基于频率比与集成学习的滑坡易发性评价——以金沙江上游巴塘—德格河段为例

金沙江上游巴塘—德格河段地处青藏高原东部,该区地质、地形、地貌极其复杂,滑坡灾害最为发育,开展区域滑坡易发性评价对防灾减灾工作有着重要的意义。本文以金沙江上游巴塘—德格河段为研究区,在滑坡编录与野外实际调查的基础上,通过对滑坡分布规律和影响因素分析,选取高程、坡度、坡向、曲率、地形起伏度、地表切割度、地表粗糙度、地层岩性、断层、水系和道路等11个影响因子,构建了滑坡易发性评价指标体系。利用皮尔森系数去除高相关性影响因子,运用频率比方法定量分析各个因子与滑坡发育的关系。通过频率比模型选取非滑坡样本,采用集成学习算法模型进行滑坡易发性评价,根据易发性指数将研究区划分为极高易发区、高易发区、中易发区、低易发区及极低易发区5个等级。由滑坡易发性分区图和ROC曲线表明,高和极高易发区主要沿金沙江沿岸和沟谷分布,随机森林模型的成功率曲线下面积AUC=0.84,历史滑坡灾害位于高-极高易发区的灾害数占总滑坡数的84.8%,梯度提升树模型的成功率曲线下面积AUC=0.79,历史滑坡灾害位于高-极高易发区灾害数占总滑坡数的79.3%。由AUC值和历史灾害的分布可知,随机森林模型比梯度提升树模型在本研究区滑坡易发性评价中有着更好的评价精度和更高的预测能力。     

基于证据权法的巴东县城滑坡灾害易发性评价

巴东县城由于其特殊的地理位置和特有的地质条件,使之成为滑坡灾害多发地带,严重威胁着巴东县城的发展,因此,有必要对巴东县城进行滑坡易发性评价研究。首先,基于GIS平台分别提取影响滑坡发生发育的各指标因子(地层岩性、地形地貌、地质构造、水文地质条件等),并划分证据层;其次,采用证据权法分别计算各证据层的权重及后验概率;然后将单元各证据层后验概率进行叠加,生成滑坡易发性分区图;最后,使用自然断点法将研究区按滑坡易发程度分为极高易发区、高易发区、中易发区、低易发区与极低易发区5类,极高易发区与高易发区面积之和约占研究区总面积的33%,其中86%的已有滑坡发生在极高易发区和高易发区,利用成功率曲线检验表明区划效果较好。     

GIS支持下CF与Logistic回归模型耦合的九寨沟景区滑坡易发性评价

2017年8月8日九寨沟M_S7.0地震诱发了数以千计的崩滑体,产生的大量松散固体碎屑在降雨作用下极易启动转化为新的滑坡或泥石流形成次生灾害,因此对九寨沟景区进行滑坡易发性评价尤为必要。基于震前、震后高精度遥感影像对比分析结合现场调查,共获取1047处滑坡,总面积为3.88 km2。在分析滑坡发育分布与影响因素关系的基础上,本文选取了构造因子、地形因子、地质因子及其他因子等9个指标,采用确定性系数(CF)模型、逻辑回归(Logistic)模型以及两种模型耦合分析进行滑坡易发性评价。研究结果表明,坡度、坡向、高程和地层岩性是影响滑坡分布的主要因子;研究区被划分为低易发区(60.72%)、中度易发区(24.18%)、高易发区(9.89%)和极高易发区(5.21%),高-极高易发区基本沿沟谷分布,面积为99 km2,其中熊猫海、老虎海周边均为滑坡极高易发区;采用耦合模型比单一模型评价结果更加合理,其结果可作为景区滑坡防治和分段分时开放的参考依据。     

