MAPGIS管网开发平台的设计

设计了一个通用的管线信息系统开发平台。该开发平台构筑于大型GIS基础软件MAPGIS之上，具有完备的数据模型，强大的数据包容能力。采用多层次体系结构，包含网络数据管理与网络分析、管网工作区管理、专业管网工作区管理、管网工程管理、管网实用服务工具包、管网管理类库和控件库等多个模块。该开发平台同时支持API和组件接口，二次开发便利灵活，可以较好地满足管网应用系统的。在该平台基础上已开发出多个成功的管网信息系统，证明它具有广泛的应用前景。     

GIS支持下青海湖地区草地蝗虫发生的地形分析

草地蝗虫发生的地形分析是建立草地蝗虫发生预报模型的基础，以青海湖地区为实验区，在Arc/Info和ArcView地理信息系统的支持下，进行草地蝗虫发生与各地形变量（包括海拔高度、坡度与坡向）的叠置分析，提取草地蝗虫发生的地形信息数据库，然后，分别采用T－检验（对连续变量－海拔高度和坡度）和卡方（Chisquare)检验（对类变量－坡向类型）进行各地形变量对草地蝗虫发生的差异显著性检验，结果表明，海拔高度和坡度对草地蝗虫发生的影响极为显著（显著性水平p=0.000)，而坡向地草地蝗虫发生的影响不是特别明显（显著性水平p=0.039)。     

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.     

Use of Fuzzy Membership Input Layers to Combine Subjective Geological Knowledge and Empirical Data in a Neural Network Method for Mineral-Potential Mapping

Use of GIS layers, in which the cell values represent fuzzy membership variables, is an effective method of combining subjective geological knowledge with empirical data in a neural network approach to mineral-prospectivity mapping. In this study, multilayer perceptron (MLP), neural networks are used to combine up to 17 regional exploration variables to predict the potential for orogenic gold deposits in the form of prospectivity maps in the Archean Kalgoorlie Terrane of Western Australia. Two types of fuzzy membership layers are used. In the first type of layer, the statistical relationships between known gold deposits and variables in the GIS thematic layer are used to determine fuzzy membership values. For example, GIS layers depicting solid geology and rock-type combinations of categorical data at the nearest lithological boundary for each cell are converted to fuzzy membership layers representing favorable lithologies and favorable lithological boundaries, respectively. This type of fuzzy-membership input is a useful alternative to the 1-of-N coding used for categorical inputs, particularly if there are a large number of classes. Rheological contrast at lithological boundaries is modeled using a second type of fuzzy membership layer, in which the assignment of fuzzy membership value, although based on geological field data, is subjective. The methods used here could be applied to a large range of subjective data (e.g., favorability of tectonic environment, host stratigraphy, or reactivation along major faults) currently used in regional exploration programs, but which normally would not be included as inputs in an empirical neural network approach.     

The rate of grain release by pore-ice sublimation in cold-aeolian environments

Pore‐ice sublimation is a prerequisite for aeolian activity in cold environments where surface sediments hold significant amounts of frozen water. Few quantitative studies have defined the rate of grain release from cemented surfaces by pore‐ice sublimation. In 1996–1997, controlled field experiments at Presqu'ile Beach, Ontario, were implemented to measure sediment release from frozen surfaces. The release rates were compared to the local wind regime, ambient temperature and humidity. In additional field experiments, the effect of sediment water content on grain release by sublimation was examined. From the experimental results, an equation which predicts grain release based on local wind speed, ground temperature, humidity, and surface water content is proposed. Predicted release rates show reasonable agreement with natural deflation measured on the beach at Presqu'ile Provincial Park.     

Seismic risk assessments and GIS technology: applications to infrastructures in the Friuli–Venezia Giulia region (NE Italy)

This paper illustrates the seismic risk preliminary estimates of two different groups of structures located on the territory of the Friuli–Venezia Giulia region (NE Italy) : the first group includes some special industrial plants, and the second group includes bridges and tunnels belonging to the regional highway network. The part of the study on special industrial plants tries to evaluate the degree of expected damage, taking into account their structural typology and ground shaking expressed in terms of macroseismic intensity. The second part of the study is an application of the HAZUS methodology to the tunnels and bridges of a highway network: the combination of expected ground shaking and the construction characteristics lead to very different risk levels, especially when considering the bridges. The resulting damage levels to bridges and tunnels are still only indicative because of the fragility curves used in the evaluations: they were developed for existing bridge and tunnel structural typologies in the U.S.A. Moreover, both examples show the power of GIS technology in storing, elaborating, and mapping spatial data. Copyright © 2003 John Wiley & Sons, Ltd.     

地下水及溶质运移数值模拟系统

介绍了地下水及溶质运移数值模拟的研究进展、数值模型的分类和数值模拟的步骤。根据数值模拟中涉及到的地质信息资源的特点，提出了基于地理信息系统(GIS)技术的地下水及溶质运移数值模拟系统的设计思路。该系统能够对模拟区域的基础地质资料、水文地质勘探资料以及数值模型的输入、输出资料进行动态管理，而且随着勘探、科研和生产的不断进行，通过对数据库的及时更新以及对数值模型的不断校正，可为不同的科研和生产方案的预测与评价提供信息资源。     

分形学:现代地图学的非线性数学分析方法

分析了地图学的传统数学分析方法，讨论了对象复杂性与方法简单化的矛盾，阐述了分形几何学，为现代地图学研究的定量化、系统化提供了新的数学分析方法。     

基于MapXtreme的地理信息发布

随着近年来计算机技术的发展,尤其是网络技术的发展,GIS在组成结构和应用技术等方面已与传统的GIS技术有了很大的不同,基于MapXtreme/MapX的WebGIS则是GIS技术发展的趋势。本文简单介绍WebGIS的发展趋势,结合一些例子介绍了利用MapXtreme的地理信息发布的技术和原理。     

基于移动Agent的分布式地理信息查询

提出了基于移动Agent的分布式地理信息查询的新思路，给出了构建基于移动Agent的分布式地理信息查询系统的方法，并利用移动Agent开发平台Aglets开发了一个分布式地理信息查询原型系统，实现了分布式地理信息的透明访问。