.8%, and 35.73 ?km^?2 peaks with 2 ?km as the search radius. It should be noted that the number of landslides obtained in this paper will be lower than the actual situation because some areas are covered by clouds and there are no available post-earthquake remote sensing images. Based on the available post-earthquake remote sensing images, the number of landslides triggered by this earthquake is roughly estimated to be up to 10 000. This study can be used to support further research on the distribution pattern and risk evaluation of the coseismic landslides in the region, and the prevention and control of landslide hazards in the seismic area.     

基于修正岩土体强度参数的简化纽马克位移法地震滑坡危险性快速评估技术

地震滑坡危险性评估可为震后应急响应等提供科学的决策依据。纽马克位移法可不依赖同震滑坡编目快速评估同震滑坡危险性。工程岩体物理力学参数是该方法的核心参数之一,但其赋值过于单一,难以反映复杂地质背景下岩体强度的空间差异性。针对上述问题,本文在分析地震滑坡影响因子的基础上,选择距断层距离、高程和距水系距离作为影响岩体强度的评价指标并建立岩体强度评价模型,获得区域岩体强度修正系数,进而修正传统方法的临界加速度。结合震后的即时地震动峰值加速度,采用简化纽马克位移法计算边坡累积位移,开展地震滑坡危险性快速评估,并以汶川M_W7.9地震的地震滑坡危险性评估为例验证本文方法。结果表明,相对于传统方法,本文方法划分的地震滑坡危险区与同震滑坡分布更加一致。      

区域地震滑坡灾害定量评估研究进展和展望

地震滑坡是最常见的地震次生地质灾害之一,不仅带来环境恶化,通常还造成严重的人员伤亡和财产损失,因此备受关注。为了解地震滑坡研究发展趋势,凝练地震滑坡定量评估科学问题,文章对区域地震滑坡定量评估起源、发展现状、存在的问题及未来发展进行了系统总结。研究结果表明：(1)区域地震滑坡灾害定量评估研究兴起于20世纪80年代,经过50多年学者的不懈努力,取得了丰硕的成果。区域地震滑坡灾害定量评估研究面临着新的社会需求。(2)地震滑坡是地震动力、地质特征和地貌条件等多因素耦合作用的结果,地震滑坡现象只有考虑成因机理与动力过程方可解释,地震滑坡成因机理研究主要集中于强震条件下斜坡的动力响应规律分析。(3)地震滑坡发育特征、成因机理以及数据库建设等基础研究推动了地震滑坡灾害风险定量评估研究。区域地震滑坡灾害风险定量评估包括地震滑坡危险性定量评估、地震滑坡易损性定量评估、地震滑坡危害性定量评估等内容。(4)在区域地震滑坡灾害定量评估方面,还需要进一步探索区域地震滑坡灾害形成的系统性和时空分布规律性、改进和完善区域地震滑坡灾害风险定量评估方法、开拓区域地震滑坡灾害防治战略规划。     

Spatial Distribution of Seismic Landslides in the Areas of 1927 Gulang M8.0 Earthquake

The 1927 Gulang M8.0 earthquake has triggered a huge number of landslides, resulting in massive loss of people''s life and property. However, integrated investigations and results regarding the landslides triggered by this earthquake are rare; such situation hinders the deep understanding of these landslides such as scale, extent, and distribution. With the support of Google Earth software, this study intends to finish the seismic landslides interpretation work in the areas of Gulang earthquake (VIII-XI degree) using the artificial visual interpretation method, and further analyze the spatial distribution and impact factors of these landslides. The results show that the earthquake has triggered at least 936 landslides in the VIII-XI degree zone, with a total landslide area of 58.6 km². The dense area of seismic landslides is located in the middle and southern parts of the X intensity circle. Statistical analysis shows that seismic landslides is mainly controlled by factors such as elevation, slope gradient, slope direction, strata, seismic intensity, faults and rivers. The elevation of 2 000-2 800 m is the high-incidence interval of the landslide. The landslide density is larger with a higher slope gradient. East and west directions are the dominant sliding directions. The areas with Cretaceous and Quaternary strata are the main areas of the Gulang seismic landslides. The X intensity zone triggered the most landslides. In addition, landslides often occur in regions near rivers and faults. This paper provides a scientific reference for exploring the development regularities of landslides triggered by the 1927 Gulang earthquake and effectively mitigating the landslide disasters of the earthquake.     

