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.     

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.     

基于高分卫星遥感影像的地震应急滑坡编目与分布特征探讨——以2017年8月8日九寨沟7.0级地震为例

地震应急是减轻地震灾害的重要途径之一。地震应急工作具有时间紧迫、事关重大的特点。2017年8月8日四川九寨沟M_S7.0级地震发生后,为快速、准确地提供地震引发的滑坡灾害分布,本研究基于震后第一天获取到的高分辨率遥感影像（高分二号卫星影像、北京二号卫星影像）,通过人工目视解译的方法初步建立了四川九寨沟地震滑坡编目。结果表明,该地震至少触发了622处同震滑坡,分布在沿使用影像边界框定的面积为3919km2的区域内。本研究还利用这个地震滑坡编目,统计了九寨沟地震滑坡数量和滑坡点密度（LND）与地形（坡度、坡向）、地震（地震烈度、震中距）等因素的关系。结果表明九寨沟地震滑坡多发生在坡度为20°—50°的区域内,滑坡的易发性随着坡度的增加而增加。受地震波传播方向的影响,E、SE向是地震滑坡较易发生的坡向。滑坡的易发程度和地震烈度呈正相关,即随着烈度的增大,滑坡易发性增大。滑坡易发性还随着震中距增加而降低,这是由于地震波能量随震中距的增加而衰减导致的。     

基于不同核函数的2010年玉树地震滑坡空间预测模型研究

基于统计学习理论与地理信息系统(GIS)技术的地震滑坡灾害空间预测是一个重要的研究方向,其可以对相似地震条件下地震滑坡的发生区域进行预测.2010年4月14日07时49分(北京时间),青海省玉树县发生了M_w6.9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,这些滑坡大概分布在一个面积为1455.3 km²的矩形区域内.本文以该矩形区域为研究区,以GIS与支持向量机(SVM)模型为基础,开展基于不同核函数的地震滑坡空间预测模型研究.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、坡度、坡向、斜坡曲率、坡位、水系、地层岩性、断裂、公路、归一化植被指数(NDVI)、同震地表破裂、地震动峰值加速度(PGA)共12个因子作为地震滑坡预测因子.以SVM模型为基础,基于线性核函数、多项式核函数、径向基核函数、S形核函数等4类核函数开展地震滑坡空间预测研究,分别建立了玉树地震滑坡危险性指数图、危险性分级图、预测结果图.4类核函数对应的模型正确率分别为79.87%,83.45%,84.16%,64.62%.基于不同的训练样本开展模型训练与讨论工作,表明径向基核函数是最适用于该地区的地震滑坡空间预测模型.本文为地震滑坡空间预测模型中核函数的科学选择提供了依据,也为地震区的滑坡防灾减灾工作提供了参考.     

A PANORAMA OF LANDSLIDES TRIGGERED BY THE 8 AUGUST 2017 JIUZHAIGOU,SICHUAN MS7.0 EARTHQUAKE

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. In this paper, we use the trinity method of space, sky and earth to create a panorama of the landslides triggered by this event. There are 4 roads in the distribution area of the coseismic landslides. The Jinglinghai-Xiamo and Jiudaoguai-Jiuzhaitiantang road sections register the most serious coseismic landslides. The landslides are mainly of moderate-and small-scales, and also with a few large landslides and avalanches. A detailed visual interpretation of the coseismic landslides is performed in two areas of Wuhuahai(11.84km²) and Zharusi-Shangsizhai village(47.07km²), respectively. The results show the overall intensity of landsliding(1088 landslides, a total area 1.514km²) in the Wuhuahai area is much higher than those in the Zharusi-Shangsizhai village area(528 landslides, a total area 0.415km²). On the basis of a scene of post-earthquake Geoeye -1 satellite images, we delineate more than 4 800 coseismic landslides with a total occupation area 9.6km². The spatial pattern of these landslides is well related with the locations of the inferred seismogenic fault and aftershocks. Widely distributed earthquake-affected weakened slopes, residual loose materials staying at high-position slopes and in valleys have greater possibilities to fail again and generate new landslides or debris flows under the conditions of strong aftershocks or heavy rainfalls in the future. Geological hazard from these events will become one of the most serious problems in the recovery and reconstruction of the earthquake-affected area which should receive much attention.     

