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1.
This study is aimed at the evaluation of the hazard of soil erosion and its verification at Boun, Korea, using a Geographic Information System (GIS) and remote sensing. Precipitation, topographic, soil, and land use data were collected, processed, and constructed into a spatial database using GIS and remote sensing data. Areas that had suffered soil erosion were analysed and mapped using the Universal Soil Loss Equation (USLE). The factors that influence soil erosion are rainfall erosivitiy (R) from the precipitation database, soil erodibility (K) from the soil database, slope length and steepness (LS) from the topographic database, and crop and management (C) and conservation supporting practices (P) from the land use database. Land use was classified from Landsat Thematic Mapper satellite images. The soil erosion map verified use of the landslide location data. Landslide locations were identified in the Boun area from interpretation of aerial photographs and field surveys.  相似文献   

2.
This paper presents landslide hazard analysis at Cameron area, Malaysia, using a geographic information system (GIS) and remote sensing data. Landslide locations were identified from interpretation of aerial photographs and 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 are topographic slope, topographic aspect, topographic curvature, and distance to rivers, all from the topographic database; lithology and distance to faults were taken from the geologic database; land cover from TM satellite image; the vegetation index value was taken from Landsat images; and precipitation distribution from meteorological data. Landslide hazard area was analyzed and mapped using the landslide occurrence factors by frequency ratio and bivariate logistic regression models. The results of the analysis were verified using the landslide location data and compared with the probabilistic models. The validation results showed that the frequency ratio model (accuracy is 89.25%) is better in prediction of landslide than bivariate logistic regression (accuracy is 85.73%) model.  相似文献   

3.
The production of flood hazard assessment maps is an important component of flood risk assessment. This study analyses flood hazard using flood mark data. The chosen case study is the 2013 flood event in Quang Nam, Vietnam. The impacts of this event included 17 deaths, 230 injuries, 91,739 flooded properties, 11,530 ha of submerged and damaged agricultural land, 85,080 animals killed and widespread damage to roads, canals, dykes and embankments. The flood mark data include flood depth and flood duration. Analytic hierarchy process method is used to assess the criteria and sub-criteria of the flood hazard. The weights of criteria and sub-criteria are generated based on the judgements of decision-makers using this method. This assessment is combined into a single map using weighted linear combination, integrated with GIS to produce a flood hazard map. Previous research has usually not considered flood duration in flood hazard assessment maps. This factor has a rather strong influence on the livelihood of local communities in Quang Nam, with most agricultural land within the floodplain. A more comprehensive flood hazard assessment mapping process, with the additional consideration of flood duration, can make a significant contribution to flood risk management activities in Vietnam.  相似文献   

4.
This study shows the construction of a hazard map for presumptive ground subsidence around abandoned underground coal mines (AUCMs) at Samcheok City in Korea using an artificial neural network, with a geographic information system (GIS). To evaluate the factors governing ground subsidence, an image database was constructed from a topographical map, geological map, mining tunnel map, global positioning system (GPS) data, land use map, digital elevation model (DEM) data, and borehole data. An attribute database was also constructed by employing field investigations and reinforcement working reports for the existing ground subsidence areas at the study site. Seven major factors controlling ground subsidence were determined from the probability analysis of the existing ground subsidence area. Depth of drift from the mining tunnel map, DEM and slope gradient obtained from the topographical map, groundwater level and permeability from borehole data, geology and land use. These factors were employed by with artificial neural networks to analyze ground subsidence hazard. Each factor’s weight was determined by the back-propagation training method. Then the ground subsidence hazard indices were calculated using the trained back-propagation weights, and the ground subsidence hazard map was created by GIS. Ground subsidence locations were used to verify results of the ground subsidence hazard map and the verification results showed 96.06% accuracy. The verification results exhibited sufficient agreement between the presumptive hazard map and the existing data on ground subsidence area. An erratum to this article can be found at  相似文献   

