首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到10条相似文献，搜索用时 278 毫秒
1.
嘉陵江流域北碚段基于GIS平台的地质灾害易发性评价   总被引：1，自引：0，他引：1  
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。  相似文献   

2.
Landslides lead to a great threat to human life and property safety. The delineation of landslide-prone areas achieved by landslide susceptibility assessment plays an important role in landslide management strategy. Selecting an appropriate mapping unit is vital for landslide susceptibility assessment. This paper compares the slope unit and grid cell as mapping unit for landslide susceptibility assessment. Grid cells can be easily obtained and their matrix format is convenient for calculation. A slope unit is considered as the watershed defined by ridge lines and valley lines based on hydrological theory and slope units are more associated with the actual geological environment. Using 70% landslide events as the training data and the remaining landslide events for verification, landslide susceptibility maps based on slope units and grid cells were obtained respectively using a modified information value model. ROC curve was utilized to evaluate the landslide susceptibility maps by calculating the training accuracy and predictive accuracy. The training accuracies of the grid cell-based susceptibility assessment result and slope unit-based susceptibility assessment result were 80.9 and 83.2%, and the prediction accuracies were 80.3 and 82.6%, respectively. Therefore, landslide susceptibility mapping based on slope units performed better than grid cell-based method.  相似文献   

3.
The reliability of susceptibility maps depends largely on the quality of the information used for its evaluation. This study seeks to analyze the influence of sample size and type on the results of discriminant analysis applied to shallow landslide susceptibility assessment. The study also assesses the role of the terrain unit in discriminant analysis. To this end, two databases based on fieldwork (slope unit) and GIS with 15- and 45-m grid cells (grid cell-based unit), were compared in the same zone at La Pobla de Lillet, Spanish Eastern Pyrenees. The results show that although there is no significant influence of the type of sample, it is necessary to use at least half of the individuals of the sample in order to obtain good results from discriminant analysis. It is the terrain unit that exerts the biggest influence on the result of susceptibility. Some morphometric parameters related to landslides were compared in the databases. The slope unit of the fieldwork database better reflects the land characteristics than the regular grid used by GIS. The values of the variables obtained by GIS procedures are smooth, obtaining mean errors for the slope angle variable of 19.5 and 33.5% for the grids of 15 and 45 m, respectively, in the study area. One-way and T tests demonstrate that the smoothness of the values exerts a decisive influence on the discriminant results. Kappa’s analysis shows that there is no significant equivalence between some of the categorical variables used in both databases. The use of these variables demand the application of clearly defined criteria. The cell size should match the dimensions of the phenomenon analyzed given the unsuitability of the grid of 45 m in this study.  相似文献   

4.
In recent years SAR interferometry has become a widely used technique for measuring altitude and displacement of the surface of the earth. Both these capabilities are highly relevant for landslide susceptibility studies. Although there are many problems that make the use of SAR interferometry less suitable for landslide inventory mapping, it’s use in landslide monitoring and in the generation of input maps for landslide susceptibility assessment looks very promising. The present work attempts to evaluate the usefulness and limitations of this technique based on a case study in the Swiss Alps. Input maps were generated from ERS repeat pass data using SAR interferometry. A land cover map has been generated by image classification of multi-temporal SAR intensity images. An InSAR DEM was generated and a number of maps were derived from it, such as slope-, aspect, altitude- and slope form classes. These maps were used to generate landslide and rockfall susceptibility maps, which give fairly well acceptable results. However, a comparison of the InSAR DEM with the conventional Swisstopo DEM, indicated significant errors in the absolute height and slope angles derived from InSAR, especially along the ridges and in the valleys. These errors are caused by low coherence mostly due to layover and shadow effects. Visual comparison of stereo images created from hillshading maps and corresponding DEMs demonstrate that a considerable amount of topographic details have been lost in the InSAR-derived DEM. It is concluded that InSAR derived input maps are not ideal for landslide susceptibility assessment, but could be used if more accurate data is lacking.  相似文献   