Hazard Assessment of Co-seismic Landslides Based on Information Value Method: A Case in 2018 MW6.6 Hokkaido Earthquake, Japan

An M_W6.6 earthquake occurred in eastern Hokkaido, Japan on September 6^th, 2018. Based on the pre-earthquake image from Google Earth and the post-earthquake image from high resolution (3 m) planet satellite, we manually interpret 9 293 coseismic landslides and select 7 influencing factors of seismic landslide, such as elevation, slope, slope direction, road distance, flow distance, peak ground acceleration (PGA) and lithology. Then, 9 293 landslide points are randomly divided into training samples and validation samples with a proportion of 7:3. In detail, the training sample has 6 505 landslide points and the validation sample has 2 788 landslide points. The hazard risk assessment of seismic landslide is conducted by using the information value method and the study area is further divided into five risk grades, including very low risk area, low risk area, moderate risk area high risk area and very high risk area. The results show that there are 7 576 landslides in high risk area and very high risk area, accounting for 81.52% of the total landslide number, and the landslide area is 22.93 km², accounting for 74.35% of the total area. The hazard zoning is in high accordance with the actual situation. The evaluation results are tested by using the curve of cumulative percentage of hazardous area and cumulative percentage of landslides number. The results show that the success rate of the information value method is 78.50% and the prediction rate is 78.43%. The evaluation results are satisfactory, indicating that the hazard risk assessment results based on information value method may provide scientific reference for landslide hazard risk assessment as well as the disaster prevention and mitigation in the study area.     

STUDY ON THE DISTRIBUTION PATTERN OF EARTHQUAKE- TRIGGERED LANDSLIDES BASED ON SEISMIC LANDSLIDE SUSCEPTIBILITY ANALYSIS: A CASE STUDY OF LANDSLIDES TRIGGERED BY THE MS6.5 LUDIAN EARTHQUAKE IN 2014

On August 3, 2014, an M_W6.5 earthquake occurred in Ludian County, Yunnan Province, which triggered significant landslides and caused serious ground damages and casualties. Compared with the existing events of earthquake-triggered landslides, the spatial distribution of co-seismic landslides during the Ludian earthquake showed a special pattern. The relationship between the co-seismic landslides and the epicenter or the known faults is not obvious, and the maximum landslide density doesn't appear in the area near the epicenter. Peak ground acceleration (PGA), which usually is used to judge the limit boundary of co-seismic landslide distribution, cannot explain this distribution pattern. Instead of correlating geological and topographic factors with the co-seismic landslide distribution pattern, this study focuses on analyzing the influence of seismic landslide susceptibility on the co-seismic distribution. Seismic landslide susceptibility comes from a calculation of critical acceleration values using a simplified Newmark block model analysis and represents slope stability under seismic loading. Both DEM (SRTM 90m)and geological map (1 ︰ 200^￣￣000)are used as inputs to calculate critical acceleration values. Results show that the most susceptible slopes with the smallest critical accelerations are generally concentrated along the banks of rivers. The stable slopes, which have the larger critical accelerations and are comparably stable, are in the places adjacent to the epicenter. Comparison of the distribution of slope stability and the real landslides triggered by the 2014 M_W6.1 Ludian earthquake shows a good spatial correlation, meaning seismic landslide susceptibility controls the co-seismic landslide distributions to a certain degree. Moreover, our study provides a plausible explanation on the special distribution pattern of Ludian earthquake triggered landslides. Also the paper discusses the advantages of using the seismic landslide susceptibility as a basic map, which will offer an additional tool that can be used to assist in post-disaster response activities as well as seismic landslides hazards zonation.     

