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1.
Landslide susceptibility mapping using rough sets and back-propagation neural networks in the Three Gorges, China 总被引：3，自引：2，他引：1
In the Three Gorges of China, there are frequent landslides, and the potential risk of landslides is tremendous. An efficient and accurate method of generating landslide susceptibility maps is very important to mitigate the loss of lives and properties caused by these landslides. This paper presents landslide susceptibility mapping on the Zigui-Badong of the Three Gorges, using rough sets and back-propagation neural networks (BPNNs). Landslide locations were obtained from a landslide inventory map, supported by field surveys. Twenty-two landslide-related factors were extracted from the 1:10,000-scale topographic maps, 1:50,000-scale geological maps, Landsat ETM + satellite images with a spatial resolution of 28.5 m, and HJ-A satellite images with a spatial resolution of 30 m. Twelve key environmental factors were selected as independent variables using the rough set and correlation coefficient analysis, including elevation, slope, profile curvature, catchment aspect, catchment height, distance from drainage, engineering rock group, distance from faults, slope structure, land cover, topographic wetness index, and normalized difference vegetation index. The initial, three-layered, and four-layered BPNN were trained and then used to map landslide susceptibility, respectively. To evaluate the models, the susceptibility maps were validated by comparing with the existing landslide locations according to the area under the curve. The four-layered BPNN outperforms the other two models with the best accuracy of 91.53 %. Approximately 91.37 % of landslides were classified as high and very high landslide-prone areas. The validation results show sufficient agreement between the obtained susceptibility maps and the existing landslide locations. 相似文献
2.
三峡库区涉水滑坡众多,目前库岸滑坡空间发育规律及其影响因素尚不明确.收集三峡大坝至库尾江津长江两岸593处滑坡相关资料,选取地层岩性、斜坡结构、高程与坡度作为滑坡关键控制因素及库水作用这一诱发因素.沿三峡大坝追溯至库尾,根据不同影响因子把干流库岸进行分段研究,统计滑坡在各影响因子中的分布特征,分析其分布规律及内在机理,可得以下结论:（1）受不同岩组的工程地质性质差异,干流库岸稳定性差异较大,造成滑坡在空间分布上呈显著区域差异性与分带性特征;（2）在同一岩组的左、右两岸或上下游段滑坡发育密度呈明显局部差异性,其主要受斜坡结构影响,顺向坡中发育密度明显高于横向坡与逆向坡;（3）由于地形地貌条件及库水作用影响,滑坡后缘高程与坡度由库首至库尾逐渐降低,而前缘主要集中于100~175 m,滑坡复活变形的最主要诱发因素为库水位升降作用,当水位作用于滑坡中前部时影响效果最明显,影响时效随着滑坡逐年变形应力调整后逐渐减弱.研究结果为三峡库区滑坡防治提供了一定依据. 相似文献
3.
区域滑坡易发性的研究是滑坡空间预测的核心内容之一。从影像多尺度分割和面向对象的分类理论出发,以研究区遥感影像的熵、能量、相关性、对比度共4个参数作为影像纹理因子提取易发性特征,利用滑坡所处区域的库水影响等级、坡度、斜坡结构、工程岩组4类地质因子分析地质背景,搭建C5.0决策树的易发性分类模型,实现了对研究区内4类滑坡易发性单元的预测。结果表明:高易发性单元的工程岩组通常发育为软岩岩组和软硬相间岩组,且坡度在15°～30°之间;模型显示该区域训练样本和测试样本平均正确率达91.64%,Kappa系数分别为0.84,0.51,因此这种基于影像多尺度分割与地质因子分级的滑坡易发性分类研究具有一定的适用性。 相似文献
4.
运用地理信息系统和遥感技术,从LandsatTM遥感图像获取了一系列滑坡及其影响因子数据。结合粗糙集理论,对三峡库区秭归县青干河流域滑坡发生的影响因子进行了分析,提取了一组基本的滑坡影响条件属性因子,并导出了基于该因子集合的判断滑坡与非滑坡的规则集。研究结果表明,所选择的坡度、高程、斜坡类型、植被指数和岩石地层单元等5个条件属性因子对滑坡是重要的影响因素(核);由粗糙集生成的对预测滑坡相对较有价值的11条决策规则中,3条主要决策规则可作为滑坡影响因子的评价规则。 相似文献
5.
