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1.
WU Wei-ying  XU Chong 《地震地质》2018,40(5):1140-1148
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2.
The MS7.0 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.  相似文献   

3.
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 23rd 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 MW7.9 on 12th 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.  相似文献   

4.
The MS7.0 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.  相似文献   

5.
On August 3, 2014, an MW6.5 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 MW6.1 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.  相似文献   

6.
利用新技术、新方法,研究历史强震的发震构造及震害,是修订历史强震震源参数的重要内容.本文以1718年通渭M 7.5地震滑坡为研究对象,采用地质学“将今论古”原理,基于历史文献分析、遥感解译、野外验证等方法获得通渭地震滑坡数据库.研究发现,(1)总解译滑坡数量5019处,总面积635 km^2,滑坡密集沿通渭断裂分布,与X度等震线吻合,但范围均向西、向北各扩展约20 km;(2)与2008年汶川M8地震滑坡相比,面积<10^3 m^2的滑坡大量缺失,面积10^3~10^4 m^2的滑坡部分缺失,面积>10^4 m^2的滑坡数量相当;(3)尽管通渭地震滑坡数据库并不完整,但是能够反映极震区中大型滑坡的总体特征,可据此确定极震区范围;(4)通渭地震极震区至少有27处以“泄山”等记录地震滑坡的地名,这些受滑坡影响的居民点集中在通渭断裂两侧,占比超过50%,是致7万人死亡的重要致灾因素.研究认为,在黄土高原地区,确认密集的中大型滑坡体可能由单次历史强震触发,且排除其他远场强震影响之后,可以利用现今多时相的高分辨率卫星影像解译获得“相对完整”的历史地震滑坡数据库,为历史强震震源参数的修订提供基础资料.  相似文献   

7.
许冲  徐锡伟 《地球物理学报》2012,55(9):2994-3005
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Mw6.9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.  相似文献   

8.
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 MS8.0 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.  相似文献   

9.
The topography, occurrence mechanism and lithology are the important factors of landslide movement. The lithology, seismic intensity, geological structure and topography in the travel path of 215 incomplete obstruction landslides with volumes more than 104m3 induced by Wenchuan earthquake were studied. Based on the classification of the factors established, we studied the factors influencing the movement distance of incomplete obstruction landslides. The following results are drawn. In the influence factors of topography in the travel path, the distance is largest in the straight valley topography, followed by the concave, ladder, turning valley, slope toe-type and slope-type landslides, in turn. The topography not only has remarkable influence on the distance of large-scale landslides, but also on the medium and small-scale landslides as well, which is the most important factor influencing the distance. The formation mechanism controlled by lithology, seismic intensity and geological structure has little influence on the mobility of medium-and small-scale landslides. For the large-scale landslides with volume more than 106m3, the distance of landslide with medium hard rock is larger than landslides with hard and soft rock. In the seismic intensity Ⅸ to Ⅺ areas, the landslide distance decreases with intensity increasing, contrary to the distribution of landslide-point density and landslide-area density. The geological structure has influence on the slide aspect of landslides and occurrence mechanism, but the influence is not remarkable to the landslide movement distance.  相似文献   

10.
为了充分识别和有效减轻滑坡灾害风险,对滇西南南涧(约470 km2)和凤庆—昌宁(约2300 km2)两个研究区开展了基于GIS和专家知识的滑坡敏感性模糊逻辑评价研究。通过检查模型计算得到的历史滑坡点敏感性值与整个研究区域的滑坡敏感性平均值是否不同来评价本方法的性能,用Z值检查来测试差异的统计显著性。计算结果显示,南涧地区的Z值为4.1,相应的P值小于0.001,表明通过模型计算得到的滑坡敏感性值是该区域滑坡事件发生的良好指标;凤庆—昌宁地区的Z值为8.93,相应的P值小于0.001。在此基础上,采用自然断点法对滑坡敏感性值进行分类,根据分类结果将滑坡敏感性水平划分成5个等级:极低(0.0~0.001)、较低(0.001~0.051)、中等(0.051~0.394)、较高(0.394~0.557)和极高(0.557~1.0)。敏感性极低和较低的地区没有发现历史滑坡记录;敏感性极高地区的历史滑坡密度约是敏感性较高地区的4倍,约为敏感性中等地区的10倍。凤庆—昌宁地区的研究结果表明,从区域专家群中提取的滑坡敏感性与环境因子关系的知识可以外延到滇西南其它地区。  相似文献   