DISTRIBUTION CHARACTERISTICS OF THE AD 1556 HUAXIAN EARTHQUAKE TRIGGERED DISASTERS AND ITS IMPLICATIONS

A complete understanding to the disasters triggered by giant earthquakes is not only crucial to effectively evaluating the reliability of existing earthquake magnitude, but also supporting the seismic hazard assessment. The great historical earthquake with estimated magnitude of M8.5 in Huaxian County on the 23^rd January 1556, which caused a death toll of more than 830 000, is the most serious earthquake on the global record. But for a long time, the knowledge about the hazards of this earthquake has been limited to areas along the causative Huashan piedmont fault(HSPF) and within the Weihe Basin. In this paper, we made a study on earthquake triggered landslides of the 1556 event along but not limited to the HSPF. Using the high-resolution satellite imagery of Google Earth for earthquake-triggered landslide interpretation, we obtained two dense loess landslides areas generated by the 1556 earthquake, which are located at the east end and west end of the HSPF. The number of the interpreted landslides is 1 515 in the west area(WA), which is near to the macro-epicentre, and 2 049 in the east area(EA), respectively. Based on the empirical relationship between the landslide volume and area, we get the estimated landslide volume of 2.85~6.40km³ of WA and EA, which is equivalent or bigger than the value of ~2.8km³ caused by Wenchuan earthquake of M_W7.9 on 12^th May 2008. These earthquake triggered landslides are the main cause for the death of inhabitants living in houses or loess house caves located outside of the basin, such as Weinan, Lintong, Lantian(affected by WA) and Lingbao(affected by EA). Our results can help deeply understand the distribution characteristics of coseismic disaster of the 1556 Huaxian earthquake to the south of Weihe Basin, and also provide important reference for the modification of the isoseismals.     

analyses on the triggering facrors of large quantities of landslides in the upper reaches of the minjiang river,sichuan province

Over the past geological and historical period, tens of thousands of landslides occurred in the upper reaches of the Minjiang River, an area which is characterized by alpine valleys and has been densely populated over the past several hundreds of years. Discussing the triggering factor of these landslides is of great significance to geological hazard mitigation and prevention in this region. In this paper, we focus on four aspects of regional rainfall, shape features of landslide slopes, the corresponding relationship between landslide area and earthquake magnitude, and the recurring features of the reconstructed palaeoearthquake record at Diexi. Compared with those in Nepal, both mean seasonal rainfall accumulation and mean daily rainfall for the past 30 years are too low to reach the threshold values triggering landslides in the upper reaches of the Minjiang River. Secondly, landslides in the study area are usually absent of inner gorges(canyon topography)on the hillslope toes, which are confirmed in previous studies as typical features of landslides triggered by storms. Thirdly, wide distribution of the landslides in the study area supports our notion of earthquake-triggering because the landslides triggered by storms commonly distribute locally. Fourthly, periodicity analysis of the reconstructed palaeoearthquake record at Diexi provides a few cycles of twenty to thirty years, possibly corresponding to the earthquakes of magnitudes>5.0 or 5.5 which are believed to have caused soft-sediment deformation in the study area. In contrast, like the 2008 M_S8.0 Wenchuan earthquake, the average recurrence interval of the large earthquakes in the study area is 2.6ka. They caused tens of thousands of landslides and provided more coarse silt particles for the nearby lake sediments at least in 330 years for each time. This is consistent with exponential increase of earthquake magnitude from large to medium and of the landslide area with the increased earthquake magnitude. To sum up, we suggest that tens of thousands of landslides in the upper reaches of the Minjiang River were most likely triggered by earthquakes instead of storms. This preliminary viewpoint needs further examination in the future.     

An updated method for estimating landslide‐event magnitude

Summary statistics derived from the frequency–area distribution (FAD) of inventories of triggered landslides allows for direct comparison of landslides triggered by one event (e.g. earthquake, rainstorm) with another. Such comparisons are vital to understand links between the landslide‐event and the environmental characteristics of the area affected. This could lead to methods for rapid estimation of landslide‐event magnitude, which in turn could lead to estimates of the total triggered landslide area. Previous studies proposed that the FAD of landslides follows an inverse power‐law, which provides the basis to model the size distribution of landslides and to estimate landslide‐event magnitude (mLS), which quantifies the severity of the event. In this study, we use a much larger collection of earthquake‐induced landslide (EQIL) inventories (n=45) than previous studies to show that size distributions are much more variable than previously assumed. We present an updated model and propose a method for estimating mLS and its uncertainty that better fits the observations and is more reproducible, robust, and consistent than existing methods. We validate our model by computing mLS for all of the inventories in our dataset and comparing that with the total landslide areas of the inventories. We show that our method is able to estimate the total landslide area of the events in this larger inventory dataset more successfully than the existing methods. © 2018 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.     

