A multi-method approach to study the stability of natural slopes and landslide susceptibility mapping

In this paper, a multi-method approach for the assessment of the stability of natural slopes and landslide hazard mapping applied to the Dakar coastal region is presented. This approach is based on the effective combination of geotechnical field and laboratory works, of GIS, and of mechanical (deterministic and numerical) stability analysis. By using this approach, valuable results were gained regarding instability factors, landslide kinematics, simulation of slope failure and coastal erosion. This led to a thorough assessment and strong reduction in the subjectivity of the slope stability and hazard assessment and to the development of an objective landslide danger map of the SW coast of Dakar. Analysis of the results shows that the slides were influenced by the geotechnical properties of the soil, the weathering, the hydrogeological situation, and the erosion by waves. The landslide susceptibility assessment based on this methodological approach has allowed for an appropriate and adequate consideration of the multiple factors affecting the stability and the optimization of planning and investment for land development in the city.     

Assessment of sand encroachment in Kuwait using GIS

Assessment of sand encroachment in Kuwait using Geographical Information System (GIS) technology has been formulated as a Multi-Criteria Decision Making problem. The Delphi method and Analytical Hierarchy Process were adopted as evaluating techniques, in which experts’ judgments were analyzed for objectively estimating and weighting control factors. Seven triggering factors, depicted in the form of maps, were identified and ordered according to their priority. These factors are (1) wind energy; (2) surface sediment; (3) vegetation density; (4) land use; (5) drainage density; (6) topographic change and (7) vegetation type. The factor maps were digitized, converted to raster data and overlaid to determine their possible spatial relationships. Applying a susceptibility model, a map of sand encroachment susceptibility in Kuwait was developed. The map showed that the areas of very high and high sand encroachment susceptibility are located within the main corridor of sand pathway that coincides with the northwesterly dominant wind direction.     

Decision-support systems for groundwater protection: innovative tools for resource management

Governmental authorities are forced by law to make decisions within the framework of European, national and regional directives in the fields of spatial planning, groundwater and environmental protection. These tasks can be supported by a decision-support system, which integrates data from various sources and helps to make decision processes more effective and transparent. Basic work for such a decision support system has been done in a transnational and interdisciplinary project (Interreg II C: KATER), including metadata definition, metadata system, cartographic tools and GIS tools. The direct integration of these tools and information in the decision process will be implemented in the next few years (project KATER II).     

滨里海盆地东缘阿克纠宾地区遥感地质及地球物理场研究

 以图像处理、GIS为平台，对哈萨克斯坦阿克纠宾地区的重、磁、电、遥感及地震资料进行了综合分析。指出，该地区重、磁力资料信息含量较高，对于确定盐下构造分布具有积极意义。使用遥感资料对小断层及裂隙发育状况进行研究，有助于裂隙孔隙型碳酸盐岩油藏开发注水效率的提高。同时可对扎纳若尔、阿里别克莫拉等油田的井网状况进行监控和地面设施进行调查。     

城市震害高危害小区的研究和GIS的实现技术

论述了在城市地震灾害中如何考虑诸方面因素来评价城市的灾害轻重分布情况。中建立坑危害小区分析模型，设想将城市划分等面积网格，给每个单元网格赋予灾害指数，以确定城市中受灾较为严重的区域，为求灾指挥提供决策信息。同时，将高危害小区的模型研究结果转化为计算机技术可以实现的GIS模型。该研究结果已应用于泰安市防震减灾示范研究项目中。     

Evaluating Earthquake-Triggered Landslide Hazard at the Basin Scale Through Gis in the Upper Sele River Valley