基于GIS的白龙江流域舟曲—武都段的滑坡危险性评价

本研究以围绕着白龙江流域的甘肃省南部的宕昌县、舟曲县和武都区部分地区为研究区,根据全国滑坡编目中得到的272个历史滑坡数据以及选取的高程、坡度、坡向、平面曲率、剖面曲率、归一化植被指数（NDVI）、降雨、岩性、距道路距离和距河流距离10种影响因子,利用三种具有代表性的定量方法：信息量模型、以及基于频率比模型的逻辑回归模型和人工神经网络模型对研究区内滑坡灾害危险性进行评价。三种评价结果均显示研究区内滑坡灾害的极高和高危险区主要沿白龙江河谷地区呈带状分布。从危险性分区图可看出,人工神经网络模型得到的分区图较为合理,既表现出沿河谷地区集中分布的趋势,也呈现出对滑坡历史数据较为独立的特征,这一研究结果与前人研究结果一致。根据受试者工作特征曲线（ROC曲线）对三种模型的精度进行检验,检验得到的AUC值分别为0.818、0.829和0.837,说明三种评价结果均具有较高的可靠性,基于频率比模型的人工神经网络模型相比其他两个模型具有更好的评价精度,能更好地进行滑坡危险性的预测和评价,其中高程、降雨、岩性以及距道路距离对评价结果影响更大,这四种影响因子重要性值占比为52.1%。为该地区的城市扩建与灾害预防预测提供了参考。     

Level-2 susceptibility zoning on seismic-induced landslides: An application to Sannio and Irpinia areas,Southern Italy

In this paper we recall a method for medium scale (level-2) zoning of seismic-induced landslide susceptibility and present its application to the Sannio–Irpinia area, Southern Italy. Previous small scale studies of the entire Campania Region identified this area as one of the most susceptible to earthquake-induced landslides in the region. The area’s intense seismic and landslide activity and the characteristics of the deposits involved in landslides make this analysis an interesting case study for land planning, management and protection of an area characterized by high seismic and hydrogeological hazard. The result of the zoning shows good agreement between the distribution of the historical earthquake-triggered landslides and the areas defined by the method as the most susceptible ones. They also highlight the method’s effectiveness in the presence of complex clayey deposits.     

Dynamic mechanisms of earthquake-triggered landslides

Earthquake-triggered landslides usually cause great disasters,and yet their dynamic mechanisms remain poorly understood.This paper will derive a general conceptual landslide model from the geometric and kinematic features of the most landslide masses triggered by the 2008 Wenchuan earthquake.Kinematic characteristics and dynamic processes are simulated here by means of finite element method(FEM)based on the dynamic process of the discontinuous deformable body.The calculated results presented the whole course of landslide motion,and displayed some typical kinematic characteristics such as initiation,sliding,ejection,collision,flying in the air,and climbing of landslides.The simulation result also shows that,under combined seismic inertial forces and gravity,landslides will start to slip once it overcomes the friction between the sliding mass and slip-bed,then it will move from slow to fast along the slippery bed until it ejects from the slip-bed.Moreover,the high frequencies and serious damages by landslides in the Wenchuan earthquake are caused by the strong ground motion on the mountain slopes in and around the epicenter that was dramatically amplified owing to both resonances produced by the seismic event and topographical amplification by seismic motion.In addition,the modeling results suggest that the direction,amplitude,frequency,and duration of strong ground motion have a great influence on the stability of landslide mass.Therefore,the study helps us better understand dynamic mechanism of landslides,seismic hazard assessment,and dynamic earthquake triggering.     