汶川震区北川县城泥石流源地特征的遥感动态分析

汶川地震导致山地斜坡积累了大量碎屑物质,在降雨作用下极易成为泥石流源地。震后的2008年9月24日一场暴雨导致北川县境内72条沟同时暴发泥石流。本文选择了汶川地震高烈度区的北川县城8条泥石流沟流域为研究区,基于遥感手段开展了震后和相继暴雨后的泥石流源地变化特征。强震后泥石流流域的重要变化是在沟谷内诱发了大量滑坡。通过开展遥感解译和野外调查,重点分析了研究区泥石流源地的滑坡活动。将512汶川地震后的2008年5月18日获取的航空图像与924暴雨后获取的2008年10月14日SPOT图像相比较,发现泥石流源地的地震滑坡面积由1537104m2增加到暴雨后的1912104m2,即汶川高烈度区一场暴雨过程新增滑坡面积达244%。根据SPOT图像解译,暴雨后泥石流沟床中的松散堆积物增大到97104m2。上述研究结果表明汶川震区在强降雨条件下发生泥石流的敏感性特别高。     

河北省顺平县地质灾害发育特征及易发性评价

河北省顺平县位于太行山东麓,主要发育有崩塌、滑坡、泥石流、地裂缝等四种类型地质灾害。基于该县地质灾害发育特征,采用GIS技术和信息量数学评价模型,选取坡度、起伏度、坡向、工程地质岩组、归一化植被指数（NDVI）、与河流的距离6个评价因子,对顺平县地质灾害进行易发性评价。评价结果显示:高易发区面积约为125 km2,占全县总面积的17.5%,分散分布于西北部的中低山和丘陵地区,密集发育崩塌灾害,少量发育滑坡、泥石流灾害;中易发区面积约为200 km2,占全县总面积的28.0%,成片分布于西北部的中低山和丘陵地区,少量发育崩塌、滑坡、泥石流灾害;低易发区面积约为389 km2,占全县总面积的54.5%,主要分布于东南部的平原地区及西北部丘陵地区内的宽阔沟谷,沿古河道发育地裂缝灾害,个别地区发育崩塌、滑坡灾害。      

基于GIS的哀牢山戛洒镇小流域滑坡易发性评价

根据研究区的基本情况,选择坡度、坡向、地层岩性、距断层距离、降雨、土地利用等6个评价因子,采用滑坡灾害易发性评价的GIS与AHP耦合模型进行戛洒镇滑坡灾害易发性评价,并将滑坡灾害分为极高、高、中、低和极低易发区5个区域进行了滑坡灾害易发性评价结果分析,以期为后期的小流域滑坡风险评估研究服务。     

逻辑回归和信息量模型在山区滑坡易发性评价中适宜性的分析

以万山区为例,在区域滑坡孕灾条件的基础上,筛选工程地质岩组、斜坡结构、平均坡度、地貌、距构造距离及距河流距离共6个易发条件因子,选取逻辑回归模型和信息量模型对山区滑坡进行易发性评价。结果显示逻辑回归模型中中高易发区面积占比分别为1578%和1970%,82%的地质灾害点落在该区域内;信息量模型中中高易发区面积占比为1241%、2519%,包含了区域88%的滑坡灾害点。最后通过实际发生的灾害点在各易发区的分布情况进行检验,逻辑回归模型中灾害点落在高易发区的比例远小于信息量模型,且高易发等级中灾害点实际发生的比值较小,说明针对山区区域滑坡地质灾害易发性评价结果预测上,信息量模型的评价结果更为客观准确。     

金沙江溪洛渡库区水库诱发滑坡时空分布规律及易发性研究

水库诱发滑坡作为重大工程对地质环境影响的一种重要形式,是国内外工程地质学科研究的前沿和热点。金沙江流域地处青藏高原东缘高山峡谷区,地质环境脆弱,水能资源丰富,是世界上水电站建设最密集的地区之一,规划了25级梯级电站,但是水库蓄水对岸坡改造的时空效应尚不清楚。本文以溪洛渡水电站为例,对金沙江流域水库诱发滑坡的分布规律进行研究,利用2013~2020年多期遥感影像解译溪洛渡库区范围内的水库诱发滑坡,共解译滑坡433处。在此基础上,对水库诱发滑坡数量和面积随蓄水时间的变化趋势进行了分析,随后利用频率比法对水库诱发滑坡的分布与高程、坡度、坡向、工程地质岩组、断裂、距死水位距离6个因素的关系进行了统计分析,同时进行了各个单因子的滑坡易发性评价,利用曲线下面积AUC法验证了评价结果的可靠性,并基于评价结果选取了高程、距断裂距离、坡度、距死水位距离4个因素进行了水库诱发滑坡易发性评价。研究认为:(1)水库诱发滑坡主要发生在蓄水初期3~4年内,之后滑坡数量和面积逐渐减少,岸坡表生演化逐渐趋于稳定。(2)库区内水库诱发滑坡主要分布在高程1 km以内,2 km以上无诱发滑坡分布,优势坡度为30°~60°,发育滑坡的斜坡坡向以SE、W和NW向为主;在距断裂400~3200 m范围内更有利于滑坡发育;距死水位100~200 m范围内灾害发育数量最多。(3)易发性评价验证AUC高达0.912,评价结果可信度较好。(4)水库诱发滑坡的主控因素为距死水位距离和高程,极高易发区与高易发区主要分布在距死水位400 m以内、高程1 km以下的范围内。本文首次利用多期遥感影像建立了溪洛渡水电站水库诱发滑坡数据库,研究结果能够为已建水电站正常运营、未建及在建水电站的规划建设和防灾减灾提供借鉴。     

