基于多源大数据的武汉市区域空间格局研究*
Study on Regional Spatial Structure of Wuhan Based on Multiple Online Data
詹庆明
武汉大学城市设计学院 教授，博士生导师
张月朦
武汉大学城市设计学院 硕士研究生
张慧子
武汉大学城市设计学院 硕士研究生
米子豪
武汉大学城市设计学院 硕士研究生
罗名海
武汉市测绘研究院 副总工程师，教授级高级工程师，博士
范域立
武汉大学城市设计学院 博士研究生
摘要: 综合多源数据、采用精细方法、分析具体问题，是大数据时代对于城市和区域问题分析提出的新要求。探讨交通格局、区域联系、人口腹地等区域研究中的主要话题在这一背景下的发展方向，利用交通大数据和人口流动大数据表现出的多属性、高密度和广覆盖特点，在经典的区域分析模型基础上，提出综合便利度模型、便利度—引力模型和势力范围模型。以武汉市为研究对象展开分析，通过一系列多对多指标，揭示武汉市与周边中心城市的不同形式的竞争关系；从东西、远近等不同角度阐述武汉所面对的区域发展机遇。通过研究发现，针对多源大数据的特点设计区域空间格局方法和指标，能更好地梳理和量化对区域问题的理解。
Abstract: The big data era of urban and regional analytics calls for the synthesis of resources, refinement of measures, and pertinence in research topics. This paper discusses the potential development of major issues in regional studies, including transportation, intercity connection, and population hinterland. Comprehensive accessibility model, accessibility-gravity model, and range-of-influence model are proposed or improved based on classical models exploiting the density, coverage, and multi-dimension of new data sources for region analytics. An empirical study on Wuhan reveals its various competitive relationships with its neighboring provinces by exploiting aforementioned many-to-many indicators, and potential opportunities in Wuhan’s future development are thus demonstrated. Methods specifically designed for big data analytics thus proves useful when facing pertinent regional spatial structure problems.
关键词：多源大数据 | 区域空间格局 | 交通可达性 | 人口腹地 | 区域城市联系
Keyword: Multiple online data | Regional spatial structure | Transportation accessibility | Population hinterland | Intercity connection
中图分类号：TU981
文献标识码: A
资金资助
国家自然科学基金重点项目 “可靠性遥感影像分类与空间关联分析” 41331175
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