全站仪断面测量方法

从野外断面测量的角度出发,主要讨论全站仪在断面测量中的野外观测方法、数据处理思路以及相应的软件研制.     

天宝GEOXT数据采集模式及精度研究

随着经济的不断发展,移动GIS越来越受到人们的关注,而GEOXT的出现正是符合这一发展趋势的产物。GEOXT这一款仪器将GPS与GIS结合在一起,利用GPS技术得出GIS的成果。文中在说明天宝GEOXT数据采集系统配置及特点的基础上,通过实验总结了数据采集的3种模式：单机码相位测距、后差分改正和实时差分改正数据采集,并对数据采集的技术流程、点位精度、特点和应用范围进行了阐述。最后对不同采集时间间隔对精度的影响进行了试验研究。     

城市公共卫生安全应急管理系统技术集成研究

从国内城市公共卫生安全应急管理系统的研究和应用现状出发,指出城市公共卫生安全应急管理系统建设的核心要务是集成现有的卫生信息系统、消除卫生信息孤岛、实现数据共享与交换;并提出了城市公共卫生安全应急管理系统数据采集类型和业务支持部门。在此基础上,构建了一个基于数据仓库、以GIS为应急响应支持平台、能统一管理信息、可与其他电子政务系统互连互通的城市公共卫生安全应急管理系统框架结构,并详细阐述了各业务模块的基本功能和系统实现的关键技术方法。     

一种时空数据静态可视化表达方法

本文简要介绍了时空数据可视化的必要性,以及目前人们采用的时空数据可视化方法,并分析了这些方法的局限性,提出了一种将年轮(annual ring)作为时空载体,结合视觉变量对面状地物的属性数据进行静态可视化的方法。该方法将面状地物的同心环按照类似树木年轮的生长特征进行划分,作为空间和时间的载体,不同时期属性数据映射到相应的同心环中,同心环的厚度和色彩的差异揭示了属性数据的变化。最后以武汉市城市管理网格化平台的统计评价数据为例实现了对比率量表数据的时态可视化表达。本文所提出的静态时空可视化方法将面状地物的空间、属性和时间紧密地结合在一起,克服了以往静态可视化方法中时间-空间、时间-属性相分离的不足,试验证明了这种方法在实践中的可行性。     

空间数据重复记录的清理方法研究

在空间数据的更新过程中,需要利用多种数据源对现有数据进行更新,这样可能会导致在获得的空间数据中出现重复记录。利用计算机自动对这些重复记录进行检查处理,将会极大地降低数据生产者的工作量。本文根据在数字制图系统研制过程中所遇到的此类问题,提出了对重复空间数据进行检查与处理的方法,并在所研制的数字制图系统中得到了应用。     

基于MAPGIS的土地利用数据库的更新方法讨论

本文主要对基于MAPGIS平台的土地利用数据库的更新方法进行分析讨论,并针对一些具体的数据变更叙述了其更新的方法;在本文最后还提出一些更新数据过程中需要注意的问题。     

Geodatabase与公交网络数据建模

随着城市交通的迅猛发展,交通问题已成为各国政府面临的首要问题,建立智能交通系统,将先进的地理信息技术引入城市道路交通管理已是必由之路。论文对公交网络数据模型进行深入分析。论文介绍了一种全新的面向对象的空间数据模型——Geodatabase,并对公交网络数据进行建模。     

Delaunay三角网关键技术探讨

利用计算机技术,基于实际测量数据,利用逐点插入法,在不建立格网索引的情况下,提出一种高效的Delaunay三角网构建方法,与建立格网索引法搜索点所在的三角形相比,具有较高的执行效率.     

Using snakes for the registration of topographic road database objects to ALS features

For historical reasons many national mapping agencies store their topographic data in a dual system consisting of a Digital Landscape Model (DLM) and a Digital Terrain Model (DTM). The DLM contains 2D vector data representing objects on the Earth’s surface, such as roads and rivers, whereas the DTM is a 2.5D representation of the related height information, often acquired by Airborne Laser Scanning (ALS). Today, many applications require reliable 3D topographic data. Therefore, it is advantageous to convert the dual system into a 3D DLM. However, as a result of different methods of acquisition, processing, and modelling, the registration of the two data sets often presents difficulties. Thus, a straightforward integration of the DTM and DLM might lead to inaccurate and semantically incorrect 3D objects.In this paper we propose a new method for the fusion of the two data sets that exploits parametric active contours (also called snakes), focusing on road networks. For that purpose, the roads from a DLM initialise the snakes, defining their topology and their internal energy, whereas ALS features exert external forces to the snake via the image energy. After the optimisation process the shape and position of the snakes should coincide with the ALS features. With respect to the robustness of the method several known modifications of snakes are combined in a consistent framework for DLM road network adaptation. One important modification redefines the standard internal energy and thus the geometrical model of the snake in order to prevent changes in shape or position not caused by significant features in the image energy. For this purpose, the initial shape is utilized creating template-like snakes with the ability of local adaptation. This is one crucial point towards the applicability of the entire method considering the strongly varying significance of the ALS features. Other concepts related to snakes are integrated which enable our method to model network and ribbon-like characteristics simultaneously. Additionally, besides ALS road features information about context objects, such as bridges and buildings, is introduced as part of the image energy to support the optimisation process. Meaningful examples are presented that emphasize and evaluate the applicability of the proposed method.     

Automatic interpretation of digital maps

In the past, the availability and/or the acquisition of spatial data were often the main problems of the realization of spatial applications. Meanwhile this situation has changed: on one hand, comprehensive spatial datasets already exist and on the other hand, new sensor technologies have the ability to capture fast and with high quality large amounts of spatial data. More and more responsible for the increasing accessibility of spatial data are also collaborative mapping techniques which enable users to create maps by themselves and to make them available in the internet. However, the potential of this diversity of spatial data can only hardly be utilized. Especially maps in the internet are represented very often only with graphical elements and no explicit information about the map’s scale, extension and content is available. Nevertheless, humans are able to extract this information and to interpret maps. For example, it is possible for a human to distinguish between rural and industrial areas only by looking at the objects’ geometries. Furthermore, a human can easily identify and group map objects that belong together. Also the type, scale and extension of a map can be identified under certain conditions only by looking at the objects’ geometries. All these examples can be subsumed under the term “map interpretation”. In this paper it is discussed how map interpretation can be automated and how automatic map interpretation can be used in order to support other processes. The different kinds of automatic map interpretation are discussed and two approaches are shown in detail.