基于阿里亚斯烈度估值的概率性地震危险性分析——以四川丹棱县及其周缘为例

以编制《中国地震动参数区划图》时所构建的地震潜在震源区模型和地震活动性模型为基本输入,在四川省丹棱县及其周缘地区开展基于阿里亚斯烈度的概率地震危险性分析,计算50年超越概率10%的阿里亚斯烈度(Arias Intensity,Ia)。结果表明:丹棱县及其周缘绝大部分地区的Ia值都在0.11m/s以上,部分地区在0.32m/s甚至0.54m/s以上,具有较高的地震诱发滑坡风险,应当加强人员密集区的地震诱发滑坡危险性评估。根据不同Ia预测方程计算得到的Ia分布有较大差异,因此在计算Ia时应考虑多个Ia预测方程,对最终结果进行加权平均,以减小Ia结果的不确定性。同时还发现Ia值与1.0s的谱加速度具有很好的相关性,这也印证了Ia和1.0s谱加速度与砂土液化的相关性。     

基于降雨入渗的Newmark模型改进及地震滑坡危险性预测研究

滑坡是一种破坏性非常强的地质灾害,其中地震与降雨均为诱导滑坡发生的关键因素。从降雨期间发生地震的角度考虑,基于Green-Ampt降雨入渗模型对Newmark模型进行改进,推导两因素耦合作用下的边坡安全系数F_S。以云南省鲁甸县某一区域为例,分别开展无降雨、降雨无积水与降雨积水三种情况下的地震滑坡危险性预测及坡度与入渗深度因子对位移影响分析。通过比较上述三种情况,得到研究区域内的Newmark累积位移分布及危险性区划。结果表明：与未降雨情况相比,后两种情况下地震滑坡高危险程度区域面积占比计算区域随着降雨时间的增加从1%分别提高至9%、12%,滑坡低危险程度区域面积从51%分别降低至35%、33%;坡度值与入渗深度值越大,滑坡位移越大,危险性越高。Newmark改进模型充分考虑了降雨对地震滑坡产生的促进作用,能更好地反映出研究区每个场点相对的滑坡危险性,对滑坡危险性预测具有一定指导意义。     

Spatial distribution analysis of landslides triggered by the 2013-04-20 Lushan earthquake,China

The 2013-04-20 Lushan earthquake(seismic magnitude Ms 7.0 according to the State Seismological Bureau)induced a large number of landslides.In this study,spatial characteristics of landslides are developed by interpreting digital aerial photography data.Seven towns near the epicenter,with an area of about 11.11 km2,were severely affected by the earthquake,and 703 landslides were identified from April 24,2013 aerial photography data over an area of 1.185 km2.About 55.56% of the landslide area was less than 1000 m2,whereas about 3.23 % was more than 10,000 m2.Rock falls and shallow landslides were the most commonly observed types in the study area,and were primarily located in the center of Lushan County.Most landslide areas were widely distributed near river channels and along roads.Five main factors were chosen to study the distribution characteristics of landslides:elevation,slope gradients,fault,geologic unit and river system.The spatial distribution of coseismal landslides is studied statistically using both landslide point density(LPD),defined as the number of landslides(LS Number)per square kilometer,and landslide area density(LAD),interpreted as the percentage of landslides area affected by earthquake.The results show that both LPD and LAD have strong positive correlations with five main factors.Most landslides occurred in the gradient range of 40°-50° and an elevation range of 1.0-1.5 km above sea level.Statistical results also indicate that landslides were mainly formed in soft rocks such as mudstone and sandstone,and concentrated in IX intensity areas.     