To evaluate techniques for assessing earthquake-triggeredlandslide hazard in the Southern Apennines (Italy), a GIS-based analysis was used to modelseismically induced slope deformations. Geological, geotechnical, geomorphological and seismologicaldata were integrated into a standard earthquake slope stability model. The model assessed thelandslide potential that existed during the 1980 Irpinian earthquake in the Upper Sele river Valley.The standard Newmark displacement analysis, widely used for predicting the location of shallowunstable slopes, does not take into account errors and/or uncertainties in the input parameters.Therefore, a probabilistic Newmark displacement analysis technique has been used. Probabilistictechniques allow, e.g., an estimation of the probability that a slope will exceed a certain criticalvalue of Newmark displacement. In our probabilistic method, a Monte-Carlo based simulation modelis used in conjunction with a GIS. The random variability of geotechnical data is modelled by probabilitydensity functions (pdfs), while for the seismic input three different regression laws wereconsidered. Input probability distributions are sampled and the resulting values input into empiricalrelations for estimating Newmark displacement. The outcome is a map in which to each siteis related a spatial probability distribution for the expected displacement in response to seismic loading.Results of the experiments show a high grade of uncertainty in the application of the Newmarkanalysis both for the deterministic and probabilistic approach in a complex geological setting suchas the high Sele valley, quite common in the Southern Apennines. They show a strong dependence onthe reliability of the spatial data used in input, so that, when the model is used at basin scale,results are strongly influenced by local environmental condition (e.g., topography, lithology, groundwatercondition) and decrease the model performance.     

基于GIS的滑坡CF多元回归模型及其应用

目前基于GIS滑坡变形失稳危险性评价方法均有各自的局限性。本文在基于数据的数学统计模型的基础上提出CF多元回归模型。通过将滑坡确定性稳定系数与回归模型的融合，在一定程度以解决了滑坡评价过程中影响因子的选择和量化的问题，有利于建立准确的滑坡分析模型。最后，将模型应用于云南小江流域，进行了该区的滑坡空间分布及稳定性分析。     

Use of Noise to Augment Training Data: A Neural Network Method of Mineral–Potential Mapping in Regions of Limited Known Deposit Examples

One of the main factors that affects the performance of MLP neural networks trained using the backpropagation algorithm in mineral-potential mapping isthe paucity of deposit relative to barren training patterns. To overcome this problem, random noise is added to the original training patterns in order to create additional synthetic deposit training data. Experiments on the effect of the number of deposits available for training in the Kalgoorlie Terrane orogenic gold province show that both the classification performance of a trained network and the quality of the resultant prospectivity map increasesignificantly with increased numbers of deposit patterns. Experiments are conducted to determine the optimum amount of noise using both uniform and normally distributed random noise. Through the addition of noise to the original deposit training data, the number of deposit training patterns is increased from approximately 50 to 1000. The percentage of correct classifications significantly improves for the independent test set as well as for deposit patterns in the test set. For example, using ±40% uniform random noise, the test-set classification performance increases from 67.9% and 68.0% to 72.8% and 77.1% (for test-set overall and test-set deposit patterns, respectively). Indices for the quality of the resultant prospectivity map, (i.e. D/A, D × (D/A), where D is the percentage of deposits and A is the percentage of the total area for the highest prospectivity map-class, and area under an ROC curve) also increase from 8.2, 105, 0.79 to 17.9, 226, 0.87, respectively. Increasing the size of the training-stop data set results in a further increase in classification performance to 73.5%, 77.4%, 14.7, 296, 0.87 for test-set overall and test-set deposit patterns, D/A, D × (D/A), and area under the ROC curve, respectively.     

GIS专题数据综合的研究

随着GIS技术在各种应用领域的推广使用，各领域的专业数据与G1S的空间数据相结合，形成描述特定地理现象的各种专题数据。与GIS空间数据一样，专题数据的应用也由微观的、较为详细地描述小区域地理现象特征，转向宏观的、较为概略地描述较大范围地理现象特征，这是专题数据综合的主要任务。该文在讨论GIS专题数据类型及特征的基础上，着重分析了专题数据综合的基本类型，并提出了专题数据综合的概念模型，为GIS专题数据自动综合的实施提供理论依据和实施方案。