基于信息量法的湖北省秭归县滑坡易发性评价

本文以湖北省秭归县为研究区,选取高程、水系距离、道路距离、岩土体类型、坡向、坡度、土地覆盖类型、年降雨量等8个评价因子开展滑坡易发性评价工作,依据ArcGIS软件数据分析工具完成各评价因子相关性分析。对评价因子相关性值|r|>0.1的高程、坡向因子剔除,计算各因子信息量值。利用信息量模型进行滑坡易发性评价,将研究区划分为四个区域：(1)极高易发区,面积140.0864 km²,占研究区总面积6.18%,主要分布在长江及支流沿岸;(2)高易发区,面积1002.445 km²,占研究区总面积44.23%,主要呈带状分布在极高易发区两侧,部分位于两河口镇、磨坪乡周边区域;(3)中易发区,面积833.8711 km²,占研究区总面积36.79%,呈带状分布在极高易发区两侧,零散分布;(4)低易发区,面积290.2564 km²,占研究区总面积12.80%,多分布在高山人稀区域。本文研究结果能够较好地反映研究区滑坡灾害分布规律,可为秭归县防灾减灾工作提供依据。     

嘉陵江流域北碚段基于GIS平台的地质灾害易发性评价

基于GIS平台．选取坡度、岩性、河流距离、曲率共4个地质灾害致灾因子,采用多因子综合分析方法,对嘉陵江流域北碚段进行地质灾害易发性分区。按照地质灾害的易发性分级,将2343．6km^2范围的研究区划为4类,其中低易发区面积为141．82km^2,中易发区面积为1162．47km^2,高易发区面积为914．95km^2,极高易发区面积为124．38km^2。最后应用野外地质灾害调查结果对分区结果进行验证,位于极高易发区与高易发区的灾害点分别占全部灾点的59．7％与28．2％,共为87．9％,且几处大型的滑坡、堆积体、危险库岸都位于极高易发区．表明研究成果比较客观。     

2013年7月22日岷县漳县MS6.6级地震滑坡编录与空间分布规律分析

2013年7月22日,中国甘肃省岷县漳县交界地区发生MS6.6级地震。地震触发了大量的滑坡,主要类型为小型的黄土崖崩、滑、倾,还有一些深层连贯型滑坡、大型土质流滑、侧向滑移等地震滑坡类型。本文主要基于地震滑坡野外考察与高分辨卫星影像人工目视解译方法,开展本次地震触发滑坡的编录图制作工作,并基于编录成果开展地震滑坡空间分布规律分析工作。滑坡编录结果表明此次地震至少触发了2330处滑坡。基于GIS平台下开展了地震滑坡与地形控制因子、地质控制因子与地震控制因子的关系统计。结果表明岷县漳县地震滑坡受地形因子的控制作用较小; 受地层岩性的控制作用较大。其中1401处滑坡(占总滑坡的60.13%)分布在下伏基岩为古近系下统地层(Eb)砾岩与砂岩的区域内,其中滑坡密度是所有地层分类中最高的,达到22.78个km-2。地震滑坡与PGA的统计关系并不明显。地震滑坡主要集中在一个与发震断层走向一致的长条形区域内,长约14km,宽约5km。该区域内滑坡数量为1864个,占所有滑坡数量的80%,表明了岷县漳县地震滑坡空间分布的密集特征。文章获得的基于地震事件的区域滑坡编录成果是后续地震滑坡相关科学研究的重要基础与核心数据; 空间分布规律分析成果可为地震区滑坡与泥石流防灾减灾提供科学参考。     

