面向对象的多媒体空间数据库系统设计

给出了一个多媒体空间数据模型,采用面向对象的技术将多媒体数据与空间数据有机地集成一体,具有数据管理方便和数据操作高效的特点,并给出了基于模型的系统的实现过程     

基于GIS的零售商业网点选址评价模型研究

传统零售商业网点选址模型主要是基于统计的静态模型。分析了影响零售商业网点选址的人口、经济、市场竞争三个关键要素,结合GIS,提出了一种基于权重设置的零售商业网点选址评价模型,并阐述了模型的应用流程。该模型在深圳市罗湖区公共信息服务平台中进行了典型应用实现,并检验了模型的应用可行性。     

A comparision of interpolation methods for producing digital elevation models at the field scale

Digital elevation models have been used in many applications since they came into use in the late 1950s. It is an essential tool for applications that are concerned with the Earth's surface such as hydrology, geology, cartography, geomorphology, engineering applications, landscape architecture and so on. However, there are some differences in assessing the accuracy of digital elevation models for specific applications. Different applications require different levels of accuracy from digital elevation models. In this study, the magnitudes and spatial patterning of elevation errors were therefore examined, using different interpolation methods. Measurements were performed with theodolite and levelling. Previous research has demonstrated the effects of interpolation methods and the nature of errors in digital elevation models obtained with indirect survey methods for small‐scale areas. The purpose of this study was therefore to investigate the size and spatial patterning of errors in digital elevation models obtained with direct survey methods for large‐scale areas, comparing Inverse Distance Weighting, Radial Basis Functions and Kriging interpolation methods to generate digital elevation models. The study is important because it shows how the accuracy of the digital elevation model is related to data density and the interpolation algorithm used. Cross validation, split‐sample and jack‐knifing validation methods were used to evaluate the errors. Global and local spatial auto‐correlation indices were then used to examine the error clustering. Finally, slope and curvature parameters of the area were modelled depending on the error residuals using ordinary least regression analyses. In this case, the best results were obtained using the thin plate spline algorithm. Copyright © 2009 John Wiley & Sons, Ltd.     

点分布-双蛇模型用于矢量边界更新

在利用遥感影像更新GIS矢量数据的过程中,往往忽略了对已知信息的有效利用,针对这一问题,本文提出一种基于点分布的双蛇模型用于GIS矢量数据更新,该模型利用已有遥感影像信息计算目标边界点的平均分布,以此为"镜面"建立初始矢量边界的"镜像",将两边界各自演化的结果取平均作为更新后的GIS矢量边界。该方法同时利用了GIS和遥感的历史数据作为先验知识,分别作为蛇模型的初始位置和区域约束信息,使遥感与GIS信息结合更加紧密。仿真实验表明,基于点分布的双蛇模型在GIS矢量边界更新的应用中,可以得到比以传统蛇模型更好的更新准确率和多边形相似度,并且接近手工方法的效果。     

基于证据权法的伊尔岗地块金矿成矿预测

在分析澳大利亚伊尔岗地块金矿床成矿特征的基础上,建立了区域金矿找矿模型,提取各类找矿信息,在GIS中构成了与成矿有关的容矿岩石、构造、岩浆岩、物探、化探异常等6个证据图层。用证据权法统计综合证据图层生成研究区成矿后验概率图。按照后验概率的相对大小划分出3级成矿远景区,共圈定3个I级成矿远景区,为澳大利亚的金矿预测提供了有效方法。     

虚拟天文台数据访问系统(VO-DAS)任务调度设计与实现

为解决异地、异构、海量天文数据无缝透明地统一访问,中国虚拟天文台(China-VO)研究小组自主设计并开发了一套解决方案——虚拟天文台数据访问系统(VO-DAS)。着重从执行流程、设计模式、Session机制、生命周期、资源销毁、异常处理等模块详细阐述了该系统的任务调度设计。为了验证该系统的可行性和性能,最后描述了多个天文科学范例。     

基于SuperMap GIS的道路网络特征分析

道路网络特征分析是进行交通网络分析的基础,本文基于SuperMap GIS分析了道路网络特征,其中包括网络统计特征、网络中心性等网络特征,并以北京市道路网络数据为例进行了实验分析,实验结果表明SuperMapGIS是研究道路网络特征分析的重要计算平台。     

海量海洋地图数据的分布式体系研究

针对目前架设海量海洋数据服务的主要方式优缺点,结合海洋数据的海量特点,提出需要解决的关键问题,具体阐述了海量海洋地图数据服务系统的双分布式架构的各个方面,介绍分布式服务系统的性能测试方案,分析了性能测试结果,最后给出了结论。     

GIS技术在油气勘探中的应用及发展趋势

GIS是处理空间信息的强大工具,GIS应用于油气勘探中,能够有效的分析潜在资源,发现新资源或扩展现有资源。今后,网络GIS、三维甚至高维GIS是GIS在油气勘探领域应用的重要发展方向。     

Use of Geomorphological Information in Indirect Landslide Susceptibility Assessment

The objective of this paper is to evaluate the importance of geomorphological expert knowledge in the generation of landslide susceptibility maps, using GIS supported indirect bivariate statistical analysis. For a test area in the Alpago region in Italy a dataset was generated at scale 1:5,000. Detailed geomorphological maps were generated, with legends at different levels of complexity. Other factor maps, that were considered relevant for the assessment of landslide susceptibility, were also collected, such as lithology, structural geology, surficial materials, slope classes, land use, distance from streams, roads and houses. The weights of evidence method was used to generate statistically derived weights for all classes of the factor maps. On the basis of these weights, the most relevant maps were selected for the combination into landslide susceptibility maps. Six different combinations of factor maps were evaluated, with varying geomorphological input. Success rates were used to classify the weight maps into three qualitative landslide susceptibility classes. The resulting six maps were compared with a direct susceptibility map, which was made by direct assignment of susceptibility classes in the field. The analysis indicated that the use of detailed geomorphological information in the bivariate statistical analysis raised the overall accuracy of the final susceptibility map considerably. However, even with the use of a detailed geomorphological factor map, the difference with the separately prepared direct susceptibility map is still significant, due to the generalisations that are inherent to the bivariate statistical analysis technique.