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1.
Over the last few decades, many researchers have produced landslide susceptibility maps using different techniques including the probability method (frequency ratio), the analytical hierarchy process (AHP), bivariate, multivariate, logistics regression, fuzzy logic and artificial neural network In addition, a number of parameters such as lithology, slope, aspect, land cover, elevation, distance to stream, drainage density, distance to lineament, seismicity, and distance to road are recommended to analyze the mechanism of landslides. The data quality is a very important issue in landslide studies, and more accurate results will be achieved if the data is adequate, appropriate and drawn from a wide range of parameters. The aim of this study was to evaluate the susceptibility of the occurrence of landslides in Trabzon province, situated in north east Turkey. This was achieved using the following five methods the frequency ratio model, AHP, the statistical index (Wi), weighting factor (Wf) methods, and the logistics regression model, incorporating a Geographical Information System (GIS) and remote sensing techniques. In Trabzon province there has been an increasing occurrence of landslides triggered by rainfall. These landslides have resulted in death, significant injury, damage to property and local infrastructure and threat of further landslides continues. In order to reduce the effects of this phenomenon, it is necessary to scientifically assess the area susceptible to landslide. To achieve this, landslide susceptible areas were mapped the landslide occurrence parameters were analyzed using five different methods. The results of the five analyses were confirmed using the landslide activity map containing 50 active landslide zones. Then the methods giving more accurate results were determined. The validation process showed that the Wf method is better in prediction than the frequency ratio model, AHP, the statistical index (Wi), and logistics regression model.  相似文献   

2.
A detailed landslide-susceptibility map was produced using a data-driven objective bivariate analysis method with datasets developed for a geographic information system (GIS). Known as one of the most landslide-prone areas in China, the Zhongxian-Shizhu Segment in the Three Gorges Reservoir region of China was selected as a suitable case because of the frequency and distribution of landslides. The site covered an area of 260.93 km2 with a landslide area of 5.32 km2. Four data domains were used in this study, including remote sensing products, thematic maps, geological maps, and topographical maps, all with 25 m × 25 m pixels. Statistical relationships for landslide susceptibility were developed using landslide and landslide causative factor databases. All continuous variables were converted to categorical variables according to the percentile divisions of seed cells, and the corresponding class weight values were calculated and summed to create the susceptibility map. According to the map, 3.6% of the study area was identified as high-susceptibility. Extremely low-, very low-, low-, and medium-susceptibility zones covered 19.66%, 31.69%, 27.95%, and 17.1% of the area, respectively. The high- and medium-hazardous zones are along both sides of the Yangtze River, being in agreement with the actual distribution of landslides.  相似文献   

3.
A correct assessment of the landslide susceptibility component is extremely useful for the diminution of associated potential risks to local economic development, particularly in regard to land use planning and soil conservation. The purpose of the present study was to compare the usefulness of two methods, i.e., binary logistic regression (BLR) and analytical hierarchy process (AHP), for the assessment of landslide susceptibility over a 130-km2 area in the Moldavian Plateau (eastern Romania) region, where landslides affect large areas and render them unsuitable for agriculture. A large scale inventory mapping of all types of landslides (covering 13.7% of the total area) was performed using orthophoto images, topographical maps, and field surveys. A geographic information system database was created, comprising the nine potential factors considered as most relevant for the landsliding process. Five factors (altitude, slope angle, slope aspect, surface lithology, and land use) were further selected for analysis through the application of a tolerance test and the stepwise filtering procedure of BLR. For each predictor, a corresponding raster layer was built and a dense grid of equally spaced points was generated, with an approximately equal number of points inside and outside the landslide area, in order to extract the values of the predictors from raster layers. Approximately half of the total number of points was used for model computation, while the other half was used for validation. Analytical hierarchy process was employed to derive factor weights, with several pair-wise comparison matrices being tested for this purpose. The class weights, on a scale of 0 to 1, were taken as normalized landslide densities. A comparison of results achieved through these two approaches showed that BLR was better suited for mapping landslide susceptibility, with 82.8% of the landslide area falling into the high and very high susceptibility classes. The susceptibility class separation using standard deviation was superior to either the equal interval or the natural break method. Results from the study area suggest that the statistical model achieved by BLR could be successfully extrapolated to the entire area of the Moldavian Plateau.  相似文献   

4.
《土壤圈》2016,(3)
A correct assessment of the landslide susceptibility component is extremely useful for the diminution of associated potential risks to local economic development, particularly in regard to land use planning and soil conservation. The purpose of the present study was to compare the usefulness of two methods, i.e., binary logistic regression(BLR) and analytical hierarchy process(AHP), for the assessment of landslide susceptibility over a 130-km~2 area in the Moldavian Plateau(eastern Romania) region, where landslides affect large areas and render them unsuitable for agriculture. A large scale inventory mapping of all types of landslides(covering 13.7% of the total area) was performed using orthophoto images, topographical maps, and field surveys. A geographic information system database was created, comprising the nine potential factors considered as most relevant for the landsliding process. Five factors(altitude, slope angle, slope aspect, surface lithology, and land use) were further selected for analysis through the application of a tolerance test and the stepwise filtering procedure of BLR. For each predictor, a corresponding raster layer was built and a dense grid of equally spaced points was generated, with an approximately equal number of points inside and outside the landslide area, in order to extract the values of the predictors from raster layers. Approximately half of the total number of points was used for model computation, while the other half was used for validation. Analytical hierarchy process was employed to derive factor weights, with several pair-wise comparison matrices being tested for this purpose. The class weights, on a scale of 0 to 1, were taken as normalized landslide densities. A comparison of results achieved through these two approaches showed that BLR was better suited for mapping landslide susceptibility, with 82.8% of the landslide area falling into the high and very high susceptibility classes. The susceptibility class separation using standard deviation was superior to either the equal interval or the natural break method. Results from the study area suggest that the statistical model achieved by BLR could be successfully extrapolated to the entire area of the Moldavian Plateau.  相似文献   