滑坡空间易发性分析有助于开展滑坡防灾减灾工作,训练有效的滑坡预测模型在其中扮演重要角色.以三峡库区湖北段为研究区,选取高程、坡度、斜坡结构、土地利用类型、岩土体类型、断裂距离、路网距离、河网距离、以及归一化植被指数这9个影响因子建立滑坡空间数据库,采用集成学习中的随机森林算法进行滑坡易发性评价.结果显示,随机森林抽样训练的方式有利于确定较优的训练参数,保证随机森林在不过拟合的情况下取得满意的拟合能力和泛化能力.随机森林绘制的滑坡易发性分级图显示出合理的空间分布,其中73.35%的滑坡分布在较高和极高级别区域.而巴东县北部、秭归县中部以及夷陵区南部等区域显示出较高的易发性级别.性能评估及易发性统计结果均表明随机森林是一种出色的算法,在滑坡空间预测领域具有较好的适用性. 相似文献
6.
三峡库区树坪滑坡变形失稳机制分析 总被引：8，自引：0，他引：8
树坪滑坡自2003年三峡水库蓄水以来,就一直持续变形。为了对其稳定性及变形发展趋势进行评价和预测,有必要对其变形失稳机制进行深入研究。为此,采用现场地质调查和勘探的方法确定了滑坡的形态和性质;充分挖掘变形监测数据,详细分析了滑坡的变形特征。在此基础上,深入研究了变形失稳机制及影响因素,并对滑坡的稳定性进行了计算和预测。结果表明,滑坡区地形、岩性及地质构造等地质因素控制了树坪滑坡的形成和发展;库水位下降和大气降雨进一步激励了滑坡的变形。库水位下降,坡体内地下水位随之下降,但其速度远小于库水位下降速度,导致坡体内水力梯度和渗透力明显增大,从而使滑坡稳定性急剧下降,并且库水位下降速度越快,滑坡的位移速率也越大,是典型的水库下降型滑坡。在库水位下降过程中,若出现明显的降雨过程,更加剧了滑坡的变形,有产生大规模滑动的可能性,须采取防护治理措施。 相似文献
7.
Landslide susceptibility mapping using LiDAR and DMC data: a case study in the Three Gorges area, China 总被引：2，自引：0，他引：2
The objective of this study is to map landslide susceptibility in Zigui segment of the Yangtze Three Gorges area that is known as one of the most landslide-prone areas in China by using data from light detection and ranging (LiDAR) and digital mapping camera (DMC). The likelihood ratio (LR) and logistic regression model (LRM) were used in this study. The work is divided into three phases. The first phase consists of data processing and analysis. In this phase, LiDAR and DMC data and geological maps were processed, and the landslide-controlling factors were derived such as landslide density, digital elevation model (DEM), slope angle, aspect, lithology, land use and distance from drainage. Among these, the landslide inventories, land use and drainage were constructed with both LiDAR and DMC data; DEM, slope angle and aspect were constructed with LiDAR data; lithology was taken from the 1:250,000 scale geological maps. The second phase is the logistic regression analysis. In this phase, the LR was applied to find the correlation between the landslide locations and the landslide-controlling factors, whereas the LRM was used to predict the occurrence of landslides based on six factors. To calculate the coefficients of LRM, 13,290,553 pixels was used, 29.5 % of the total pixels. The logical regression coefficients of landslide-controlling factors were obtained by logical regression analysis with SPSS 17.0 software. The accuracy of the LRM was 88.8 % on the whole. The third phase is landslide susceptibility mapping and verification. The mapping result was verified using the landslide location data, and 64.4 % landslide pixels distributed in “extremely high” zone and “high” zone; in addition, verification was performed using a success rate curve. The verification result show clearly that landslide susceptibility zones were in close agreement with actual landslide areas in the field. It is also shown that the factors that were applied in this study are appropriate; lithology, elevation and distance from drainage are primary factors for the landslide susceptibility mapping in the area, while slope angle, aspect and land use are secondary. 相似文献
8.
