论文

地球空间数据集成研究概况

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  • 1. 中国科学院遥感应用研究所,北京100083;
    2. 中国科学院地理科学与资源研究所,北京100101
李军(1968-),男,河北大名县人,博士后。1998年在中科院地理研究所获得地图学与地理信息系统专业博士学位,主要从事地学数据基础研究及地理信息系统应用基础研究。

收稿日期: 2000-07-01

  修回日期: 2000-08-01

  网络出版日期: 2000-08-24

基金资助

“九五”重中之重攻关项目(96-B02-02-02)“重大自然灾害评估系统研究”资助

Overview of Study on Geo spatial Data Integration

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  • 1. Institute of Remore Sensing Spplication, CAS, Beijing 100083;
    2. Institute of Geographical Sciences and Natural Resources, CAS, Beijing 100101

Received date: 2000-07-01

  Revised date: 2000-08-01

  Online published: 2000-08-24

摘要

数字地球空间数据的集成研究及应用始于本世纪 60年代 ,地理信息系统的出现及应用、多元数据的使用推动了地球空间数据集成研究及其应用。本文首先对地球空间数据概念进行描述 ,然后对地球空间数据集成研究状况及存在的问题进行了详细的分析。结合数据集成需求及存在的问题 ,论文分析了数据集成的发展方向。

本文引用格式

李军, 费川云 . 地球空间数据集成研究概况[J]. 地理科学进展, 2000 , 19(3) : 203 -211 . DOI: 10.11820/dlkxjz.2000.03.002

Abstract

Application of Geographical Information Systems (GIS) and multi resources geo spatial data promotes the appearance of digital geo spatial data integration in 1960’s. But the weakness of study on geo spatial data integration hinders its own development. As a overview on geo spatial data integration, the paper focuses on fundamental concept, theory of data integration and problems in geo spatial data integration research currently. Geo spatial data is one kind of data used to represent, describe geographical processes and geographical phenomena. From the point view of geographical cognition, geo spatial data is abstraction of geographical entity controlled by geographical knowledge. Geo spatial data integration, as argued by many researchers, is the process during which multi resources and multi scale geo spatial data can be used in one uniform GIS software platform. The goals of geo spatial data integration, put simply, are creating seamless (including attribute seamless, temporal seamless and spatial seamless) dataset or database for certain application or general construction of geo spatial database. Study of geo spatial data integration mainly focus on data integration mechanism, error transfer, data quality controlling, multi scale, and representation of geo spatial data. Also many successful application of geo spatial data integration were carried out, but there are still many shortcomings of the fundamental researches on geo spatial data integration, such as integration principles, error propagation rules, multi scale data integration and data quality evaluation and controlling. The main problems about geo spatial data integration are short of general integration principles and rules, weak studying on geo spatial metadata, ignoring the applications of geo sciences principles and rules. Based on the analysis on geo spatial data integration, the authors list out some further research field on data integration such as network based data integration, data integration principles, metadata utility in data integration, geo sciences expert knowledge system and their application in geo spatial data integration.
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