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中国科学院大学学报 ›› 2022, Vol. 39 ›› Issue (1): 64-73.DOI: 10.7523/j.ucas.2020.0029

• 环境科学与地理学 • 上一篇    

基于高速公路流的江苏省交通网络地域分异及影响因素

周健1,2, 靳诚3, 李平星1   

  1. 1. 中国科学院南京地理与湖泊研究所 中国科学院流域地理学重点实验室, 南京;
    2. 中国科学院大学资源与环境学院, 北京 100049;
    3. 南京师范大学地理科学学院, 南京 210023
  • 收稿日期:2020-03-31 修回日期:2020-05-25 发布日期:2021-06-01
  • 通讯作者: 周健
  • 基金资助:
    国家自然科学基金(41871209,41871137)资助

Regional differentiation and its influencing factors of traffic network in Jiangsu Province based on the expressway flow

ZHOU Jian1,2, JIN Cheng3, LI Pingxing1   

  1. 1. Key Laboratory of Watershed Geographic Sciences of CAS, Nanjing Institute of Geography&Limnology, Chinese Academy of Sciences, Nanjing 210008, China;
    2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China;
    3. College of Geography Science, Nanjing Normal University, Nanjing 210023, China
  • Received:2020-03-31 Revised:2020-05-25 Published:2021-06-01

摘要: 基于江苏省高速公路交通流量数据,构建高速公路全年流量模型,利用社会网络分析方法探究各县域的中心性与凝聚子群,结合地理探测器方法从江苏省整体以及苏南、苏中、苏北不同地域范围进行影响因素分析。结果表明:1)从总体上看,全年总流出量和流入量空间分布呈现由苏南向苏北递减的趋势;外出率较高地区分布于苏南—苏中—苏北地区的交界处、全省的边界地区以及苏南地区镇江市和常州市的交界地区;2)以苏州、南京、无锡为核心的苏南地区对全省有较强的交通集聚辐射效应,凝聚子群显示江苏省高速公路网络整体上呈现出“4组团、8片区”的特征;3)探测因子结果显示在省域范围内经济水平、产业结构、汽车保有量、人口规模、基础设施、居民购买力对高速公路流量的影响都较为显著,基于不同区域范围的因子决定力存在差异。

关键词: 高速公路流量, 空间网络分异, 社会网络分析, 地理探测器, 江苏省

Abstract: Based on the data of expressway traffic flow of Jiangsu Province, this paper builds the annual expressway traffic flow model, uses the method of social network analysis to explore the centrality and the agglomeration sub group of each county, and combines with the method of geographical detector to analyze the influencing factors from the perspective of the whole of Jiangsu Province, as well as the southern, central, and northern regions of Jiangsu. The results show that:1) On the whole, the spatial distribution of annual total outflow and inflow shows a decreasing trend from the south to the north; the areas with higher outflow rate are located at the junction of southern, central, and northern Jiangsu, the border areas of the whole province and the junction of Zhenjiang City and Changzhou City in southern Jiangsu. 2) The southern Jiangsu, with Suzhou, Nanjing, and Wuxi area as the core, has a strong traffic concentration and radiation effect on the whole province, and the cohesive subgroups show the characteristics of "four groups and eight zones" of the expressway network in Jiangsu Province in general.3) The results of detection factors show that economic level, industrial structure, car ownership, population scale, infrastructure, and purchasing power of residents all have a significant influence on the expressway flow in the province, and the explanatory power of factors are different in various regions.

Key words: expressway traffic flow, spatial network differentiation, social network analysis, geographical detector, Jiangsu Province

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