Chong Xu Xiwei Xu Fuchu Dai Zhide Wu Honglin He Feng Shi Xiyan Wu Suning Xu 《Natural Hazards》2013,68(2):883-900
The main purpose of this paper is to present the use of multi-resource remote sensing data, an incomplete landslide inventory, GIS technique and logistic regression model for landslide susceptibility mapping related to the May 12, 2008 Wenchuan earthquake of China. Landslide location polygons were delineated from visual interpretation of aerial photographs, satellite images in high resolutions, and verified by selecting field investigations. Eight factors, including slope angle, slope aspect, elevation, distance from drainages, distance from roads, distance from main faults, seismic intensity and lithology were selected as controlling factors for earthquake-triggered landslide susceptibility mapping. Qualitative susceptibility analyses were carried out using the map overlaying techniques in GIS platform. The validation result showed a success rate of 82.751 % between the susceptibility probability index map and the location of the initial landslide inventory. The predictive rate of 86.930 % was obtained by comparing the additional landslide polygons and the landslide susceptibility probability index map. Both the success rate and the predictive rate show sufficient agreement between the landslide susceptibility map and the existing landslide data, and good predictive power for spatial prediction of the earthquake-triggered landslides. 相似文献
9.
Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models 总被引：24，自引：0，他引：24
This study applied, tested and compared a probability model, a frequency ratio and statistical model, a logistic regression to Damre Romel area, Cambodia, using a geographic information system. For landslide susceptibility mapping, landslide locations were identified in the study area from interpretation of aerial photographs and field surveys, and a spatial database was constructed from topographic maps, geology and land cover. The factors that influence landslide occurrence, such as slope, aspect, curvature and distance from drainage were calculated from the topographic database. Lithology and distance from lineament were extracted and calculated from the geology database. Land cover was classified from Landsat TM satellite imagery. The relationship between the factors and the landslides was calculated using frequency ratio and logistic regression models. The relationships, frequency ratio and logistic regression coefficient were overlaid to make landslide susceptibility map. Then the landslide susceptibility map was compared with known landslide locations and tested. As the result, the frequency ratio model (86.97%) and the logistic regression (86.37%) had high and similar prediction accuracy. The landslide susceptibility map can be used to reduce hazards associated with landslides and to land cover planning. 相似文献
10.
11.
准确的滑坡易发性评价结果是滑坡风险评价的重要基础.为提升滑坡易发性评价精度,以三峡库区龙驹坝为例,选取坡度等10个因子构建滑坡易发性评价指标体系,应用频率比方法定量分析各指标与滑坡发育的关系.在此基础上,随机选取70%/30%的滑坡数据作为训练/测试样本,应用径向基神经网络和Adaboost集成学习耦合模型(RBNN-Adaboost),径向基神经网络和逻辑回归模型分别开展易发性评价.结果显示:水系距离、坡度等是滑坡发育的主控因素;RBNN-Adaboost耦合模型的预测精度最高(0.820),优于RBNN模型和LR模型的0.781和0.748.Adaboost集成算法能进一步提升模型的预测性能,所提出的耦合模型结合了两者的优点,具有更强的预测能力,是一种可靠的滑坡易发性评价模型. 相似文献
12.
Predictive landslide susceptibility mapping using spatial information in the Pechabun area of Thailand 总被引：2，自引：0，他引：2
Hyun-Joo Oh Saro Lee Wisut Chotikasathien Chang Hwan Kim Ju Hyoung Kwon 《Environmental Geology》2009,57(3):641-651
For predictive landslide susceptibility mapping, this study applied and verified probability model, the frequency ratio and
statistical model, logistic regression at Pechabun, Thailand, using a geographic information system (GIS) and remote sensing.