海原地区黄土的微观结构及地脉动特征分析

1920年8.5级地震诱发了大量的黄土滑坡,对研究黄土地区的滑坡灾害、土层地脉动特征分析具有重要意义。基于高精度电子扫描显微镜（SEM）分析发现海原地震现场表层黄土为架空孔隙弱胶结微观结构,且该黄土是以粉粒为主的低黏性粉土,有震陷和地震滑坡的高风险。基于地脉动测试得到滑坡场地15个地脉动数据,采用傅里叶变换法对苏堡村滑坡土层的脉动特征进行分析,获得地脉动频谱特征曲线。研究表明场地卓越周期建议值为0.126 s,将其划分为坚硬场地,可为该滑坡场地类别划分作为参考,同时发现滑坡体与未滑体的地脉动特征有较大差异,可为海原地震滑坡的脉动特性分析提供依据。     

DATABASE OF LANDSLIDES TRIGGERED BY 2015 GORKHA(NEPAL) MW7.8 EARTHQUAKE

In this study, a detailed database of landslides triggered by the 25 April 2015 Gorkha (Nepal)M_W7.8 earthquake is constructed based on visual interpretation of pre- and post-earthquake high-resolution satellite images and field reconnaissance. Results show the earthquake triggered at least 47 200 landslides, which have a NWW direction spatial distribution, similar with the location and strike of the seismogenic fault. The landslides are of a total area about 110km² and an oval distribution area about 35 700km². On the basis of a scale relationship between landslide area (A)and volume (V), V=1.314 7×A^{1.208 5}, the total volume of the coseismic landslides is estimated to be about 9.64×10⁸m³. In the oval landslide distribution area, the landslide number density, area density, and volume density were calculated and the results are 1.32km^-2, 0.31%, and 0.027m, respectively. This study provides a detailed and objective inventory of landslides triggered by the Gorkha earthquake, which provides very important and essential basic data for study of mechanics of coseismic landslides, spatial pattern, distribution law, and hazard assessment. In addition, the landslide database related to an individual earthquake also provides an important earthquake case in a subduction zone for studying landslides related to multiple earthquakes from a global perspective.     

APPLICATION OF TWO SIMPLIFIED NEWMARK MODELS TO THE ASSESSMENT OF LANDSLIDES TRIGGERED BY THE 2008 WENCHUAN EARTHQUAKE

At present, with the wide application of the Newmark method, various Newmark empirical formulas with different ground motion parameters have been fitted by many researchers based on global strong-motion records. However, the existing study about the Wenchuan earthquake does not quantitatively evaluate the applicability of different Newmark models based on the actual landslides distribution. The aim of this paper is to present a comparison between observed landslides from the 2008 Wenchuan earthquake and predicted landslides using Newmark displacement method based on different ground motion parameters. The factor-of-safety map and critical acceleration(a_c)map in the study area are obtained by using the terrain data and geological data. The distribution of Arias intensity(I_a)and PGA in the study area is obtained by using the attenuation formulas of Arias intensity(I_a)and PGA, which is regressed by Wenchuan ground motion records. Based on the distribution of Arias intensity(I_a)and PGA parameters, we obtained the predicted locations of landslide using Newmark regression equations which are generated using global strong-motion records. The results shows that the assessment results can better reflect the macroscopic distribution characteristics of co-seismic landslides, most predicted landslide cells are distributed on the two sides of the Beichuan-Yingxiu Fault, especially the Pengguan complex rock mass in the hanging wall. The abilities to predict landslide occurrence of the two Newmark simplified models are different. On the whole, the evaluated result of simplified model based on parameter I_a is better than that based on PGA parameter. The GFC values obtained by the Newmark model of I_a and PGA parameters are 65.7% and 34.9%respectively. The evaluated result based on I_a can better reflect the macro distribution of coseismic landslides. The Ls_Pred value based on the Newmark model of parameter I_a is 26.5%, and the Ls_Pred value based on the Newmark model of PGA parameter is 10.3%. However the total area of predicted landslides accounts for 2.4% of the study area, which indicates that the predicted landslide cells are greater than the observed landslide cells. This reminds us that depending on the current input of shear strength and ground-motion parameters, we can only conduct landslide hazard assessment in macro areas, the ability to predict landslide can be improved using more accurate topographic data and input parameters.