Characteristics of earthquake-induced landslides in a heavy snowfall region—landslides triggered by the northern Nagano prefecture earthquake, March 12, 2011, Japan

The northern Nagano Prefecture earthquake, M_JMA?6.7 (Mw?6.2), which is inferred to have been triggered by the huge (Mw?9.0) March 11, 2011 Tohoku earthquake, occurred on March 12, 2011, in northern Nagano Prefecture, an area in Japan famous for heavy snowfall. A large number of landslides were triggered by the 12 March earthquake, and it caused building damage in the area of the epicenter. To clarify characteristics of the distribution and dynamic behavior of these landslides, we analyzed aerial photographs and conducted field surveys in and around the epicentral area. Large-scale landslides with long distance run-outs are a remarkable characteristic of the landslides induced by this earthquake. The long travel distance is considered to be related to the thick snowpack at the time the earthquake occurred. Moderate scale deep-seated landslides and shallow landslides were also observed in the study area. Based on an analysis of landslides with the active fault on which the earthquake is believed to have occurred, most of these landslides were distributed on the hanging wall of the active fault, within a distance of 12?km from the fault.     

Geological and geomorphological characteristics of landslides triggered by the 2004 Mid Niigta prefecture earthquake in Japan

The 2004 Mid Niigta prefecture earthquake (M_JMA 6.8) triggered more than one thousand landslides in the Miocene to Quaternary sedimentary rocks in Japan. The most common landslides were shallow disrupted landslides on steep slopes, which has been common in many previous disastrous earthquakes in the world. The Mid Niigta prefecture earthquake also triggered more than one hundred deep landslides, providing valuable information on the conditions for their occurrence. A field investigation and the interpretation of aerial photographs taken before and after the earthquake suggest that reactivation of existing landslides and undercutting of slopes are the most important factors for deep landslides to be triggered by earthquakes. In addition, planar sliding surfaces seem to be essential for the generation of catastrophic landslides triggered by this earthquake. Planar bedding–parallel sliding surfaces were formed at the boundary between the overlying permeable sandstone and underlying siltstone or along the bedding planes of alternating beds of sandstone and siltstone. Sliding surfaces along the slope-parallel oxidation front were formed in the area of black mudstone. New landslides (rockslide-avalanches) occurred with the sliding surfaces in a several-cm thick tuff interbedded in siltstone. One rockslide-avalanche occurred on a slope where buckling deformation preceded the earthquake. Gentle valley bottom sediments were mobilized in many locations, probably because they were saturated and partial liquefaction had occurred due to the earthquake shaking.     

Revisions of the M 8.0 Wenchuan earthquake seismic intensity map based on co-seismic landslide abundance

Natural Hazards - Hundreds of thousands of landslides were triggered by the May 12, 2008, Mw 7.9 Wenchuan earthquake in China. A detailed inventory of landslides triggered by the earthquake was...     

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.     

利用Newmark方法进行地震滑坡制图——以映秀研究区为例

2008年汶川5.12地震触发了大量滑坡,这些滑坡所造成的损失甚至超过地震本身。在地震区映秀,获取了地震边坡稳定性分析所需的地震滑坡编目图、强震监测数据、1：50000地质图、岩组单元的物理力学数据及基于1：50000地形图得到的DEM数据,所有这些数据都通过GIS（ilwis3.6）进行了矢量化及栅格化（10m）处理。基于上述数据,利用Newmark方法对每个单元格的变形及位移进行计算分析,然后通过Newmark位移与地震滑坡编目图进行对比分析,建立边坡失稳概率与Newmark位移之间的关系,用于地震滑坡预测及编图,为地震应急及灾后重建提供科学依据。     