5.
The main goal of this study is to produce landslide susceptibility maps of a landslide-prone area (Haraz) in Iran by using both fuzzy logic and analytical hierarchy process (AHP) models. At first, landslide locations were identified by aerial photographs and field surveys, and a total of 78 landslides were mapped from various sources. Then, the landslide inventory was randomly split into a training dataset 70?% (55 landslides) for training the models and the remaining 30?% (23 landslides) was used for validation purpose. Twelve data layers, as the landslide conditioning factors, are exploited to detect the most susceptible areas. These factors are slope degree, aspect, plan curvature, altitude, lithology, land use, distance from rivers, distance from roads, distance from faults, stream power index, slope length, and topographic wetness index. Subsequently, landslide susceptibility maps were produced using fuzzy logic and AHP models. For verification, receiver operating characteristics curve and area under the curve approaches were used. The verification results showed that the fuzzy logic model (89.7?%) performed better than AHP (81.1?%) model for the study area. The produced susceptibility maps can be used for general land use planning and hazard mitigation purpose.  相似文献   

6.
Tsunamis are among the most destructive and lethal of coastal hazards. These are time-specific events, and despite directly affecting a narrow strip of coastline, a single occurrence can have devastating effects and cause massive loss of life, especially in urbanized coastal areas. In this work, in order to consider the time dependence of population exposure to tsunami threat, the variation of spatio-temporal population distribution in the daily cycle is mapped and analyzed in the Lisbon Metropolitan Area. High-resolution daytime and nighttime population distribution maps are developed using ‘intelligent dasymetric mapping,’ that is, applying areal interpolation to combine best-available census data and statistics with land use and land cover data. Workplace information and mobility statistics are considered for mapping daytime distribution. In combination with a tsunami hazard map, information on infrastructure, land use and terrain slope, the modeled population distribution is used to assess people’s evacuation speed, applying a geospatial evacuation modeling approach to the city of Lisbon. The detailed dynamic population exposure assessment allows producing both daytime and nighttime evacuation time maps, which provide valuable input for evacuation planning and management. Results show that a significant amount of population is at risk, and its numbers increase dramatically from nighttime to daytime, especially in the zones of high tsunami flooding susceptibility. Also, full evacuation can be problematic in the daytime period, even if initiated immediately after a major tsunami-triggering earthquake. The presented approach greatly improves tsunami risk assessment and can benefit all phases of the disaster management process.  相似文献   

7.
Landslide susceptibility maps are vital for disaster management and for planning development activities in the mountainous country like Nepal. In the present study, landslide susceptibility assessment of Mugling?CNarayanghat road and its surrounding area is made using bivariate (certainty factor and index of entropy) and multivariate (logistic regression) models. At first, a landslide inventory map was prepared using earlier reports and aerial photographs as well as by carrying out field survey. As a result, 321 landslides were mapped and out of which 241 (75?%) were randomly selected for building landslide susceptibility models, while the remaining 80 (25?%) were used for validating the models. The effectiveness of landslide susceptibility assessment using GIS and statistics is based on appropriate selection of the factors which play a dominant role in slope stability. In this case study, the following landslide conditioning factors were evaluated: slope gradient; slope aspect; altitude; plan curvature; lithology; land use; distance from faults, rivers and roads; topographic wetness index; stream power index; and sediment transport index. These factors were prepared from topographic map, drainage map, road map, and the geological map. Finally, the validation of landslide susceptibility map was carried out using receiver operating characteristic (ROC) curves. The ROC plot estimation results showed that the susceptibility map using index of entropy model with AUC value of 0.9016 has highest prediction accuracy of 90.16?%. Similarly, the susceptibility maps produced using logistic regression model and certainty factor model showed 86.29 and 83.57?% of prediction accuracy, respectively. Furthermore, the ROC plot showed that the success rate of all the three models performed more than 80?% accuracy (i.e. 89.15?% for IOE model, 89.10?% for LR model and 87.21?% for CF model). Hence, it is concluded that all the models employed in this study showed reasonably good accuracy in predicting the landslide susceptibility of Mugling?CNarayanghat road section. These landslide susceptibility maps can be used for preliminary land use planning and hazard mitigation purpose.  相似文献   