联合DBSCAN聚类采样和SVM分类的滑坡易发性评价

针对基于机器学习的滑坡易发性评价中非滑坡样本选取不规范导致的分类精度较低问题,本文提出联合基于密度的噪声应用空间聚类（Density-Based Spatial Clustering of Applications with Noise,DBSCAN）采样策略和支持向量机（Support Vector Machine,SVM）分类方法的DBSCAN-SVM滑坡易发性评价模型。首先,基于DBSCAN聚类和空间分析选取非滑坡样本;然后,将样本数据代入SVM分类模型进行训练与验证,预测并提取SVM分类中属于滑坡的概率,获得滑坡易发性;最后,以四川省绵阳市为试验区,预测滑坡易发性概率,基于滑坡易发性精度与分级结果等要素,与传统非滑坡样本采集策略的SVM滑坡易发性评价模型进行对比,并结合实际情况对DBSCAN-SVM模型评价结果进行分析。研究结果表明,相比传统SVM滑坡易发性评价模型,本文提出的DBSCAN-SVM滑坡易发性评价模型在高易发区和极高易发区中包含的滑坡样本数量较多,准确率、召回率、AUC、F1分数均得到提高,精度较高。     

EVOLUTION CHARACTERISTICS OF LANDSLIDES TRIGGERED BY 2008 MS8.0 WENCHUAN EARTHQUAKE IN YINGXIU AREA

Strong earthquakes can not only trigger a large number of co-seismic landslides in mountainous areas, but also have an important impact on the development level of geological hazards in the disaster area. Usually, geological hazards caused by strong earthquakes will significantly increase and continue for a considerable period of time before they recover to the pre-earthquake level. Therefore, studying the evolution characteristics of landslides triggered by earthquake is particularly important for the prevention of geological disaster. In this paper, a 66km² region in Yingxiu near the epicenter of the 2008 M_S8.0 Wenchuan earthquake, which was strongly disturbed by the earthquake, was investigated. Firstly, one high-resolution satellite image before the earthquake(April, 2005) and five high-resolution satellite images after the earthquake(June, 2008; April, 2011; April, 2013; May, 2015; May, 2017)were used to interpret and catalog multi-temporal landslide inventories. Secondly, seven primary factors were analyzed in the GIS platform, including elevation, slope, aspect, curvature, stratum, lithology, and the distance from the nearest water system and the distance from seismogenic faults. Finally, the evolution of the landslide triggered by earthquake in this region was analyzed by comparing the landslide activity intensity in different periods, using the methods of correlation analysis, regression analysis, and single-factor statistical analysis. It was found that the total area of landslides in the study region decreased sharply from 2008 to 2017, with the area of the co-seismic landslide reducing from 21.41km² to 1.33km². This indicates that the magnitude of the landslides has recovered or is close to the pre-earthquake level. Moreover, correlation analysis shows that the elevation has a strong positive correlation with the distance from the nearest water system, and a weak positive correlation with the area. Meanwhile, there is a weak negative correlation between the distance from the nearest water system and the distance from seismogenic faults. Overall, the degree of landslide activity in the study region decreased over time, as well as the number of reactivated landslides and new landslides. The region where the area of earthquake triggered landslides decreased mainly concentrated at an elevation of 1 000m to 2 100m, a slope of 30° to 55°, an aspect of 40° to 180°, and a curvature of -2 to 2. In addition, the lithology of the Pengguan complex in the Yingxiu study region is more conducive to the occurrence of landslides, while the sedimentary rock is more conducive to the landslide recovery. When the distance from the nearest water system is more than 1 600m, the effect of the water system on the landslides gradually decreases. Also, the landslides triggered by Wenchuan earthquake in this area have the characteristics of the hanging wall effect, which means, the number of landslides in the northwestern region is much higher than that in the southeast side.     

