矿产预测中成矿信息的提取和强化

成矿信息的提取是矿产预测的重要手段,其方法的有效性直接影响到预测成果的可靠性。在成矿规律研究的基础上,有意识地干预模型的构成,突出与成矿有关的信息;抑制某些成矿意义不明显和属干扰的信息,有目的地使模型向反映成矿信息的方向逼近,提高模型与矿床实际赋存地质环境的吻合程度,均是成矿信息提取和强化的内涵。本文从研究实践中总结了先验约束模型和非先验约束模型的强化方法,在新疆阿勒泰地区的地质－找矿工作中已取得     

浅论军用土地统计计算机应用系统设计方法问题

本文在解放军土地管理局研制的“军用土地管理信息系统”的基础上,从系统设计和应用的角度出发,明确了系统应包括的基本功能,提出了改进和完善系统的方法。     

基于GIS城市洪水淹没模拟分析

城市洪水淹没范围动态模拟分析是城市防洪规划与防治决策的一个重要基础工作。本文主要研究洪水从翻堤口出发在地理空间蔓延、扩散、动态行进及确定淹没范围的数字模拟方法。为此,根据数学形态学及测地圆概念,研究设计了洪水扩散范围的“膨胀”模拟算法和淹没范围搜索算法,用于查询淹没通块中从翻堤处到任一点之间的淹没路径和ｔ时刻洪水扩散范围。     

Kriging with imprecise (fuzzy) variograms. I: Theory

Imprecise variogram parameters are modeled with fuzzy set theory. The fit of a variogram model to experimental variograms is often subjective. The accuracy of the fit is modeled with imprecise variogram parameters. Measurement data often are insufficient to create good experimental variograms. In this case, prior knowledge and experience can contribute to determination of the variogram model parameters. A methodology for kriging with imprecise variogram parameters is developed. Both kriged values and estimation variances are calculated as fuzzy numbers and characterized by their membership functions. Besides estimation variance, the membership functions are used to create another uncertainty measure. This measure depends on both homogeneity and configuration of the data.     

GIS技术支持下的招远市金矿区崩塌遥感调查

在总结前人研究成果的基础上,全面系统地分析了诱发招远市金矿区崩塌的自然和人为因数,然后运用遥感技术对金矿区遥感图像进行处理,提取诱发崩塌的条件因子,聘请有经验的专家对各项诱发因子进行诊断分析,以此作为判断条件,在G IS技术的支持下对诱发崩塌的条件因子进行空间分析,预测出招远金矿区发生崩塌的危害程度,为防治崩塌提供科学依据。预测结果表明,招远金矿区崩塌有进一步发展的可能,其中,高危险区有36820 m2,中易发区有50 610 m2,低易发区有67 200 m2,需要采取有效措施加以防治。     

基于GIS的山地林道网优化配置系统

应用系统选择永安元沙国有林业采育场的部分林班为示范,建立森林资源空间数据库.以ARC/INFO为开发平台,以山地林道网理论为指导,应用G IS技术、DBMS技术与数学规划集成技术,使用AML语言进行二次开发设计山地林道网优化配置系统,实现计算机辅助林道网配置,提高决策的科学性。     

A Decision Support System for the Evaluation of Eco-engineering Strategies for Slope Protection

A decision support system (DSS) has been developed to assist expert and non-expert users in the evaluation and selection of eco-engineering strategies for slope protection. This DSS combines a qualitative hazard assessment of erosion and mass movements with a detailed catalogue of eco-engineering strategies for slope protection of which the suitability is evaluated in relation to the data entered. The slope decision support system (SDSS) is a knowledge based DSS in which knowledge is stored in frames containing rules that can evaluate the available information for a project, stored as project specific information (PSI) in a data file. The advantages of such a system are that it accepts incomplete information and that the qualitative nature of the information does not instil the user with a sense of unjustified exactitude. By its multidisciplinary and progressive nature, the DSS will be of value during the initial stages of an eco-engineering project when data collection and the potential of different eco-engineering strategies are considered. The accent of the output of the DSS is on the application of eco-engineering strategies for slope protection as an environmentally-friendly solution aiding sustainable development. For its acceptance within the engineering community, the DSS needs to prove its predictive capacity. Therefore, its performance has been benchmarked against successful and unsuccessful cases of slope stabilisation using eco-engineering. The target audience and the areas of application of this DSS are reviewed and the strategies for further development in this area suggested.     

Groundwater study using remote sensing and geographic information systems (GIS) in the central highlands of Eritrea

Remote sensing, evaluation of digital elevation models (DEM), geographic information systems (GIS) and fieldwork techniques were combined to study the groundwater conditions in Eritrea. Remote sensing data were interpreted to produce lithological and lineament maps. DEM was used for lineament and geomorphologic mapping. Field studies permitted the study of structures and correlated them with lineament interpretations. Hydrogeological setting of springs and wells were investigated in the field, from well logs and pumping test data. All thematic layers were integrated and analysed in a GIS. Results show that groundwater occurrence is controlled by lithology, structures and landforms. Highest yields occur in basaltic rocks and are due to primary and secondary porosities. High yielding wells and springs are often related to large lineaments, lineament intersections and corresponding structural features. In metamorphic and igneous intrusive rocks with rugged landforms, groundwater occurs mainly in drainage channels with valley fill deposits. Zones of very good groundwater potential are characteristic for basaltic layers overlying lateritized crystalline rocks, flat topography with dense lineaments and structurally controlled drainage channels with valley fill deposits. The overall results demonstrate that the use of remote sensing and GIS provide potentially powerful tools to study groundwater resources and design a suitable exploration plan.The online version of the original article can be found at     

长江口水域多光谱遥感水深反演模型研究

利用Landsat-7 ETM 遥感影像反射率和实测水深值之间的相关性可以探测水深。该文介绍单波段、双波段比值和多波段3种线性回归模型以及动量BP人工神经网络水深反演模型。选择长江口北港河道上段作为研究区,利用上述模型,分两种情况进行水深反演:一是以河道全部历史样本建模;二是将河道按自然水深划分为浅水区和深水区分别建模。结果表明:神经网络模型预测精度高于线性回归模型;水深分区后线性回归和神经网络模型预测误差均有所减小。