Landslide locations were identified in the study area from interpretation of aerial photographs and field surveys, and maps
of the topography, geology and land cover were constructed to spatial database. The factors that influence landslide occurrence,
such as slope gradient, slope aspect and curvature of topography and distance from drainage were calculated from the topographic
database. Lithology and distance from fault were extracted and calculated from the geology database. Land cover was classified
from Landsat TM satellite image. The frequency ratio and logistic regression coefficient were overlaid for landslide susceptibility
mapping as each factor’s ratings. Then the landslide susceptibility map was verified and compared using the existing landslide
location. As the verification results, the frequency ratio model showed 76.39% and logistic regression model showed 70.42%
in prediction accuracy. The method can be used to reduce hazards associated with landslides and to plan land cover. 相似文献
13.
Frequency ratio model based landslide susceptibility mapping in lower Mae Chaem watershed, Northern Thailand 总被引：4，自引：2，他引：2
The purpose of this study is to produce a landslide susceptibility map for the lower Mae Chaem watershed, northern Thailand
using a Geographic Information System (GIS) and remotely sensed images. For this purpose, past landslide locations were identified
from satellite images and aerial photographs accompanied by the field surveys to create a landslide inventory map. Ten landslide-inducing
factors were used in the susceptibility analysis: elevation, slope angle, slope aspect, lithology, distance from lineament,
distance from drainage, precipitation, soil texture, land use/land cover (LULC), and NDVI. The first eight factors were prepared
from their associated database while LULC and NDVI maps were generated from Landsat-5 TM images. Landslide susceptibility
was analyzed and mapped using the frequency ratio (FR) model that determines the level of correlation between locations of
past landslides and the chosen factors and describes it in terms of frequency ratio index. Finally, the output map was validated
using the area under the curve (AUC) method where the success rate of 80.06% and the prediction rate of 84.82% were achieved.
The obtained map can be used to reduce landslide hazard and assist with proper planning of LULC in the future. 相似文献
14.
Deformation and mechanism of landslide influenced by the effects of reservoir water and rainfall, Three Gorges, China 总被引：3，自引：0，他引：3
Since the impoundment of the Three Gorges Reservoir in June 2003, numerous preexisting landslides have been reactivated. This paper seeks to find the factors influencing landslide deformation and the relationship between displacement and fluctuation of the reservoir water level, while the displacement and the intensity of rainfall based on monitoring data; 6 years of monitoring were carried out on the Shiliushubao landslide, a old landslide, consisting of a deep-seated main block and two shallow blocks, with a volume of 1,180 × 104 m3 and located on the left bank of the Yangtze River, 66 km upstream of the Three Gorges dam. This landslide was reactivated by the impoundment and since then the landslide body has been experiencing persistent deformation with an observed maximum cumulative displacement of 8,598.5 mm up to December 2009. Based on the monitoring data, we analyzed the relationship between the fluctuation of the reservoir water level and displacement, rainfall and displacement, and found that the rainfall is the major factor influencing deformation for two shallow blocks and the displacement has a positive correlation with the variation of rainfall intensity. The fluctuation of the reservoir water level is the primary factor for main block, and the deformation rate has a negative correlation with the variation of reservoir water level, declined with the rise of the water level and increased with the drawdown of the water level. 相似文献
15.
三峡库区涉水滑坡主要影响因素是水位和降雨量,也是库区滑坡体失稳的主要影响因素和诱发因素。库区每年重复着水位升降不利于滑坡的稳定,而降雨特别是大强度的降雨也诱发产生滑坡。当水位波动遇到降雨,出现工况叠加,滑坡将加剧。因此,有必要对影响滑坡变形的主导因素进行了解分析。2016年6月三峡库区全面展开了自动化监测,使得数据统计方便可靠。本文采用滑坡变形速率、降雨量、库水位变化、最大水位变化速率、淹没程度,运用灰色关联度分析法对涉水滑坡进行了计算分析。水位下降阶段,文中土质滑坡变形受库水位影响最大。水位上升阶段,该土质滑坡上部变形受降雨影响最大,下部受水位影响最大。文中岩质滑坡总是受库水位影响最大。 相似文献
16.
