地球信息科学学报 ›› 2015, Vol. 17 ›› Issue (2): 135-146.doi: 10.3724/SP.J.1047.2015.00135

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多尺度空间关系研究进展

杜世宏1(), 雒立群1,2, 赵文智1, 郭舟1   

  1. 1. 北京大学遥感与GIS研究所,北京 100871
    2. 61243部队,乌鲁木齐 830006
  • 收稿日期:2014-11-15 修回日期:2014-12-10 出版日期:2015-02-10 发布日期:2015-02-10
  • 作者简介:

    作者简介:杜世宏(1975-),男,副教授,主要从事空间关系知识描述与推理研究。E-mail:dshgis@hotmail.com

  • 基金资助:
    国家自然科学基金项目(41171297)

Research Progress in Multi-scale Spatial Relations

DU Shihong1,*(), LUO Liqun1,2, ZHAO Wenzhi1, GUO Zhou1   

  1. 1. Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China
    2. Unit 61243 of PLA, Urumqi 830006, China
  • Received:2014-11-15 Revised:2014-12-10 Online:2015-02-10 Published:2015-02-10
  • Contact: DU Shihong E-mail:dshgis@hotmail.com.
  • About author:

    *The author: CHEN Nan, E-mail:fjcn99@163.com

摘要:

空间关系及其尺度变化建模,一直是地理信息科学基础理论的重要前沿领域之一。本文全面总结了该领域在理论、方法和应用方面的最新进展。首先,详细阐述了关系表现与几何表现的特点和差异,提出了关系表现的尺度问题,尤其是与制图综合的关系。然后,分别结合形状化简、面对象合并、属性归纳、空间维数退化等制图综合算子,论述了拓扑和方向关系尺度变化规律的推导和建模方法。最后,结合多尺度空间关系变化模型,提出了基于关系的多尺度数据分析技术框架,并重点阐述了基于关系的多尺度数据一致性检测和多尺度数据查询的概念及解决方法,且用实例分析证明了它们的有用性。详细而具体地研究不同综合算子对拓扑和方向关系尺度变化的影响及建模方法,对于分析和理解多尺度空间数据,具有重要意义。

关键词: 拓扑关系, 方向关系, 制图综合, 尺度变化, 关系一致性

Abstract:

Modeling spatial relations and their scale changes has been one of the important topics in GIS science. This paper discussed the geometric-based and relational-based representation of geographic information. The first representation aims to store, manage, and analyze geometric data with coordinates, and concentrates on the geometric locations, shapes and distributions of spatial objects, thus it is termed as geometric representation. The latter uses symbols to qualitatively represent, communicate and infer spatial relationships between spatial objects based on people’s cognition and understanding, thus it is termed as relational representation. This paper mainly focused on summarizing the latest progress in theories, methods and applications about the relational representation. First, the above-mentioned two representations were compared and their scale changes were highlighted. It is discovered that the geometric representations of same geographic entities vary at different spatial scales, so do the relational representations vary between geographic entities. This type of changes in relational representations strongly associates with cartographic generalization operators, which affects the changes of shapes, sizes and structures of spatial objects. Second, the influences of the generalization operators, which include shape simplification, merging of areal objects, attribute induction and spatial dimension reduction, on spatial relations were analyzed, and related methods were presented for deriving and modeling the scale changes of topological and directional relations which was caused by the four operators. Third, combined with multi-scale spatial relations, a technological framework for analyzing multi-scale datasets was presented. We also illustrated the concepts and solutions for detecting the consistency of multi-scale data, and tested them practically with case studies to demonstrate their efficiency. Finally, it can be concluded that the generalization operators and modeling methods play important roles in analyzing and understanding multi-scale spatial datasets.

Key words: topological relations, direction relations, map generalization, scale changes, relation consistency