地球信息科学学报 ›› 2020, Vol. 22 ›› Issue (1): 30-40.doi: 10.12082/dqxxkx.2020.190736

• 专辑:地理智能 • 上一篇    下一篇

地理流的空间模式:概念与分类

裴韬1,2,3,*(), 舒华1,2, 郭思慧1,2, 宋辞1, 陈洁1, 刘亚溪1,2, 王席1,2   

  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. 江苏省地理信息资源开发与利用协同创新中心,南京 210023
  • 收稿日期:2019-12-01 修回日期:2019-12-31 出版日期:2020-01-25 发布日期:2020-04-08
  • 通讯作者: 裴韬 E-mail:peit@lreis.ac.cn
  • 作者简介:裴 韬(1972— ),男,江苏扬州人,研究员,研究方向为地理大数据挖掘。
  • 基金资助:
    国家自然科学基金项目(41525004);国家自然科学基金项目(41421001)

The Concept and Classification of Spatial Patterns of Geographical Flow

PEI Tao1,2,3,*(), SHU Hua1,2, GUO Sihui1,2, SONG Ci1, CHEN Jie1, LIU Yaxi1,2, WANG Xi1,2   

  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
  • Received:2019-12-01 Revised:2019-12-31 Online:2020-01-25 Published:2020-04-08
  • Contact: PEI Tao E-mail:peit@lreis.ac.cn
  • Supported by:
    National Natural Science Foundation of China(41525004);National Natural Science Foundation of China(41421001)

摘要:

地理流被定义为地理对象在不同空间位置间的流动,而地理流通常涵盖了物质、信息、资金、能量等的空间转移。位置之间各种流的出现与强化,改变了以距离衰减效应为基本规律的传统认知。因此,针对地理流的研究将有助于从新的角度理解地理格局及其形成机理。本文认为可采用2种模型对地理流进行表达:① 将地理流抽象为包含起点和终点坐标的四元组(又称地理流正交模型);② 将其抽象为包含起点坐标、流长度与流方向的模型(又称地理流极坐标模型)。在地理流表达模型的基础上,流空间可以定义为由两个二维空间通过笛卡尔积形成的四维空间。本文给出了流空间中4种距离(最大距离、加和距离、平均距离和加权距离)、不同距离下地理流的r邻域体积以及地理流密度等测度的定义。根据地理流极坐标模型中不同要素随机性的组合方式,将地理流模式分为随机、丛集、聚散、社区、并行与等长6种常见的单一模式,并梳理了不同模式的识别方法。单一模式之间的组合可以形成混合模式,而多类流数据之间可以形成多元流模式。在未来的研究中,地理流的基础统计理论、地理流模式的挖掘方法以及在实际问题中的应用将是其重要的发展方向。

关键词: 流聚类, 流随机性, 流异质性, 流丛集模式, 流聚散模式, 流社区模式, 流等长模式, 流并行模式

Abstract:

Geographical flow can be defined as the movements of geographical objects between different locations, which are usually displayed as the movement of matter, information, energy and funds, e.g. the jobs-housing flow in a city, communications between different mobile phone holders and the fund transferred between different business entities. Due to the existence of the various flows, the link strength between different locations may not depend on distance only, say one may strongly related to a store faraway through express delivery rather than a store nearby. The traditional knowledge of distance-decay law may be changed. As a result, research on the geographical flow may help to understand geographical patterns and their mechanism from a new point of view. Two conceptual models are introduced for the expression of geographical flows in this paper. In the first model, a flow is abstracted as a coordinate quaternion composed of the origin point and the destination point (called the orthonormal flow model). Thus, the flow space can be defined as a 4-D space which is formed by the Cartesian product of two 2-D spaces. In the second model, a flow is composed of the origin point coordinates, the flow length and the flow angle (called the polar coordinate model). Based on the expression models, four distances are defined, specifically, maximum distance, additive distance, average distance and weighted distance. In addition, this paper defines some other flow measurements, including flow direction, the volume of a flow's r -neighborhood and the flow density. According to the combination of different statistical features (i.e. heterogeneity, homogeneity and randomness) between variables in the polar coordinate model, the spatial patterns of geographical flows are divided into six single patterns including random, clustering, convergent and divergent, community, parallel (angle-clustered) and equilong (length-clustered). The methods for identifying different flow patterns are also analyzed and summarized. Besides the single patterns, the combination of different single patterns will generate mixed patterns, and if more than one type of flows coexists, multi-flow patterns can be produced. Regarding research directions of geographical flow in the future, three aspects should be given more attentions: the basic statistical theory of flow, the mining method of flow pattern and its application in practical problems.

Key words: flow clustering, flow randomness, flow heterogeneity, flow clustering pattern, flow convergent and divergent pattern, flow community pattern, flow equilong pattern, flow parallel pattern