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| 东北地区人口流动与多元交通网络格局的偏离和关联 | |
| 引用本文： | 李卓伟,王士君,程利莎,施响,关皓明,舒畅.东北地区人口流动与多元交通网络格局的偏离和关联[J].地理科学进展,2022,41(6):985-998. |
| 作者姓名： | 李卓伟 王士君 程利莎 施响 关皓明 舒畅 |
| 作者单位： | 1.东北师范大学地理科学学院,长春 130024 2.河南大学地理与环境学院,河南 开封 475004 3.吉林大学东北亚学院,长春 130015 4.东北师范大学数学与统计学院,长春 130024 |
| 基金项目： | 国家自然科学基金项目(42171198);国家自然科学基金项目(42001117);国家自然科学基金项目(41801153);中央高校基本科研业务费项目(2412020FZ001) |
| 摘 要： | 受限于个体流动数据的获取制约,以往人口流动研究多采用交通网络强度来模拟城市间的人口流动强度,忽视了二者之间的偏离。论文以铁路、公路车次构建交通网络,以腾讯位置大数据的铁路出行、公路出行数据构建人口流动网络,运用社会网络分析法、QAP模型,对比分析两者之间的偏离和关联。研究发现：① 东北地区铁路人口流动和其交通网络格局均呈现出以“哈大”走廊为轴的南密北疏、东众西寡的特征。铁路人口流动网络结构较为分散,铁路交通网络的极化效应明显。② 公路人口流动和其交通网络的偏离较大。公路和铁路之间存在竞争和互补关系,在铁路交通不太发达的地区,公路人口流动强度和其交通网络强度较高。③ 人口流动与交通网络存在一定关联,但人口流动受多方面因素影响,综合联系网络模型则能更准确地模拟城市间人口流动。其他影响因素中,经济联系、人口规模等因素对人口流动的影响不够明显,而城市间的邻接关系对人口流动有显著影响。④ 铁路人口流动与其交通网络的关联程度较公路人口与其交通网络的关联程度高。论文定量说明了人口流动与其交通网络的相关程度,为交通网络模拟人口流动提供了理论和实际操作层面的参考。 |
| 关 键 词： | 人口流动 交通网络 偏离和关联 社会网络分析法 QAP模型 东北地区 |
| 收稿时间： | 2021-10-12 |
| 修稿时间： | 2022-02-10 |
Differences and relationship between population flow and transportation networks in Northeast China |
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| LI Zhuowei,WANG Shijun,CHENG Lisha,SHI Xiang,GUAN Haoming,SHU Chang.Differences and relationship between population flow and transportation networks in Northeast China[J].Progress in Geography,2022,41(6):985-998. | |
| Authors: | LI Zhuowei WANG Shijun CHENG Lisha SHI Xiang GUAN Haoming SHU Chang |
| Institution: | 1. School of Geographical Science, Northeast Normal University, Changchun 130024, China 2. College of Geography and Environment, Henan University, Kaifeng 475004, Henan, China 3. Northeast Asian Studies College, Jilin University, Changchun 130015, China 4. School of Mathematics and Statistics, Northeast Normal University, Changchun 130024, China |
| Abstract: | Limited by the difficulty of obtaining individual mobility data, existing studies on population mobility mostly used strength of traffic flow to simulate population flow between cities, while ignoring the differences between them. This study constructed transportation networks based on inter-city bus and train trips in Northeast China, and built population flow networks based on Tencent location big data correspondingly. It then analyzed the differences and relationship between the two types of networks by using social network analysis and quadratic assignment procedure model. The results are as follows: 1) Both railway population network and railway transportation network in Northeast China are characterized by a spatial pattern of dense in the south and sparse in the north and numerous in the east and fewer in the west, with the Harbin-Dalian corridor as the axis. The spatial structure of railway population flow is more dispersed, while the polarization effect of railway transportation network is obvious. 2) There are great differences between road population flow network and road transportation network. There is not only competition but also complementary relationship between roads and railways. That is, road population or transportation flow is often strong in areas with less developed railways. 3) The accuracy of simulating inter-city population flow with a single transportation network is low, while the composite influencing factors can more accurately express the inter-city population flow structure. Among other influencing factors, economic ties and population size do not have significant impact on population flow, while adjacency between cities has a significant impact on the structure of population flow. 4) The fitting regression between railway population flow strength and its transportation network is better than that of roads. This study quantitatively explained the correlation between population flow and its transportation network, which provides a theoretical and practical reference for the simulation of population flow in transportation network. |
| Keywords: | population flow transportation network differences and relationship social network analysis quadratic assignment procedure model Northeast China |
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