5.
[目的]探讨汶川地震强震区滑坡的活动强度演变与敏感性,为滑坡、泥石流等地质灾害风险管理提供依据。[方法]选取四川省都江堰市龙池镇龙溪河12条泥石流流域为研究区,通过对研究区震后4期遥感影像的滑坡解译分析,研究震后滑坡的活动演化特征;同时利用概率综合判别法—层次分析法对滑坡物源进行多期敏感性评价。[结果]地震后该区域产生了825个强震滑坡;2009—2017年,在强震滑坡区域外新增376个滑坡,至2017年,仍活动的滑坡数量减少到368个,占滑坡总数的30.6%,同时利用曲线下面积(AUC)检验多期敏感性评价结果,准确率为75.6%~81.4%,评价效果较好。[结论]强震区震后活动滑坡数量及高敏感性区域面积整体表现降低趋势,表明震后滑坡处于逐步恢复过程,强震区的地质灾害活动但活动强度仍远远高于震前。  相似文献   

6.
汶川地震前后崩塌和滑坡分布特征与敏感性对比分析   总被引:1,自引:0,他引:1  
以汶川地震活动断裂龙门山断裂带穿过的12个县(市)为研究区,分析了研究区汶川地震前后崩塌和滑坡空间分布特征,并使用统计学方法Logistic回归模型分别对震前震后的崩塌和滑坡敏感性进行评价,结合崩塌和滑坡敏感性变化矩阵,分析了汶川地震后崩塌和滑坡敏感性的空间变化特征。震前崩塌和滑坡高敏感区主要沿河谷分布,而震后崩塌和滑坡高敏感区主要沿龙门山断裂带分布。震前的极高敏感区震后仍表现为极高敏感区,而靠近断裂带的区域,震前的低敏感区转换为高敏感和极高敏感区。  相似文献   

7.
香港暴雨中心迁移与滑坡位置关系分析   总被引:1,自引:0,他引:1  
香港地区每年均有一定数量的滑坡灾害发生,诱发滑坡灾害的主要因子是强降水,即暴雨.暴雨过程中,降水强度的时空分布存在一定差异性,这种降水强度的时空与滑坡灾害的时空分布存在一定的联系.以香港地区1992年5月8日暴雨为例,以30 min为时间间隔,分析了暴雨中心时空变动与滑坡事件时空分布及出现频率之间的关系,发现空间上滑坡均出现在暴雨中心或暴雨中心的边沿地区;时间上滑坡事件出现在暴雨中心出现或上一阶段时间内;并且降水的强度与滑坡的出现频率也有一定关系.  相似文献   

8.
基于GIS和多目标评价方法的果树适宜性评价   总被引:9,自引:4,他引:5  
漳州地区是福建省乃至全国有名的水果之乡,地貌复杂,自然资源与生态环境差异显著。为了科学合理地利用自然资源,对该地区进行果树适宜性综合评价,分析其种植现状与利用潜力,提供科学决策依据。首先建立研究区域内土壤、气候与地形等数据库,并利用地形对气候分布状况进行校正,同时通过LandsatTM遥感影像的分析解译得到研究区域内的土地利用现状分布图和主要果树种植分布图,在此基础上采用GIS和多目标评价(MCE)方法对漳州地区三种主要果树(香蕉、荔枝和龙眼)进行适宜性评价,最后综合分析这些果树适宜分布现状与利用潜力。研究结果表明,漳州地区大部分区域都非常适宜种植这三种水果,发展水果生产潜力较大。  相似文献   

9.
降雨入渗作用下秭归向斜核部南段斜坡稳定性评价   总被引:1,自引:0,他引:1       下载免费PDF全文
[目的]开展降雨条件下湖北省秭归县向斜核部斜坡稳定性评价研究,为政府部门减灾防灾工程提供科学支持,为滑坡灾害的预测和管理提供科学依据。[方法]以耦合了地下水动力学的TRIGRS无限斜坡稳定性计算模型为基础,详细介绍了斜坡稳定性评价的数据处理过程以及参数选取方法。[结果]发生斜坡失稳的区域多位于松散土体中等厚—较厚,地形坡度中等的区域,尤其是土层厚度在7—10m,地形坡度在20°~30°范围内为斜坡失稳高发区。[结论]在土层厚度和地形地貌的双重控制下,短历时强降雨入渗作用导致孔隙水压力增大,这些区域的斜坡土体极易发生滑动,为滑坡危险性较高的多发区域。斜坡稳定性评价结果和滑坡实际分布吻合程度较高,在一定程度上反映出降雨诱发滑坡空间分布关系和分布规律。  相似文献   

10.
甘肃东部滑坡遥感调查分析评价   总被引:3,自引:2,他引:1  
以TM数据为基础资料,结合SPOT图像及航片、地形图、地质图,建立了滑坡遥感解译标志,对甘肃东部滑坡进行了遥感调查。分析了滑坡分布特征,将滑坡分为2个大区8个小区。根据滑坡的密度、规模、危害程度,对以上地区进行了危险度评价并划分出三个等级:Ⅰ级极危险区有兰州—定西滑坡带、临夏—渭源滑坡带、通渭—秦安—清水滑坡带、舟曲—武都白龙江滑坡带;Ⅱ级危险滑坡带有武山—天水滑坡带、礼县—成县嘉陵江上游滑坡带;Ⅲ级危险区有华亭—崇信滑坡带、环县—庆阳滑坡带。  相似文献   

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