8.
The main objective of this study is to assess the land degradation risk of cultivated land in El Fayoum depression. The physiographic map of the depression was produced by using remote sensing and land surveying data. The depression comprises lacustrine plain, alluvial–lacustrine plain, and alluvial plain representing 12.22%, 53.58%, and 34.20% of the total area, respectively. The soil, climate, and topographic characteristics of the depression were extracted from land surveying, laboratory analyses, digital elevation model, and available reports. A simple model was designed to employ these data for assessing the chemical and physical risk of land degradation using Arc-GIS 9.2 software. The obtained results indicate that severe risk to chemical and physical degradation affect 54.15% and 29.23% of the depression, respectively. The current status of soil salinity, sodicity, and water table indicate that most of lacustrine and alluvial–lacustrine soils are actually degraded by salinization, sodification, and waterlogging. The results of degradation risk and the actual hazard indicate that the human activities are not sufficient to overcome the degradation processes in the most of the depression (80. 22%). Moreover, a negative human impact affects 26.29% of the area mostly in the alluvial plain. Great efforts related to the land management are required to achieve the agriculture sustainability.  相似文献   

9.
Landslide hazard, vulnerability, and risk-zoning maps are considered in the decision-making process that involves land use/land cover (LULC) planning in disaster-prone areas. The accuracy of these analyses is directly related to the quality of spatial data needed and methods employed to obtain such data. In this study, we produced a landslide inventory map that depicts 164 landslide locations using high-resolution airborne laser scanning data. The landslide inventory data were randomly divided into a training dataset: 70 % for training the models and 30 % for validation. In the initial step, a susceptibility map was developed using logistic regression approach in which weights were assigned to every conditioning factor. A high-resolution airborne laser scanning data (LiDAR) was used to derive the landslide conditioning factors for the spatial prediction of landslide hazard areas. The resultant susceptibility was validated using the area under the curve method. The validation result showed 86.22 and 84.87 % success and prediction rates, respectively. In the second stage, a landslide hazard map was produced using precipitation data for 15 years. The precipitation maps were subsequently prepared and show two main categories (two temporal probabilities) for the study area (the average for any day in a year and abnormal intensity recorded in any day for 15 years) and three return periods (15-, 10-, and 5-year periods). Hazard assessment was performed for the entire study area. In the third step, an element at risk map was prepared using LULC, which was considered in the vulnerability assessment. A vulnerability map was derived according to the following criteria: cost, time required for reconstruction, relative risk of landslide, risk to population, and general effect to certain damage. These criteria were applied only on the LULC of the study area because of lack of data on the population and building footprint and types. Finally, risk maps were produced using the derived vulnerability and hazard information. Thereafter, a risk analysis was conducted. The LULC map was cross-matched with the results of the hazard maps for the return period, and the losses were aggregated for the LULC. Then, the losses were calculated for the three return periods. The map of the risk areas may assist planners in overall landslide hazard management.  相似文献   

10.
Rapid land use change has taken place in many arid and semi-arid regions of China including the Loess Plateau. In this study, changes in land use and landscape fragmentation in the small Shanghuang watershed on the Loess Plateau were investigated by the combined use of remote sensing, GIS and landscape metrics. Land use classes were mapped and analyzed from a time series of maps and remotely sensed images that were ground truthed in 2008. Analyses of the data showed that land use had undergone substantial changes in this small watershed from 1982 to 2008, and these changes could be divided into three phases according to the change in the landscape matrix whereby the dominant land use was grassland (1982–1990), cropland (1990–2002) and forestland (2002–2008). During each phase, conversions between different land use types took place frequently, especially among cropland, orchards, grassland and forestland. Landscape fragmentation increased from 1982 to 1990 and then decreased from 1990 to 2008 as indicated by four landscape metrics. These changes in land use and landscape fragmentation in this small watershed were mainly controlled by human factors (land management, construction, population pressure, and government policy) rather than natural factors.  相似文献   

