多元交通流视角下长江经济带城市网络空间组织模式分析  

Spatial Organization Pattern of Urban Network in the Yangtze River Economic Belt from the Perspective of Multiple Traffic Flows

作　　者：鲍进剑 梁娟珠[1] 周玉科[2] 贾红霞 BAO Jinjian;LIANG Juanzhu;ZHOU Yuke;JIA Hongxia(Institute of Digital China,Key Laboratory of Spatial Data Mining and Information Sharing,Ministry of Education,Fuzhou University,Fuzhou 350003;Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic and Nature Resources Research,Chinese Academy of Sciences,Beijing 100101;Information Center of Ministry of Ecology and Environment,Beijing 100029,China)

机构地区：[1]福州大学数字中国研究院,福州大学空间数据挖掘与信息共享教育部重点实验室,福建福州350003 [2]中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室,北京100101 [3]生态环境部信息中心,北京100029

出　　处：《地理与地理信息科学》2023年第2期46-54,143,共10页Geography and Geo-Information Science

基　　金：福建省科技计划项目(2020L3005);国家重点研发计划项目(2018YFB0505301、2021xjkk0303)。

摘　　要：从复杂网络和个体出行行为角度挖掘多中心城市网络空间组织模式,有助于优化城市空间结构。该文基于长江经济带多元交通流数据,采用TCD(Transportation Cluster Detection)社区发现算法融合百度地图API获取的城市内外部实时时间成本数据,构建多元交通流网络社区结构探测模型,对长江经济带城市网络的空间组织模式进行特征提取和规则挖掘。结果表明:(1)公路网络在省域尺度表现出显著的“核心—边缘”结构;铁路网络表现出“东高西低”的分布态势;航空网络分布态势与铁路网络相反,西部城市航空网络的枢纽效应强于中部、东部城市;综合交通网络总体呈现“以铁路为主、公路为辅、航空为补”的共振状态。(2)利用TCD算法合并节点过程中,社区数量与城市节点的邻近指数符合幂律分布,共识别出24个社区,其中包括贵州、云南、安徽、川渝、鄂湘赣和江浙沪六大“城市经济社区”。(3)长江经济带城市网络空间组织模式包括以贵州、昆明、合肥为核心的“单核心”模式、成都—重庆构建的“双核心”模式以及长沙—武汉—南昌和上海—南京—杭州构建的“多核心”模式,该城市网络空间组织模式对于揭示地级市网络空间关联格局具有指示意义。Mining the spatial organization pattern of polycentric urban networks from the perspective of complex networks and individual travel behaviors can help optimize the city spatial structure.Based on the multiple traffic flow data of the Yangtze River Economic Belt,this paper adopts TCD(transportation cluster detection)community discovery algorithm and integrates Baidu Map API to obtain real-time data of time cost inside and outside city,to construct a community structure detection model of multiple traffic flow networks,and conduct feature extraction and rule mining on the spatial organization patterns of urban networks in the Yangtze River Economic Belt.The results show that:①The road network shows a significant"core-edge"structure at the provincial scale;the railway network shows a"high in the east and low in the west"distribution;the aviation network is contrary to the railway network,and the hub effect of the aviation network in western cities is stronger than that in central and eastern cities;overall,the comprehensive transportation network presents a resonance state of railway serving as dominance,highway as assistance and aviation as supplement.②In the process of merging nodes by TCD algorithm,the number of communities and the proximity index of city nodes conform to the power law distribution,and a total of 24 communities are identified,mainly including six large-scale economic communities such as Guizhou,Yunnan,Anhui,Sichuan-Chongqing,Hubei-Hunan-Jiangxi and Jiangsu-Zhejiang-Shanghai.③The spatial organization pattern of urban networks in the Yangtze River Economic Belt can be divided into three types:the single-core structure with Guiyang,Kunming and Hefei as the core,respectively,the dual-core structure with Chengdu-Chongqing as the cores,and the multi-core structure with Changsha-Wuhan-Nanchang and Shanghai-Nanjing-Hangzhou as the cores.This spatial organization pattern of urban networks is indicative for revealing the network spatial association pattern among prefecture-level city units.

关 键 词：多元交通流网络 空间组织模式 长江经济带 TCD算法 百度地图 旅行成本 

分 类 号：F512.7[经济管理—产业经济]