基于地图空间数据的空间信息多级网格生成方法

简要介绍了空间信息多级网格的核心思想以及网格编码系统,利用Visual Basic开发工具和美国ESRI公司的MapObjects控件,通过空间点坐标、基本网格行列号、网格级别和编码间的转换关系,实现了在地图空间数据基础上生成多级网格的方法.     

差分VLBI测量的一种实现方案

差分VLBI通过交替观测目标天体和参考天体,将共同的误差因素从观测量中扣除,能够实现高精度的相对定位,因而在深空探测中有重要作用.然而,差分VLBI高精度的实现要求目标天体和参考天体的角距很近,这大大限制了其应用.讨论设计了差分VLBI测量的一种实现方案,利用多颗参考源的观测内插出目标源的非几何时延修正,放宽了对目标源和参考源的角距限制.该方案在S波段对目标源非几何时延的修正精度可以达到1 ns水平.     

3D-GIS中方向关系描述及其推理

方向关系是描述一个物体与另一个物体的相对位置关系。现有文献主要研究二维空间方向关系的描述和定性推理,二维空间中方向关系的描述和推理相对比较完善。本文采用投影方法给出三维空间方向关系描述模型,研究了单方向关系的推理,在此基础之上给出了单方向与多方向关系的定性推理,以及多方向关系与多方向关系间的定性推理。最后研究单方向关系定性推理的一些规律。     

一种快速图像匹配方法的设计与实现

改进了遗传算法的编码,重新定义了交叉变异算子,结合运动估计中一种新的线性搜索方法--线性正方形搜索算法,实现了一种快速匹配算法,试验表明了算法的有效性和优越性.     

基于ArcEngine的管线系统的实现

城市综合管网是城市建设的重要组成部分,随着城市地理空间基础框架工程的推进和城市管网信息化的加速发展,城市管网数据将更加与基础地理数据融合为一体,并为城市建设提供基础服务。结合实际应用,介绍了Ar-cEngine在城市管线管理中的应用,以及管线数据库和基础地理空间框架库集成,对于基于GIS的综合管线系统开发具有借鉴和参考价值。     

近太空平台摄影测量与遥感

本文介绍了近太空平台及主要特点，提出了在近太空平台搭载各类传感器进行摄影测量与遥感的初步设想，分析了它们的测绘性能，认为未来近太空平台摄影测量系统将成为航空和卫星系统的重要补充。     

战场环境可视化中多源遥感影像数据处理

介绍了将多源遥感影像数据应用于战场环境可视化之前的主要预处理方法,如影像金字塔生成、纹理数据结构准备、纹理快速调用等。该过程中所用到的小波变换、四叉树数据结构与细节层次算法等关键技术,能够有效地提高战场建模的真实感和效率。     

Cartographic Design and the Space–Time Cube

This paper reports on the results of an empirical evaluation that aimed to define the effectiveness and efficiency of different visual variables in depicting the Space–Time Cube’s (STC) content. Existing STC applications demonstrate that the most used visual variables are size and colour hue. Less is known, however, about their usability metrics. The research sets design criteria for STC contents, such as space–time paths, based on the cartographic design theory. The visual variables colour hue, colour value, colour saturation, size and orientation have been applied in two different use case studies. Besides, to support the three-dimensional visual environment, depth cues such as shading and transparency were considered too. User tests have been executed based on real-world problems with particular attention for the visualization strategy and data complexity. The outcomes revealed the most efficient and effective visual variables to represent data of various complexities in the STC.     

Cartographic Symbol Design Considerations for the Space–Time Cube

The cartographic representation of geographic phenomena in the space–time cube comes with special challenges and opportunities when compared with two-dimensional maps. While the added dimension allows the display of attributes that vary with time, it is difficult to display rapidly varying temporal data given the limited display height. In this study, we adapt 2D cyclic point symbols to construct 3D surfaces designed along a helical path for the space–time cube. We demonstrate how these complex?3D helical surfaces can display detailed data, including data reported daily over 100 years and data reported in four-hour intervals over a year. To create the point symbols, each value is plotted along the curve of a helix, with each turn of the helix representing one year or week, respectively. The model is modified by varying the radii from the time axis to all points using the attribute value, in these cases maximum daily temperature and four-hourly ridership, and then creating a triangulated surface from the resulting points. Using techniques common to terrain representation, we apply hue and saturation to the surface based on attribute values, and lightness based on relief shading. Multiple surfaces can be displayed in a space–time cube with a consistent time interval facing the viewer, and the surfaces or viewer perspective can be rotated to display synchronized variations. We see this method as one example of how cartographic design can refine or enhance operations in the space–time cube.     

Re-examining urban region and inferring regional function based on spatial–temporal interaction

Urban system is shaped by the interactions between different regions and regions planned by the government, then reshaped by human activities and residents’ needs. Understanding the changes of regional structure and dynamics of city function based on the residents’ movement demand are important to evaluate and adjust the planning and management of urban services and internal structures. This paper constructed a probabilistic factor model on the basis of probabilistic latent semantic analysis and tensor decomposition, for purpose of understanding the higher order interactive population mobility and its impact on urban structure changes. First, a four-dimensional tensor of time (T)?×?week (W)?×?origin (O)?×?destination (D) was constructed to identify the day-to-day activities in three time modes and weekly regularity of weekday/weekend pattern. Then we reclassified the urban regions based on the space clustering formed by the space factor matrix and core tensor. Finally, we further analysed the space–time interaction on different time scales to deduce the actual function and connection strength of each region. Our research shows that the application of individual-based spatial–temporal data in human mobility and space–time interaction study can help to analyse urban spatial structure and understand the actual regional function from a new perspective.