11.
武水河上游区域土壤重金属污染风险及来源分析   总被引：1，自引：0，他引：1  
生态功能区在涵养水源、保持水土、维系生物多样性等方面具有重要的作用。本文以位于南岭生态功能区的流域——武水流域为研究对象,采集流域上游交通运输用地、采矿用地、工业用地、耕地及林地5种土地利用类型土壤样品,分析7种重金属Cd、As、Cu、Hg、Ni、Pb、Zn的含量特征,采用内梅罗综合污染指数评价重金属污染的程度,Hakanson潜在生态风险指数法评价土壤重金属潜在生态风险,并应用主成分分析法探究重金属污染的来源。研究结果显示,武水河上游地区土壤重金属Cd、As、Cu、Hg、Ni、Pb、Zn平均含量分别为1.28、72.44、54.62、0.27、68.32、72.29和158.42mg/kg,均高于土壤背景值,其中采矿用地土壤重金含量除Hg外均高于其他类型土壤。均值状态下土壤中Cd和As单因子污染指数分别为5.07、3.25,其中采矿用地中Cd单因子污染指数可达13.59;土壤重金属综合污染指数表明,采矿用地污染最为严重,其次是工业用地,林地呈安全状态。潜在生态危害指数评价结果显示,采矿用地和工业用地达到了强生态危害,其他类型土壤为轻微生态危害,而采矿用地土壤中Cd达到极强生态危害,As为强生态危害。土壤重金属来源研究结果表明,As、Cd、Cu和Zn来源于矿山开采及工业活动,Ni和Hg主要来源于成土母质,Pb则来源于交通运输。研究认为:武水流域上游区土壤重金属污染情况较为严重,Cd和As是区内主要的风险因子,主要来源于矿山开采以及工业活动。  相似文献   

12.
Landslide hazard in a region limited to data from a regional scale about triggering factors is assessed via cross tabulation between determining factors and landslides with recent activity. Firstly, landslide susceptibility was evaluated and validated through a bivariate statistical method between the previously identified stability conditioning factors and the mapped landslides. In this way, the most susceptible areas for assessing landslide hazards were selected. The main problem to solve in this type of research is the landslide activity. For this purpose, several techniques were applied: news reports, differential interferometric synthetic aperture radar, digital photogrammetry, light detection and ranging, photointerpretation, and dendrochronology. Both the strong and weak points of these techniques are also mentioned. The landslide return period was computed via the association between landslide activity and triggering factors, in this case annual rainfall. Finally, landslide hazard was mapped solely based on landslides with recent activity and their computed return period. The relationship between landslide occurrence and triggering factors shows that, according to both the considered assumptions and the observations made, deep-seated landslides are triggered or reactivated together with superficial landslides once every 18 years, while superficial landslides as flows or falls occur once every 5 years. The results show that there is generally a low landslide hazard in the study zone, especially when compared to landslide susceptibility. This means that landslides are mainly dormant from a natural evolution point of view, but could be reactivated as a result of geomorphological, climate, or human changes. In any case, the landslide hazard is successfully assessed, with a prediction of a 6% annual probability of a high hazard in 5% of the area, intersecting with the main infrastructures of the region; thus, control strategies are justified in order to avoid damage in extraordinary rainfall periods.  相似文献   