5.
Landslide susceptibility zonation mapping is a fundamental procedure for geo-disaster management in tropical and sub-tropical regions. Recently, various landslide susceptibility zonation models have been introduced in Nepal with diverse approaches of assessment. However, validation is still a problem. Additionally, the role of various predisposing causative parameters for landslide activity is still not well understood in the Nepal Himalaya. To address these issues of susceptibility zonation and landslide activity, about 4,000 km2 area of central Nepal was selected for regional-scale assessment of landslide activity and susceptibility zonation mapping. In total, 655 new landslides and 9,229 old landslides were identified with the study area with the help of satellite images, aerial photographs, field data and available reports. The old landslide inventory was “blind landslide database” and could not explain the particular rainfall event responsible for the particular landslide. But considering size of the landslide, blind landslide inventory was reclassified into two databases: short-duration high-intensity rainfall-induced landslide inventory and long-duration low-intensity rainfall-induced landslide inventory. These landslide inventory maps were considered as proxy maps of multiple rainfall event-based landslide inventories. Similarly, all 9,884 landslides were considered for the activity assessment of predisposing causative parameters. For the Nepal Himalaya, slope, slope aspect, geology and road construction activity (anthropogenic cause) were identified as most affective predisposing causative parameters for landslide activity. For susceptibility zonation, multivariate approach was considered and two proxy rainfall event-based landslide databases were used for the logistic regression modelling, while a relatively recent landslide database was used in validation. Two event-based susceptibility zonation maps were merged and rectified to prepare the final susceptibility zonation map and its prediction rate was found to be more than 82 %. From this work, it is concluded that rectification of susceptibility zonation map is very appropriate and reliable. The results of this research contribute to a significant improvement in landslide inventory preparation procedure, susceptibility zonation mapping approaches as well as role of various predisposing causative parameters for the landslide activity.  相似文献   

6.
《Engineering Geology》2007,89(1-2):47-66
This work describes the application of Logistic Regression (LR) to an assessment of susceptibility to mass movements in a 850 km2 study area mainly on the Ionian side of the Aspromonte Range, in southern Calabria.LR is a multivariate function that can be utilised, on the basis of a given set of variables, to calculate the probability that a particular phenomenon (for instance, a landslide) is present. In the present study the set of relevant variables includes: rock type, land use, elevation, slope angle, aspect, slope profile curvature down-slope and across-slope.The aim of this paper is to evaluate the LR performance when the procedure is based on the surveying of mass movements in part of the study area. The procedure adopted was GIS-based, with a 10 m DEM square-grid; for slope and curvature calculation, four adjacent cells were grouped to form a nine-point set for mathematical processing.The LR application consists of four steps: sampling, where all relevant characteristics in a part of the area (ca. 27% of the study zone) are assessed; variable parameterisation, where non-parametric variables are transformed into parametric (or semi-parametric) variables (on at least rank scale); model fitting, where regression coefficients are iteratively calculated in the sample area; model application, where the best-fit regression function is applied to the entire study area. This procedure was applied in two ways: first considering all types, then a single type of mass movement.The ground characteristics of the whole study zone were determined. The LR procedure was first tested by extending the sampling and reclassification steps to the whole study zone to find out the best possible fitting regression; the results of this were then compared with ground truth to maximise performance. Afterwards, the results of LR analysis, based on extension of regression formulas obtained also using 40% sampling zones, were compared with those of the best possible one and ground truth. Comparisons were performed by means of a confusion matrix and a simple correlation between expected vs. observed values for grouped variables. The overall results seem promising: for example, if the 27% sample areas are adopted, 94% of the cells where the probability of the existence of any kind of mass movements is between 85.5% and 95%, are actually affected by mass movements. Results are instead less good when attempting to distinguish between types of mass movement.  相似文献   

7.
A landslide susceptibility map is very important and necessary to efficiently prevent and mitigate the losses brought by natural hazard for a large area. For the purpose of landslide susceptibility analysis for the whole Xiangxi catchment (3,209 km2), Artificial Neural Network (ANN) analysis was applied as the main method. The whole catchment was divided into two parts: the training area and the implementation area. The backwater area (559 km2) of Xiangxi catchment was used as the training area for the ANN method. In the training area the correlations between the landslide distribution and its causative factors, which includes lithology, slope angle, slope curvature and river network, have been analyzed based on the geological map and digital elevation model (DEM). The back-propagation training algorithm in ANN was selected to train the sample data from the training area, which were composed of input data (causative factors) and target output data (landslide occurrence), in order to find the correlations between them. Based on these correlations and input data in the implementation area (causative factors), the network output data were obtained for the implementation area. In the end, a map of landslide susceptibility, which was established by network output data, was presented for Xiangxi catchment. ArcGIS was applied to extract and quantify input information from a DEM for susceptibility analysis and also to present the result visually. As a result, a landslide susceptibility map, in which 70 % of all landslides are rightly classified in the training area (backwater area), was created for Xiangxi catchment.  相似文献   

