计算机应用 ›› 2014, Vol. 34 ›› Issue (6): 1816-1818.DOI: 10.11772/j.issn.1001-9081.2014.06.1816

• 行业与领域应用 • 上一篇    下一篇

面向地理标记语言空间数据的地理信息聚合

苗立志1,2,焦东来1,2,杨立君1,2   

  1. 1. 南京邮电大学 地理信息与生物信息处理研究所,南京 210023
    2. 南京邮电大学 地理与生物信息学院, 南京 210023
  • 收稿日期:2013-12-12 修回日期:2014-01-26 出版日期:2014-06-01 发布日期:2014-07-02
  • 通讯作者: 苗立志
  • 作者简介:苗立志(1981-),男,山东苍山人,副教授,博士,主要研究方向:地理信息共享与空间数据互操作、分布式地理空间信息处理;焦东来(1977-),男,河北安国人,副教授,博士,主要研究方向:地图符号共享;杨立君(1977-),男,黑龙江勃利人,讲师,博士研究生,主要研究方向:摄影测量与遥感、地理信息系统。
  • 基金资助:

    重庆市科委基础与前沿研究项目;南京邮电大学2013年实验室工作研究课题

Geographic information aggregation model of spatial data described by geography markup language

MIAO Lizhi1,2,JIAO Donglai1,2,YANG Lijun1,2   

  1. 1. College of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing Jiangsu 210023, China;
    2. Institute of Geographic and Biologic Information Processing, Nanjing University of Posts and Telecommunications, Nanjing Jiangsu 210023, China
  • Received:2013-12-12 Revised:2014-01-26 Online:2014-06-01 Published:2014-07-02
  • Contact: MIAO Lizhi
  • Supported by:

    National Natural Science Foundation

摘要:

针对地理标记语言(GML)空间数据的开放、可自我描述以及离散分布等特性,为了从海量GML空间数据中获取有针对性的整合应用,实现对GML空间数据的动态聚合,基于地理简易信息聚合(GeoRSS)标准,提出了面向GML空间数据的聚合映射模型,并设计了四层的集成框架体系结构及其工作流程。依据此体系结构,开发了GML空间数据地理信息聚合原型系统,并进行了相关实验,实现了对GML空间数据的有效聚合,验证了面向GML空间数据的地理信息聚合方法的可行性和聚合模型的可用性。该聚合方法使用户能够快速地从海量GML空间信息数据中获取更有目标性的数据,实现对已有数据的挑选、分析、归类,以及快速更新与整合集成等具体应用。

Abstract:

For implementing dynamic aggregation of dispersive Geography Markup Language (GML) geospatial data, a aggregation mapping model based on GeoRSS standards was proposed considering the openness, self-description and dispersion characteristics of GML. A four-tier integrating framework of prototype architechture and its workflow were generated to utilize the above model to construct the related program. Then a aggregation prototype system was designed and developed for aggregating dispersive GML spatial data according to the system architechture. Based on this prototype system, the related experiments were performed to verify the feasibility of GML geospatial data aggregation, and confirm the correctness and availablity of the model. This prototype can help users to quikly find the GML geospatial data from the massive Geographic Information System (GIS) data, to achieve selection, analysis and classification of the existing data, as well as the instant updating and aggregating integration.

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