13.
We present the methodologies adopted and the outcomes obtained in the analysis of landslide risk in the basin of the Arno River (Central Italy) in the framework of a project sponsored by the Basin Authority of the Arno River, started in the year 2002 and completed at the beginning of 2005. In particular, a complete set of methods and applications for the assessment of landslide susceptibility and risk are described and discussed. A new landslide inventory of the whole area was realized, using conventional (aerial-photo interpretation and field surveys) and non-conventional methods (e.g. remote sensing techniques such as DInSAR and PS-InSAR). The great majority of the mapped mass movements are rotational slides (75%), solifluctions and other shallow slow movements (17%) and flows (5%), while soil slips, and other rapid landslides, seem less frequent everywhere within the basin. The relationships between landslide characteristics and environmental factors have been assessed through statistical analysis. As expected, the results show a strong control of land cover, lithology and morphology on landslide occurrence. The landslide frequency-size distribution shows a typical scaling behaviour already underlined in other landslide inventories worldwide. The assessment of landslide hazard in terms of probability of occurrence in a given time, based for mapped landslides on direct and indirect observations of the state of activity and recurrence time, has been extended to landslide-free areas through the application of statistical methods implemented in an artificial neural network (ANN). Unique conditions units (UCU) were defined by the map overlay of landslide preparatory factors (lithology, land cover, slope gradient, slope curvature and upslope contributing area) and afterwards used to construct a series of model vectors for the training and test of the ANN. Various different ANNs were selected throughout the basin, until each UCU was assigned a degree of membership to a susceptibility and a hazard class. Model validation confirms that prediction results are very good, with an average percentage of correctly recognized mass movements of about 85%. The analysis also revealed the existence of a large number of unmapped mass movements, thus contributing to the completeness of the final inventory. Temporal hazard was estimated via the translation of state of activity in recurrence time and hence probability of occurrence. The following intersection of hazard values with vulnerability and exposure figures, obtained by reclassification of digital vector mapping at 1:10,000 scale, lead to the definition of risk values for each terrain unit for different periods of time into the future. The final results of the research are now undergoing a process of integration and implementation within land planning and risk prevention policies and practices at local and national level.  相似文献   

14.
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   

15.
于军  武健强 《江苏地质》2008,32(2):113-117
平原区超采地下水引发的地面沉降地质灾害已成为影响这些地区经济可持续发展的重要制约因素,如何从收益、成本、风险三个方面为决策者提供制定地面沉降相关防治措施的综合支持,实现灾害防治从被动应对向主动防御转变,是地面沉降防治研究领域的新课题。在综合考虑苏锡常地区技术、经济、人类活动等因素基础上,从地面沉降总体风险和地区差异水平出发,提出构建地面沉降风险评价模型及决策支持系统的初步研究思路和方法,为实现地面沉降防治的科学化决策管理进行了探索。  相似文献   

16.
The frequency in occurrence and severity of floods has increased globally. However, many regions around the globe, especially in developing countries, lack the necessary field monitoring data to characterize flood hazard risk. This paper puts forward methodology for developing flood hazard maps that define flood hazard risk, using a remote sensing and GIS-based flood hazard index (FHI), for the Nyamwamba watershed in western Uganda. The FHI was compiled using analytical hierarchy process and considered slope, flow accumulation, drainage network density, distance from drainage channel, geology, land use/cover and rainfall intensity as the flood causative factors. These factors were derived from Landsat, SRTM and PERSIANN remote sensing data products, except for geology that requires field data. The resultant composite FHI yielded a flood hazard map pointing out that over 11 and 18% of the study area was very highly and highly susceptible to flooding, respectively, while the remaining area ranged from medium to very low risk. The resulting flood hazard map was further verified using inundation area of a historical flood event in the study area. The proposed methodology was effective in producing a flood hazard map at the watershed local scale, in a data-scarce region, useful in devising flood mitigation measures.  相似文献   