11.
A complete landslide inventory and attribute database is the importantly fundamental for the study of the earthquake-induced landslide. Substantial landslides were triggered by the MW7.9 Wenchuan earthquake on May 12th, 2008. Google Earth images of pre- and post-earthquakes show that 52 194 co-seismic landslides were recognized and mapped, with a total landslides area of 1 021 km2.Based on the statistics,we assigned all landslide parameters and established the co-seismic landslides database, which includes area, length, and width of landslides, elevation of the scarp top and foot edge, and the top and bottom elevations of each located slope. Finally, the spatial distribution and the above attribute parameters of landslides were analyzed. The results show that the spatial distribution of the co-seismic landslides is extremely uneven. The landslides that mainly occur in a rectangular area (a width of 30 km of the hanging wall of the Yingxiu-Beichuan fault and a length of 120 km between Yingxiu and Beichuan) are obviously controlled by surface rupture, terrain, and peak ground acceleration. Meanwhile, a large number of small landslides (individual landslide area less than 10 000 m2)contribute less to the total landslides area. The number of landslides larger than 10 000 m2 accounts for 38.7% of the total number of co-seismic landslides, while the area of those landslides account for 88% of the total landslides area. The 52 194 co-seismic landslides are caused by bedrock collapse that usually consists of three parts:source area, transport area, and accumulation area. However, based on the area-volume power-law relationship, the resulting regional landslide volume may be much larger than the true landslide volume if the landslide volume is calculated using the influenced area from each landslide.  相似文献   

12.
Empirical prediction of coseismic landslide dam formation   总被引：1，自引：0，他引：1       下载免费PDF全文
In this study we develop an empirical method to estimate the volume threshold for predicting coseismic landslide dam formation using landscape parameters obtained from digital elevation models (DEMs). We hypothesize that the potential runout and volume of landslides, together with river features, determine the likelihood of the formation of a landslide dam. To develop this method, a database was created by randomly selecting 140 damming and 200 non‐damming landslides from 501 landslide dams and > 60 000 landslides induced by the Mw 7.9 2008 Wenchuan earthquake in China. We used this database to parameterize empirical runout models by stepwise multivariate regression. We find that factors controlling landslide runout are landslide initiation volume, landslide type, internal relief (H) and the H/L ratio (between H and landslide horizontal distance to river, L). In order to obtain a first volume threshold for a landslide to reach a river, the runout regression equations were converted into inverse volume equations by taking the runout to be the distance to river. A second volume threshold above which a landslide is predicted to block a river was determined by the correlation between river width and landslide volume of the known damming landslides. The larger of these two thresholds was taken as the final damming threshold. This method was applied to several landslide types over a fine geographic grid of assumed initiation points in a selected catchment. The overall prediction accuracy was 97.4% and 86.0% for non‐damming and damming landslides, respectively. The model was further tested by predicting the damming landslides over the whole region, with promising results. We conclude that our method is robust and reliable for the Wenchuan event. In combination with pre‐event landslide susceptibility and frequency–size assessments, it can be used to predict likely damming locations of future coseismic landslides, thereby helping to plan emergency response. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   

13.
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 MS8.0 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.  相似文献   

14.
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.  相似文献   

15.
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.  相似文献   

16.
潜在地震滑坡危险区区划方法   总被引：5，自引：0，他引：5       下载免费PDF全文
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.  相似文献   

17.
This study constructs a preliminary inventory of landslides triggered by the MS 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.  相似文献   

18.
汶川地震滑坡危险性评价——以武都区和文县为例   总被引：1，自引：0，他引：1       下载免费PDF全文
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。  相似文献   

19.
许冲  徐锡伟 《地震地质》2014,36(1):90-104
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。  相似文献   

20.
We examined the characteristics of landslides triggered by the 2016 Kumamoto earthquake (Mw = 7.0: focal depth=10.0 km) in forests and grasslands within two affected watersheds (Tokosegawa: 6.9 km2 and Nigorigawa: 6.1 km2) in southwestern Japan. We identified 190 landslides using aerial photographs and analyzed their sizes by geographic information system (GIS). Field investigations were conducted to obtain landslide depth, volume and residual sediment for 38 selected landslides (21 in forests and 17 in grasslands). The minimum area of detected landslides in grasslands (400 m2) was smaller than in forests (1000 m2), probably because of reduced detectability of landslides under tree cover. The ratio of total area occupied by landslides for a given range of slope gradient in the watersheds increased from 3.2% on gentle grassland slopes (10–15°) to 15.5% on steep (>45°) slopes, whereas the maximum landslide-area ratio in forest sites (7.4%) occurred on relatively gentle slopes (25–30°). Estimated landslide volume ranged from 27 to 9622 m3, based on mean depth of each landslide measured around individual landslide scars. Moreover, the volumetric ratio of landslide deposit volume to total landslide volume exceeded 100% for 48% of the landslides within forests and 35% of the landslides within grasslands. Our findings show that land cover had extensive and recognizable effects on the characteristics of landslides and resulting in-channel sediment accumulations. Resetting sediment dynamics after earthquakes associated with different land cover distributions needs to be considered within watersheds. © 2019 John Wiley & Sons, Ltd.  相似文献   

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