求解库岸边坡岩土体的渗透系数是研究滑坡渗流场及多场演化的基础,一般通过原位试验和室内试验求得,但试验成本较高且试验位置具有一定的随机性。本文以三峡库区马家沟滑坡为例,提出一种利用地下水位动态观测资料反演滑坡岩土层渗透系数的方法。具体步骤为:（1）依据滑坡的勘察资料和水位观测数据,构建滑坡数值模型;（2）利用SPSS生成不同渗透系数正交试验组合,并将渗透系数代入数值模型中计算监测井的水位,得到不同渗透系数及其对应的模拟水位数据;（3）应用遗传算法优化的支持向量机构建坡体模拟水位与渗透系数的非线性映射关系,再通过代入实际动态监测水位值求得滑坡岩土层的渗透系数;（4）将求得的渗透系数代入数值模型,用计算的模拟水位与实际观测水位进行对比验证。研究结果表明:遗传算法优化的支持向量机具有良好的学习预测效果,能准确预测渗透系数与水位的关系。该反演方法具有高效、准确的优点,反演结果的精度满足实际应用需要。 相似文献
17.
Probabilistic landslide susceptibility and factor effect analysis 总被引：18，自引：0，他引：18
The susceptibility of landslides and the effect of landslide-related factors at Penang in Malaysia using the geographic information system (GIS) and remote sensing data have been evaluated. Landslide locations were identified in the study area from interpretation of aerial photographs and from field surveys. Topographical and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. The factors chosen that influence landslide occurrence were: topographic slope, topographic aspect, topographic curvature and distance from drainage, all from the topographic database; lithology and distance from lineament, taken from the geologic database; land use from Landsat Thermatic Mapper (TM) satellite images; and the vegetation index value from SPOT HRV (High-Resolution Visible) satellite images. Landslide hazardous areas were analyzed and mapped using the landslide-occurrence factors employing the probability–frequency ratio method using the all factors. To assess the effect of these factors, each factor was excluded from the analysis, and its effect verified using the landslide location data. As a result, all factors had relatively positive effects, except lithology, on the landslide susceptibility maps in the study area. 相似文献
18.
三峡库区岸坡消落带是库岸边坡稳定性的敏感地带。库区内多次发生的地质灾害均与消落带的岩体劣化有关。随着时间的推移消落带的岩体劣化情况日益加剧,新生型滑坡不断涌现。本文通过实地调查与室内分析,系统总结了三峡库区秭归至巴东段岸坡消落带岩体劣化的类型以及新生型滑坡隐患的演化模式。研究表明,区内消落带岩性主要以碳酸盐岩类和碎屑岩类为主,碳酸盐岩类劣化类型主要有溶蚀(潜蚀)、裂缝显化与扩张和机械侵蚀,碎屑岩类的劣化类型主要有松动(剥落)、冲蚀(磨蚀)、结构面崩解块裂和软硬相间侵蚀,其中以松动/剥落型最为发育。在此基础上结合结构面发育特征、岸坡结构、岩性及结构和边界特征,厘定了不同岸坡消落带岩体劣化演化形成新生型滑坡隐患点的模式,碳酸岩盐类岸坡主要以基座碎裂压溃型、基座掏空倾倒型、顺向滑移型为主;碎屑岩类岸坡主要以软硬相间坍(崩)塌型、视倾向楔形滑动型、顺向滑移型及逆向倾倒型为主。研究结果可为三峡库区地质灾害监测预警及防治提供技术支撑。 相似文献
19.
三峡水库区陈家沟滑坡地质特征与防治措施 总被引：4，自引：0，他引：4
在研究了三峡水库区奉节县陈家沟滑坡的工程地质条件及滑坡体基本特征的基础上，介绍了该滑坡的结构及变形特征。从滑坡形成条件、诱发变形因素两方面分析了滑坡形成的原因及诱发坡体失稳的主要因素；据岩土样品的试验值、现场大剪值，结合地区经验值及反算值，确定计算滑坡稳定性及剩余滑坡推力的抗剪强度参数，考虑到未来三峡水库蓄水，在不同工况下对滑坡体进行稳定性计算。结果表明：在天然及暴雨情况下，滑坡整体均处于稳定状态；次级滑坡体在饱水及水库蓄水后，处于临界蠕滑或失稳状态。结合工程实际对滑坡治理进行初步研究，提出回填压脚专档为幸捕以排水的综合治理措施。 相似文献