地球信息科学学报 ›› 2018, Vol. 20 ›› Issue (6): 744-752.doi: 10.12082/dqxxkx.2018.180113

• 2017年中国地理信息科学理论与方法学术年会优秀论文专辑 • 上一篇    下一篇

地理空间模型自动数据匹配结果精准表达方法

杨杰1,2(), 诸云强1,3,4,*(), 宋佳1,3, 陆锋1, 孙凯1,2, 李威蓉5   

  1. 1. 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 100101
    2. 中国科学院大学,北京 100049
    3. 江苏省地理信息协同创新中心,南京 210023
    4. 白洋淀流域生态保护与京津冀可持续发展协同创新中心,保定 071002
    5. 山东理工大学建筑工程学院,淄博 255000
  • 收稿日期:2018-02-23 修回日期:2018-04-18 出版日期:2018-06-20 发布日期:2018-06-20
  • 作者简介:

    作者简介:杨 杰(1990-),男,湖南凤凰人,硕士生,研究方向为地理空间模型自动数据匹配和地学数据共享。 E-mail:yangjie.15s@igsnrr.ac.cn

  • 基金资助:
    国家自然科学基金项目(41631177、41771430);科技基础性工作专项重点项目(2013FY110900);资源与环境信息系统国家重点实验室自主部署项目(O88RA20CYA);贵州省公益性基础性地质工作项目(黔国土资地环函[2014]23号、[2016]269号)

A Precise Description Approach on the Result of Automatic Data Matching for Geo-spatial Model

YANG Jie1,2(), ZHU Yunqiang1,3,4,*(), SONG Jia1,3, LU Feng1, SUN Kai1,2, LI Weirong5   

  1. 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
    3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
    4. Baiyangdian Lake Ecological Protection and Sustainable Development of Jing-jin-ji Collaborative Innovation Center, Baoding 071002, China
    5. School of Architecture Engineering, Shandong University of Technology, Zibo 255000, China
  • Received:2018-02-23 Revised:2018-04-18 Online:2018-06-20 Published:2018-06-20
  • Contact: ZHU Yunqiang
  • Supported by:
    National Natural Science Foundation of China, No.41631177, 41771430;National Special Program on Basic Works for Science and Technology of China, No.2013FY110900;Foundation of State Key Laboratory of Resources and Environmental Information System, No.O88RA20CYA;Public and Basic Geological Project of Guizhou Province, China, No.[2014]23, [2016]269

摘要:

随着现代地学研究的深入与交叉融合,地理空间模型变得日益复杂,需要的输入数据也越来越多。为了快速、高效准备输入数据,一种有效的方法就是为模型自动匹配网络上已经共享的数据。在此背景下,本文针对不完全匹配数据需要自动转换处理的需求,开展了匹配结果精准表达方法研究。首先分析了自动数据匹配流程,在此基础上,提出了匹配结果精准表达结构及其形式化方法。匹配结果包含数据内容、空间和时间3个本质特征项,以及数据类型、格式和结构等形态特征项,每个特征项通过基于XML的相似度、匹配关系、匹配范围分别对共享数据与模型输入数据是否一致、差异在哪、差异有多大等问题进行精准的形式化表达。如果某一数据特征项相似度为1或本质特征项相似度为0时,意味着该特征项完全满足或完全不满足模型的需求,则没有必要进一步精准表达匹配结果;否则需要按上述方法对该数据特征项的匹配结果进行精准的形式化表达。湖南省2010年土壤生产潜力计算实践表明,本文方法可以为后继数据处理服务的自动组合及其数据的自动处理,以及最终向模型推荐完全符合需求的数据奠定基础。

关键词: 地理空间模型, 数据共享, 自动匹配, 语义关系, 精准表达

Abstract:

With the deep and interdisciplinary development of research on modern geoscience, geo-spatial models are becoming more and more complicated. Consequently, input data required for geo-spatial models are also growing up increasingly. In order to prepare these data quickly and efficiently, a feasible approach is to automatically match shared data from internet for the input requirements of geo-spatial model(MD4GSM). Under this background, in order to automatically convert or transform those incomplete matching data during the process of MD4GSM, this paper conduct the study on the precise description method for the matching result of shared data and geo-spatial model. Firstly, it analyzes the automatic data matching process. On this basis, this paper proposes a precise description structure and its formalization method to represent the matching result. The matching result includes three essential characteristics of data content, spatial information, temporal information, as well as morphological characteristics, such as data type, format, and structure, etc. In addition, each characteristic item is described clearly and precisely by similarity, matching relation and matching extent based on XML (eXtensible Markup Language) to reveal whether the shared data and model’s input data are consistent, where the difference is and how large the difference is. If the similarity of a characteristic is 1 or that of an essential characteristic is 0, it means the characteristic completely or not meets the requirement of geo-spatial model. In this condition, there is no need to precisely describe the matching result further; otherwise the matching result of the characteristic should be described formally and precisely according to the above method. The experiment of soil potential productivity calculation in Hunan province in 2010 shows that the method can be a foundation for automatic combining data processing services and dealing with data in the next, and finally recommending data that fully meet the needs of geo-spatial model.

Key words: geo-spatial model, data sharing, automatic matching, semantic relation, precise description