测绘学报 ›› 2021, Vol. 50 ›› Issue (12): 1705-1716.doi: 10.11947/j.AGCS.2021.20200361

• 位置服务与地理空间信息处理 • 上一篇    下一篇

空间方向相似性二元组模型度量方法

龚希1,2, 谢忠1,3, 周林1,3, 何占军1,3   

  1. 1. 中国地质大学(武汉)地理与信息工程学院, 湖北 武汉 430074;
    2. 湖北第二师范学院计算机学院, 湖北 武汉 430074;
    3. 国家地理信息系统工程技术研究中心, 湖北 武汉 430074
  • 收稿日期:2020-07-29 修回日期:2021-03-12 发布日期:2022-01-08
  • 通讯作者: 何占军 E-mail:hezj@cug.edu.cn
  • 作者简介:龚希(1992—),女,博士,研究方向为地理空间数据相似性度量。
  • 基金资助:
    国家重点研发计划(2018YFB0505500;2018YFB0505504);地质探测与评估教育部重点实验室开放基金(GLAB2020ZR05)

A two-tuple model based spatial direction similarity measurement method

GONG Xi1,2, XIE Zhong1,3, ZHOU Lin1,3, HE Zhanjun1,3   

  1. 1. Department of Information Engineering, China University of Geosciences, Wuhan 430074, China;
    2. College of Computer, Hubei University of Education, Wuhan 430074, China;
    3. National Engineering Research Center of Geographic Information System, Wuhan 430074, China
  • Received:2020-07-29 Revised:2021-03-12 Published:2022-01-08
  • Supported by:
    The National Key Research and Development Program of China (Nos. 2018YFB0505500;2018YFB0505504);The Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education (No. GLAB2020ZR05)

摘要: 针对方向关系矩阵模型对同一方向片区内方向变化识别能力不足、对不同方向片区间基准方向距离定义不完备、对任意方向关系矩阵间距离计算不够精确等问题,本文提出一种方向关系二元组模型,结合格网方向关系矩阵与质心方向关系矩阵,顾及对象的分布比例及质心位置变化,区分同一方向片区内的方向关系差异。同时,基于人类空间认知优化传统邻域图,建立适用于任意方向关系间基准距离度量的质心方向距离,通过EMD(Earth mover's distance)距离进一步提升方向关系二元组间距离计算的精确度。试验结果表明,本文方法简单可行,度量结果更符合人类认知,可应用于制图综合结果评估等任务。

关键词: 空间方向, 相似性度量, 格网方向关系矩阵, 质心方向关系矩阵, EMD距离

Abstract: Aiming at problems that in direction relation matrix model, recognition ability for distinguishing direction changes in the same cardinal direction is insufficient, the direction distance references for different cardinal directions are defined incompletely, and the distance calculation between arbitrarily direction relation matrices is not accurate enough, this paper proposes a direction relation two-tuple model, which combines grid-based direction relation matrix and centroid-based direction relation matrix to concern both distribution ratio variations and centroid position variations for objects, thus distinguishing the direction difference in the same cardinal direction. Meanwhile, the traditional neighborhood graph is optimized based on human spatial cognition, and a centroid direction distance reference suitable for arbitrarily direction relationships is established. Finally the Earth mover's distance (EMD) is utilized to further improve the accuracy of distance calculation between direction relation two-tuples. Experiments indicate the method is simple and feasible, the measurement results are more consistent with human cognition, and can be better applied to tasks like cartographic generalization results evaluation.

Key words: spatial direction, similarity measurement, grid-based direction relation matrix, centroid-based direction relation matrix, Earth mover's distance

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