基于手机信令数据的长春市活动空间特征与社区分异研究

doi:10.13959/j.issn.1003-2398.2018.06.005

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人文地理 ›› 2018, Vol. 33 ›› Issue (6) : 35-43. DOI: 10.13959/j.issn.1003-2398.2018.06.005

社会

基于手机信令数据的长春市活动空间特征与社区分异研究

闫晴¹, 李诚固¹, 陈才¹, 罗凤龙²

作者信息 +

CHARACTERISTICS OF ACTIVITY SPACE AND COMMUNITY DIFFERENTIATION IN CHANGCHUN: A STUDY USING MOBILE PHONE SIGNALING DATA

YAN Qing¹, LI Cheng-gu¹, CHEN Cai¹, LUO Feng-long²

Author information +

文章历史 +

摘要

居民时空行为成为透视城市空间的重要视角，本文基于手机信令数据研究长春市活动空间及其社区分异，轮廓性的揭示居住空间、就业空间和消费休闲空间的分布规律，从人地互动的过程与格局的视角认识城市空间。研究发现，居住活动对中心城区依赖明显高于就业和消费休闲活动，就业活动呈现多中心连片发展格局，近郊的欧亚卖场和郊区的净月潭成为人们消费休闲活动的重要选择。就业-居住距离和消费休闲-居住距离的社区分异显著，折射出三类活动空间关系复杂，由此感知城市生活空间质量和社会空间结构。通过对社区分异的空间聚类分析明晰各地域自身问题，从而有针对性的对长春的空间调整优化和居民行为引导提出建议，构建和谐宜居的城市空间。

Abstract

The spatial and temporal behavior of the residents has become an important perspective of the perspective of urban space. This paper preliminarily explores the behavior space of residents and urban social space. This paper reveals the regularities of distribution of living space, employment space and consumption and leisure space roughly, and then we can understand the urban space from the perspective of the process and pattern of human-environment interaction. The provincial government and its surrounding areas become the regions with the highest utilization rate of space. The residents' activity space presents a typical circle structure. Taking the provincial government as the center, the population activity density is decreasing gradually. Population activities are characterized by concentration in the daytime and dispersion at night. Population activities are also concentrated in the working days and dispersed in the rest days. The paper finds that the dependence of residential activities on central urban area is very high, which is significantly higher than the employment activities and consumption and leisure activities. The lag of the development of the third industry leads to the lack of distinctions in the division of employment space. The employment activities present a multi center continuous development pattern. In addition to the traditional commercial center, the Eurasia shopping mall in the outskirts of the city and Jingyuetan forest park in the suburbs have become important choices for people to consume leisure activities. There are significant differences in the community of employment distance and consumption and leisure distance, which reflects the complexity of the three types of activities.

导出引用

闫晴, 李诚固, 陈才, 罗凤龙. 基于手机信令数据的长春市活动空间特征与社区分异研究[J]. 人文地理. 2018, 33(6): 35-43 https://doi.org/10.13959/j.issn.1003-2398.2018.06.005

YAN Qing, LI Cheng-gu, CHEN Cai, LUO Feng-long. CHARACTERISTICS OF ACTIVITY SPACE AND COMMUNITY DIFFERENTIATION IN CHANGCHUN: A STUDY USING MOBILE PHONE SIGNALING DATA[J]. HUMAN GEOGRAPHY. 2018, 33(6): 35-43 https://doi.org/10.13959/j.issn.1003-2398.2018.06.005

中图分类号： C912.81

参考文献

[1] 柴彦威,申悦,马修军,等.北京居民活动与出行行为时空数据采集与管理[J].地理研究,2013,32(3):441-451.[Chai Yanwei, Shen Yue, