共查询到18条相似文献，搜索用时 125 毫秒
1.
鲜水河断裂带是发育于青藏高原东缘的一条大型左旋走滑断裂带,该区新构造活动强烈且历史强震频发,一系列大型-巨型滑坡沿断裂带密集分布。在资料收集的基础上,对鲜水河断裂带两侧10 km区域内进行遥感解译和野外地质调查,建立数据库并对滑坡主要影响因素进行分析。在滑坡区域发育分布规律分析的基础上,选取地形坡度、地形坡向、地面高程、平面曲率、地形湿度指数、活动断裂、工程地质岩组、年降雨量、河流、道路、植被覆盖指数等11个因素作为滑坡易发性评价因子,在ArcGIS软件平台上,采用证据权模型开展了滑坡易发性评价。根据成功率曲线对评价结果的检验,滑坡易发性评价结果具有较好的精度,并将研究区的滑坡易发程度划分为极高易发、高易发、中等易发、低易发和不易发5个级别。滑坡的易发性受鲜水河断裂带影响显著,极高易发区和高易发区主要分布在东谷到道孚县沿鲜水河断裂带两侧,以及康定县城和磨西镇附近;中等易发区主要分布在鲜水河支流两岸及省道沿线;滑坡低易发区和不易发区主要分布在人类工程活动少的高山地带以及地形相对平缓的区域。滑坡易发性评价结果很好地反映了鲜水河断裂带区域内滑坡发育分布现状,为该区重大工程规划建设和防灾减灾提供参考依据。 相似文献
2.
巴塘断裂带位于青藏高原东部,呈北东—南西向展布,全新世活动强烈,沿断裂带崩塌、滑坡、泥石流等地质灾害极为发育。基于遥感解译和野外地质调查,在巴塘断裂带两侧10 km范围内识别出滑坡93处;在分析滑坡空间发育特征的基础上,选取地形地貌(地面高程、地形坡度和地形坡向)、地形湿度指数、地层岩性、活动断裂、降雨量、水系、人类工程活动和植被覆盖等10个因素作为滑坡易发程度的主控因素,采用加权证据权法建立滑坡易发性评价模型,开展巴塘断裂带滑坡易发性评价;成功率(ROC)曲线检验结果表明此次滑坡易发性评价的准确率为82.3%。采用基于自然断点法将滑坡易发程度划分为极高易发、高易发、中等易发和低易发4个级别,结果表明滑坡易发性受巴塘断裂带和河流控制显著,极高易发区和高易发区主要分布在巴塘断裂带、金沙江和巴曲河谷及一级支流两侧,中等易发区主要分布在巴曲各支流中上游,低易发区主要分布在人类工程活动弱的高山地带以及地形相对平缓的区域。滑坡易发性评价结果很好地反映了巴塘断裂带现今滑坡发育分布特征,对该区重大工程规划建设和防灾减灾具有科学指导意义。 相似文献
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4.
地处青藏高原东北缘的黄河与湟水谷地,由于剧烈的地质活动、较大高差与强烈水力作用等,使得地质灾害非常频繁,为明确该区域的地灾易发性区划,选取地貌、坡度、坡高、植被、岩性、降雨量和距断层、距河流、距道路等因子构建评价指标体系,采用信息量模型计算崩塌、滑坡、泥石流及其综合地质灾害易发性指数,将研究区地质灾害易发性划分为极高、高、中、低、极低五级易发区。结果表明:极高易发区主要位于河谷地区,占2.03%,包括贵德县、湟中县、乐都县的黄河及湟水等河流中下游地区;高易发区主要位于中小起伏山间盆地地区,占21.2%;中易发区主要位于中起伏山地地区,占23.45%,属于高、低易发区的过渡区域;低易发区主要位于大中起伏山地地区,占42.1%;极低易发区主要位于冷龙岭、拉脊山、西倾山等山地,占11.23%。研究结果对河湟谷地的防灾减灾及社会可持续发展意义重大。 相似文献
5.
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。 相似文献
6.
《西北地质》2020,(2)
云南省陇川县地质环境脆弱,易发生滑坡灾害,对其开展滑坡易发性评价对指导陇川县的滑坡地质灾害防治具有重大意义。根据陇川县地理环境、地质环境、人类活动等条件,选取高程、坡度、坡向、剖面曲率、平面曲率、归一化植被指数、水系距离、断层距离、地层岩性和道路距离等10个评价因子,利用信息量模型和ArcGIS软件进行滑坡易发性评价。结果表明,滑坡高易发区主要位于研究区北部、东南部和西南部;中易发区主要位于中部、东部和西部部分地区;低易发区主要位于陇把镇、城子镇大部分地区和户撒阿昌族乡的西北部;不易发区主要位于清平乡中部、城子镇中部部分地区、以及章凤镇大部分地区。在中易发区和高易发区包含83.56%的滑坡灾害点,且滑坡面积随着易发性等级的增加也随之增大。滑坡中、高易发区内发生的滑坡面积分别占研究区滑坡面积的22.79%和58.13%,分析结果与实际灾害分布特征相吻合,可为研究区及类似区域的滑坡地质灾害防灾减灾工作提供参考意见。 相似文献
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《地质科技情报》2020,(3)
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。 相似文献
8.
基于深度学习的CZ铁路康定—理塘段滑坡易发性评价 总被引：1，自引：0，他引：1
CZ铁路康定至理塘段地处青藏高原东部边缘,区域内地形地貌多变、地质构造复杂,滑坡灾害极其发育,严重威胁着CZ铁路康定至理塘段的规划建设和未来安全运行。因此,选取高程、坡向、平面曲率、剖面曲率、地形起伏度、地表切割度、地形湿度指数、归一化植被指数、岩性、距断层距离、距河流距离、距道路距离共计12个影响因子构建滑坡空间数据库,采用深度学习的卷积神经网络(convolutional neural network,CNN)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(13.76%)、高易发区(14.00%)、中易发区(15.86%)、低易发区(18.17%)、极低易发区(38.21%)5个等级,并与人工神经网络(artificial neural network,ANN)模型进行对比。结果表明,CNN模型的评价精度AUC(0.87)大于ANN(0.84)模型,且极高易发区的频率比值高于ANN模型,CNN模型在本研究区有着更高的预测能力;极高和高易发区主要分布在水系较为发育的地区,沿着雅砻江和其他河流两侧2 km范围内呈带状分布。滑坡易发性评价结果较好地反映了研究区滑坡灾害发育的分布现状,能够为该区的CZ铁路建设和未来安全运行过程中的防灾减灾工作提供科学的依据。 相似文献
9.
以安徽省池州市为研究区,选取坡度、坡向、工程地质岩组、断裂、道路、河流、降雨量、土地利用类型8个影响因子进行地质灾害易发性评价。基于全市345个地质灾害点(崩塌和滑坡)样本数据,采用信息量模型对研究区各影响因子的信息量进行计算,依据灾害点密度将区域灾害易发性划分为5个等级:低易发区、较低易发区、中易发区、较高易发区和高易发区。结果表明:安徽省池州市地质灾害高易发区和较高易发区主要分布在坡度较大的山区河谷两侧,反映人类工程活动破坏、流水冲刷作用和地形地貌因素是影响该区地质灾害的主要因素。其中,高易发区和较高易发区面积为1 801.47 km~2,分别占全区总面积的7.89%和13.88%,高易发区和较高易发区内的灾害点分别占所有灾害点的48.7%和21.5%,其中高易发区的灾积比为6.17,明显高于其他易发等级。对地质灾害易发性的方法与技术的研究,旨在为该区的灾害防治和经济建设提供技术参考。 相似文献
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舟曲县是中国罕见的滑坡、泥石流地质灾害高发区,其防灾减灾工作具有一定的挑战性。依托舟曲县1∶50 000地质灾害风险调查工作,深入分析孕灾地质条件,选取地质灾害频率比、地质灾害面积模数比、地质灾害体积模数比、坡度、坡度变化率、坡形、切割深度、沟壑密度、岩土体类型、地质构造、植被指数11个评价因子,建立AHP评价模型,确定各因子权重,运用GIS平台综合评价舟曲县地质灾害易发性。结果显示：舟曲县地质灾害极高易发区和高易发区的面积分别为68.98 km2、390.9 km2,分别占县域总面积的2.29%和12.97%,主要分布在人员财产集中的白龙江流域、石门沟流域、拱坝河流域中下游和博峪河流域舟曲段中部区域;中易发区、低易发区对应的面积分别为1 166.21 km2和1 387.76 km2。研究成果为舟曲县城镇整体规划和地质灾害防治提供决策参考。 相似文献
11.
High incidences of slope movement are observed throughout Cuyahoga River watershed in northeast Ohio, USA. The major type of slope failure involves rotational movement in steep stream walls where erosion of the banks creates over-steepened slopes. The occurrence of landslides in the area depends on a complex interaction of natural as well as human induced factors, including: rock and soil strength, slope geometry, permeability, precipitation, presence of old landslides, proximity to streams and flood-prone areas, land use patterns, excavation of lower slopes and/or increasing the load on upper slopes, alteration of surface and subsurface drainage. These factors were used to evaluate the landslide-induced hazard in Cuyahoga River watershed using logistic regression analysis, and a landslide susceptibility map was produced in ArcGIS. The map classified land into four categories of landslide susceptibility: low, moderate, high, and very high. The susceptibility map was validated using known landslide locations within the watershed area. The landslide susceptibility map produced by the logistic regression model can be efficiently used to monitor potential landslide-related problems, and, in turn, can help to reduce hazards associated with landslides. 相似文献
12.
Javed Mallick Ram Karan Singh Mohammed A. AlAwadh Saiful Islam Roohul Abad Khan Mohamed Noor Qureshi 《Environmental Earth Sciences》2018,77(7):276
Landslides are natural geological disasters causing massive destructions and loss of lives, as well as severe damage to natural resources, so it is essential to delineate the area that probably will be affected by landslides. Landslide susceptibility mapping (LSM) is making increasing implications for GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. It is considered to be an effective tool to understand natural disasters related to mass movements and carry out an appropriate risk assessment. This study is based on an integrated approach of GIS and statistical modelling including fuzzy analytical hierarchy process (FAHP), weighted linear combination and MCE models. In the modelling process, eleven causative factors include slope aspect, slope, rainfall, geology, geomorphology, distance from lineament, distance from drainage networks, distance from the road, land use/land cover, soil erodibility and vegetation proportion were identified for landslide susceptibility mapping. These factors were identified based on the (1) literature review, (2) the expert knowledge, (3) field observation, (4) geophysical investigation, and (5) multivariate techniques. Initially, analytical hierarchy process linked with the fuzzy set theory is used in pairwise comparisons of LSM criteria for ranking purposes. Thereafter, fuzzy membership functions were carried out to determine the criteria weights used in the development of a landslide susceptibility map. These selected thematic maps were integrated using a weighted linear combination method to create the final landslide susceptibility map. Finally, a validation of the results was carried out using a sensitivity analysis based on receiver operator curves and an overlay method using the landslide inventory map. The study results show that the weighted overlay analysis method using the FAHP and eigenvector method is a reliable technique to map landslide susceptibility areas. The landslide susceptibility areas were classified into five categories, viz. very low susceptibility, low susceptibility, moderate susceptibility, high susceptibility, and very high susceptibility. The very high and high susceptibility zones account for 15.11% area coverage. The results are useful to get an impression of the sustainability of the watershed in terms of landsliding and therefore may help decision makers in future planning and mitigation of landslide impacts. 相似文献
13.
Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong 总被引：33，自引：1，他引：33
Steep terrain and the high frequency of tropical rainstorms make landslide occurrence on natural terrain a common phenomenon
in Hong Kong. For example, more than 800 slope failures were triggered by a rainstorm in November 1993 on Lantau Island, Hong
Kong. Maps of recent landslides interpreted from aerial photographs, in combination with a geographical information system,
were used to evaluate the frequency and distribution of landslides, with particular reference to such physical parameters
as lithology, slope gradient, slope aspect, elevation, vegetation cover, and proximity to drainage line, all of which are
considered to be influential in the occurrence of landslides. A stepwise logistic regression model was obtained between landslide
susceptibility and the above mentioned physical parameters. The study area has been classified into five classes of relative
landslide susceptibility, namely, very low, low, moderate, high, and very high, based on this methodology.
Received: 17 December 1999 · Accepted: 21 March 2000 相似文献
14.
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。 相似文献
15.
本文选择东南沿海地区具有典型降雨型滑坡的淳安县作为研究区,在完成全县地质灾害详细调查的基础上,选取高程、坡度、坡向、曲率、工程地质岩组、距断层距离、距道路距离、土地利用和植被等9个滑坡影响因子,利用GIS技术与确定性系数分析方法,对这9个影响因子开展敏感性分析。研究结果表明:(1) 寒武、震旦、石炭和白垩系是滑坡易发地层,侵入岩组、紫红色砂岩、碳酸盐岩夹碎屑岩、碳酸盐岩为主的岩组是滑坡高敏感性岩组;滑坡受断层影响总体上随着距离断层由近及远逐渐降低;(2) 坡度范围10°~35°是滑坡的易发坡度,30°~35°滑坡数量达到峰值;SE和S等朝南坡向是滑坡最易发坡向;高程范围为100~200m是滑坡最易发区间;凹坡最易发生滑坡,而凸坡则滑坡敏感性最差;非林地、茶叶、竹林和经济林等是滑坡高敏感植被类型;(3) 住宅用地、耕地、园地等与人类活动密切相关的用地类型是滑坡易发地类;距道路距离因子对滑坡敏感性低,相关性不明显。上述各滑坡影响因子最利于滑坡发生的数值区间确定,将为研究区进一步开展降雨型滑坡区域易发性评价及预测奠定基础。 相似文献
16.
Landslide susceptibility assessment in the İzmir (West Anatolia,Turkey) city center and its near vicinity by the logistic regression method 总被引：1，自引：1，他引：0
A landslide susceptibility assessment for İzmir city (Western Turkey), which is the third biggest city of Turkey, was performed
by a logistic regression method. A database of landslide characteristics was prepared using detailed field surveys. The major
landslides in the study area are generally observed in the field, dominated by weathered volcanics, and 39.63% of the total
landslide area is in this unit. The parameters of lithology, slope gradient, slope aspect, distance to drainage, distance
to roads and distance to fault lines were used as variables in the logistic regression analysis. The effect of each parameter
on landslide occurrence was assessed from the corresponding coefficients that appear in the logistic regression function.
On the basis of the obtained coefficients, lithology plays the most important role in determining landslide occurrence and
distribution. Slope gradient has a more significant effect than the other geomorphological parameters, such as slope aspect
and distance to drainage. Using a predicted map of probability, the study area was classified into five categories of landslide
susceptibility: very low, low, moderate, high and very high. Whereas 49.65% of the total study area has very low susceptibility,
very high susceptibility zones make up 11.69% of the area. 相似文献
17.
山区地质灾害易发性评价对城镇地质灾害风险管理具有重要意义。本文以康定市为例,以斜坡单元为最小评价单元,选取高程、坡度、坡向、曲率、工程地质岩组、距道路距离、距断裂距离、距水系距离和斜坡结构等9个滑坡影响因子,根据各因子滑坡面积比曲线与证据权值曲线的突变点,划分滑坡影响因子二级状态,并对各影响因子进行相关性分析,剔除相关性较高的距道路距离因子,在此基础上,采用证据权模型进行滑坡易发性评价。对已有治理工程的斜坡单元,本文尝试利用折减系数法对其易发性进行进一步评价。结合现场调查,将研究区滑坡易发性程度划分为：极高易发、高易发、中等易发、低易发。评价结果表明,自然工况下极高易发区主要位于康定市炉城镇以及研究区北侧二道桥村一带,高易发区主要位于雅拉河、折多河与瓦斯沟河谷两侧,对治理工程所在的斜坡单元进行折减后,极高易发区面积由11.21%降至8.42%,滑坡比率由4.03降低至2.3,研究结果符合实际情况,模型精度达77.8%。评价结果较好地反映了康定市区的滑坡易发性分布情况,可为城镇精细化评价提供一定的参考依据。 相似文献
18.
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 总被引：1，自引：0，他引：1
2017年8月8日九寨沟MS7.0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。 相似文献