17.
A. Wezel  S. Bender 《GeoJournal》2002,57(4):241-249
In the Alexander von Humboldt National Park in eastern Cuba many endemic animals and plants are found in various different natural habitats, which are considered to be the most important ones for in-situ conservation in the entire Insular Caribbean. In some areas of the National Park agriculture is practised. Thus, the objective of this study was to document and analyse the different land use activities and their consequences for local resource management and conservation of biodiversity in two village areas. A particular question was: what has changed since the foundation of the National Park in 1996? As time series data for land use and aerial photographs were not available for this part of Cuba, a qualitative evaluation was carried out. For this, six different land use units were mapped in 2001 and additional information gathered for areas with special interest related to sustainable land use and resource conservation. Although most parts of the study area are influenced to various degrees by human impact, the different types of land use seem presently not to have a crucial or detrimental impact on the land resources of the Alexander von Humboldt National Park. However, exploitation of the natural resources in certain areas could be improved with different management options to reach sustainability as well as to meet the conservation objectives of the National Park. This includes reduced or abandoned agricultural use of steep slopes to reduce erosion risk as well as a facilitated regeneration of natural vegetation in many parts of the study area to be able to conserve the high valuable biodiversity of the Park. Environmental education seems to have played an important and successful role since the foundation of the Park in 1996. Since then, cropping on steep slopes as well as illegal logging and poaching could be reduced.  相似文献   

18.
This article examines the effects of watershed urbanization on stream flood behavior in the Los Angeles metropolitan region. Stream gauge data, spatially distributed rainfall data, land use/land cover, and census population data were used to quantify change in flood behavior and urbanization in multiple watersheds. Increase in flood discharge started at the very early stage of the urbanization when the population density was relatively low but the rate of increase of flood discharge varied across watersheds depending on the distribution of the imperviousness surface and flood mitigation practices. This spatial variability in rainfall–runoff indices and the increasing flood risk across the metropolitan region has posed a challenge to the conventional flood emergency management, which usually responds to flood damages rather than being concerned with the broader issues of land use, land cover, and planning. This study pointed out that alternative land use planning and flood management practices could be mitigating the urban flood implemented hazard.  相似文献   

19.
This study constructs a hazard map for ground subsidence around abandoned underground coal mines (AUCMs) at Samcheok City in Korea using a probability (frequency ratio) model, a statistical (logistic regression) model, and a Geographic Information System (GIS). To evaluate the factors related to ground subsidence, an image database was constructed from a topographical map, geological map, mining tunnel map, Global Positioning System (GPS) data, land use map, lineaments, digital elevation model (DEM) data, and borehole data. An attribute database was also constructed from field investigations and reports on the existing ground subsidence areas at the study site. Nine major factors causing ground subsidence were extracted from the probability analysis of the existing ground subsidence area: (1) depth of drift; (2) DEM and slope gradient; (3) groundwater level, permeability, and rock mass rating (RMR); (4) lineaments and geology; and (5) land use. The frequency ratio and logistic regression models were applied to determine each factor’s rating, and the ratings were overlain for ground subsidence hazard mapping. The ground subsidence hazard map was then verified and compared with existing subsidence areas. The verification results showed that the logistic regression model (accuracy of 95.01%) is better in prediction than the frequency ratio model (accuracy of 93.29%). The verification results showed sufficient agreement between the hazard map and the existing data on ground subsidence area. Analysis of ground subsidence with the frequency ratio and logistic regression models suggests that quantitative analysis of ground subsidence near AUCMs is possible.  相似文献   

20.
用光学遥感数据和地理信息系统(GIS)分析了马来西亚Selangor地区的滑坡灾害。通过遥感图像解译和野外调查,在研究区内确定出滑坡发生区。通过GIS和图像处理,建立了一个集地形、地质和遥感图像等多种信息的空间数据库。滑坡发生的因素主要为:地形坡度、地形方位、地形曲率及与排水设备距离;岩性及与线性构造距离;TM图像解译得到的植被覆盖情况;Landsat图像解译得到的植被指数;降水量。通过建立人工神经网络模型对这些因素进行分析后得到滑坡灾害图:由反向传播训练方法确定每个因素的权重值,然后用该权重值计算出滑坡灾害指数,最后用GIS工具生成滑坡灾害图。用遥感解译和野外观测确定出的滑坡位置资料验证了滑坡灾害图,准确率为82.92%。结果表明推测的滑坡灾害图与滑坡实际发生区域足够吻合。  相似文献   

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