地震崩滑预测方法及其工程应用研究

在对我国已有地震崩塌和滑坡资料 (简称崩滑 )的研究分析基础上 ,提出适用于我国西部地区地震崩滑的由粗至细、分级预测地震崩滑的方法。 1 )建立地震崩滑最大震中距 ( Rm)与地震震级 ( Ms)间关系的初判准则 ;2 )综合考虑岩性、结构类型、地形、气象、地震等因素对地震崩滑的共同作用 ,并对不同因素的主次作用进行区分和量化 ,建立预测地震崩滑的再判准则。并用 1 996年 2月 3日丽江 7.0级地震引发的地震崩塌和滑坡实例对此预测方法进行了验证。     

A Hazard Assessment Method for Potential Earthquake-Induced Landslides – A Case Study in Huaxian County, Shaanxi Province

The hazard assessment of potential earthquake-induced landslides is an important aspect of the study of earthquake-induced landslides. In this study, we assessed the hazard of potential earthquake-induced landslides in Huaxian County with a new hazard assessment method. This method is based on probabilistic seismic hazard analysis and the Newmark cumulative displacement assessment model. The model considers a comprehensive suite of information, including the seismic activities and engineering geological conditions in the study area, and simulates the uncertainty of the intensity parameters of the engineering geological rock groups using the Monte Carlo method. Unlike previous assessment studies on ground motions with a given exceedance probability level, the hazard of earthquake-induced landslides obtained by the method presented in this study allows for the possibility of earthquake-induced landslides in different parts of the study area in the future. The assessment of the hazard of earthquake-induced landslides in this study showed good agreement with the historical distribution of earthquake-induced landslides. This indicates that the assessment properly reflects the macroscopic rules for the development of earthquake-induced landslides in the study area, and can provide a reference framework for the management of the risk of earthquake-induced landslides and land planning.     

汶川地震滑坡与地震参数及地质地貌因素之间的相关关系

在对汶川地震诱发的典型滑坡进行野外调查和相关资料收集、分析和整理的基础上,对汶川地震滑坡与地震参数及坡度、岩土体特性等地质地貌因素之间的相关关系进行了统计分析。结果表明: (1)汶川地震滑坡主要发生在Ⅶ～Ⅺ烈度区, Ⅵ度及以下烈度区中发生的滑坡较少; (2)汶川地震滑坡主要发生在距震中300km的范围内,且距震中200km的范围内滑坡分布最为集中; (3)汶川地震滑坡的易发斜坡坡度为30～50,其中30～40是汶川地震滑坡发育最为敏感的坡度; (4)汶川地震滑坡主要发生在600～1500m的高程范围内,在600～1000m高程范围内的中低山和丘陵区滑坡分布最为集中; (5)砂泥岩、板岩、片岩、千枚岩等软岩类和土质类岩性是汶川地震滑坡的易发岩性,其次是软硬岩组合类,在统计的47个典型滑坡中,花岗岩、碳酸盐岩等硬岩类中发生的滑坡最少,而且由汶川地震直接导致复活的老滑坡也比较少。     

2022年MS6.8级泸定地震诱发地质灾害特征与空间分布规律研究

2022年9月5日四川甘孜泸定县发生6.8级地震,诱发了大量地质灾害,造成房屋损毁和多处道路阻断,并导致了严重的人员伤亡。快速预测地震诱发地质灾害空间分布对震后应急救援至关重要。为此,成都理工大学地质灾害防治与地质环境保护国家重点实验室利用已建立的地震诱发滑坡近实时预测模型,在震后2 h内,快速预测了地震诱发滑坡空间分布概率。同时,利用震后重点区域的无人机影像和国产高分六号影像,对地震诱发滑坡进行了智能识别和人工解译及现场调查复核,共解译滑坡3633处,总面积13.78 km2。研究发现本次泸定地震诱发滑坡,较2008年汶川和2017年九寨沟地震滑坡,规模相对较小。本次地震诱发滑坡主要分布于鲜水河断裂带和大渡河两侧,呈带状分布,在磨西镇、得妥镇及王岗坪彝族藏族乡等Ⅸ度烈度区相对集中。对控制滑坡空间分布的地形地貌、地质和地震3类因素9个因子进行分析,发现其主要分布在坡度35°~55°、高程1000~1800 m范围内;受断层控制强烈,主要分布在距断层1 km范围内;在花岗岩中最为发育。上述研究成果获得的地震诱发滑坡及受损道路和房屋分布情况,为震后应急救援提供了重要支撑。