8.
In the international literature, although considerable amount of publications on the landslide susceptibility mapping exist, geomorphology as a conditioning factor is still used in limited number of studies. Considering this factor, the purpose of this article paper is to implement the geomorphologic parameters derived by reconstructed topography in landslide susceptibility mapping. According to the method employed in this study, terrain is generalized by the contours passed through the convex slopes of the valleys that were formed by fluvial erosion. Therefore, slope conditions before landsliding can be obtained. The reconstructed morphometric and geomorphologic units are taken into account as a conditioning parameter when assessing landslide susceptibility. Two different data, one of which is obtained from the reconstructed DEM, have been employed to produce two landslide susceptibility maps. The binary logistic regression is used to develop landslide susceptibility maps for the Melen Gorge in the Northwestern part of Turkey. Due to the high correct classification percentages and spatial effectiveness of the maps, the landslide susceptibility map comprised the reconstructed morphometric parameters exhibits a better performance than the other. Five different datasets are selected randomly to apply proper sampling strategy for training. As a consequence of the analyses, the most proper outcomes are obtained from the dataset of the reconstructed topographical parameters and geomorphologic units, and lithological variables that are implemented together. Correct classification percentage and root mean square error (RMSE) values of the validation dataset are calculated as 86.28% and 0.35, respectively. Prediction capacity of the different datasets reveal that the landslide susceptibility map obtained from the reconstructed parameters has a higher prediction capacity than the other. Moreover, the landslide susceptibility map obtained from the reconstructed parameters produces logical results.  相似文献   

9.
张传才  秦奋  张喜旺  王航  肖培青 《水文》2018,38(2):15-24
DEM分辨率对分布式水沙过程模拟具有重要影响,然而,产生影响的内部机制尚不明确。改进水沙物理模型CASC2D-SED的结构,将坡度由DEM在模型内部直接提取改为由模块单独计算,并将坡度设计为模型的独立输入参数,通过单独改变坡度参数来研究坡度对水沙模拟DEM尺度效应的影响。基于改进的CASC2D-SED模型,以内蒙古准格尔旗沙圪堵镇附近的一个小流域为研究对象,以无人机航测的1m分辨率DEM数据、野外实测与室内实验获得的土壤特性数据、土地利用数据和降雨数据为基础,采用3种水沙模拟方案进行多象元尺度的水沙过程模拟,进而探索水沙过程模拟的DEM尺度效应及发生机制。研究表明:⑴在4~20m GRID分辨率区间模拟的径流量位于323.18m3和411.43m3之间,波动不大;⑵2~20m GRID分辨率区间内,模拟的侵蚀流量在3.43m3和65.61m3间变化,波动很大;(3)坡度和径流路径是水文过程模拟DEM尺度效应的两个对立影响因子,是水文过程模拟DEM尺度效应不明显的主要原因;⑷DEM尺度效应对侵蚀输沙具有重要影响,地形坡度是侵蚀输沙DEM尺度效应的主要控制因子;⑸地形坡度随DEM分辨率降低而发生的空间上的波动变化是侵蚀输沙量随DEM分辨率降低而波动变化的原因。  相似文献   

10.
High-resolution digital elevation models are crucial to the investigation of natural disasters, and a variety of methods based on visualization and relief map compilations have been proposed. In this study, the sky view factor (SVF) is applied to slope maps and a digital elevation model (DEM) of the Oso landslide, a deadly landslide that occurred in Washington State on March 22, 2014, to demonstrate the effectiveness of SVF-enhanced relief maps in mapping and evaluating large-scale or deep-seated landslide hazards. A procedure for combining the SVF-enhanced DEM with slope and elevation maps is also presented. Then the maps are used to extract the landslide-prone areas and perform a reactivation analysis of the post-Oso landslide using an analytic hierarchy process (AHP). By using the SVF-enhanced DEM to perform the AHP assessment on multi-period images, we accurately evaluate hazard of the landslide for both pre and post-2014 conditions. Finally, different visualization maps, limitation and recommend parameters for generating SVF relief map are presented in the paper.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号