地震黄土滑坡滑距预测的BP神经网络模型

地震滑坡的滑距与重力滑坡的滑距有着显著的不同,科学预测地震发生时黄土地区滑坡的滑动距离是合理评估黄土地区滑坡风险和减轻滑坡灾害的有效方式之一。基于海原特大地震诱发黄土滑坡的400组野外调查数据,通过引入BP神经网络算法,论证了BP神经网络模型用于预测黄土地震滑坡滑距的适宜性和可行性;建立了地震诱发黄土滑坡滑距的BP神经网络预测模型,并通过67组数据进行了验证。BP神经网络算法和传统多元线性回归、多元非线性回归结果的对比显示,BP神经网络的预测更接近真实情况,具有较为理想的预测效果,可以用于黄土地震滑坡滑距的预测,并为圈定较为可靠的致灾范围提供依据。     

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。     

21世纪初几次大地震事件触发滑坡基础数据建设

自2008年5月12日汶川MW7.9地震发生以来,针对地震滑坡与光学遥感影像的特点,制定了地震滑坡编录新原则、遥感影像选取新原则及地震滑坡属性库建立原则。文中介绍了21世纪初4次大地震事件触发滑坡基础数据建设成果:包括2008年5月12日汶川MW7.9地震,此次地震触发了至少197 481处滑坡;2010年4月14日玉树MW6.9地震至少触发2 036处滑坡;2010年1月12日海地MW7.0地震至少触发30 828处滑坡;2007年4月21日智利艾森峡湾MW6.2地震至少触发1 000处滑坡。分析了地震触发滑坡基础数据建设成果与以往研究的不同。最后从地震滑坡基础数据建设成果对地震滑坡分布规律与危险性评价的影响,对震区滑坡与泥石流防灾减灾的意义,对地震震级、活动断层运动习性、地震烈度等的反馈,对震区河流与地貌演化研究的基础意义,对全球地震震级与触发滑坡关系研究的意义等几个方面,分析了地震滑坡基础数据建设的实际应用价值与科学研究意义。     

汶川地震高速远程滑坡速度研究

汶川地震诱发了大量的高速远程滑坡。在超强的地震动作用下,坡体结构被撕裂并抛射后,受到坡体前缘地形及自身势能的影响,很容易转化为碎屑流作远程运动,这种高位滑坡以其很快的运动速度和超常的运动距离造成了巨大的灾害与损失。本文在对汶川地震大型典型高速远程滑坡大量现场调查的基础上,分析了坡体临空飞行运动初始速度、滑程运动最大速度以及碎屑流运动速度,并且以东河口滑坡为例,对比了不同计算方法下的运动速度和运动性,得到东河口滑坡的运动特征值μ=0.2292,最大运动速度Vm ax=63.40 m/s,平均运动速度超过25 m/s,属于超高速滑坡运动以及强碎屑流性质。     

基于证据权方法的玉树地震滑坡危险性评价

玉树地震诱发了2 036处滑坡。应用地理信息系统与遥感技术,选取与地表破裂距离、峰值加速度(PGA)、高程、坡度、坡向、曲率、坡位、与水系距离、岩性、与断裂距离、与公路距离、归一化植被指数(NDVI)等12个因素作为玉树地震滑坡危险性评价因子,采用加法与减法2种证据权方法,开展玉树地震滑坡危险性评价研究工作。结果表明:基于加法证据权方法得到评价结果的正确率为80.32%,基于减法证据权方法得到结果的正确率为80.19%。将滑坡危险性评价结果图分为极高危险区、高危险区、中危险区、低危险区与极低危险区5类。这一成果可划分出滑坡危险区,为灾后滑坡防治、基础设施重建与自然环境保护提供参考。     

黄土高原地震作用下黄土滑坡滑距预测方法

为评估黄土高原地区地震滑坡致灾区域,提出一种基于模糊信息优化处理的地震滑坡滑距预测方法。在野外调查、室内试验和分析的基础上,对黄土高原的地震滑坡类型、性质和影响因素进行分析。以摩根斯坦-普莱斯法计算黄土边坡的稳定性,建立边坡最小安全系数与影响因素的关系,其影响因素主要包括地震烈度、比高、坡角、容重、内黏聚力、内摩擦角等,并在此基础上得到纯黄土地震滑坡滑距的影响关系。将黄土高原地区数次大震中采集到的93个样本数据进行归纳分析,建立模糊信息优化处理模型。所得的计算结果通过误差校验和与其他滑坡滑距预测方法进行对比,来证明本模型有较高的准确性。最后对天水市22个潜在滑坡的边坡进行滑距预测。     

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.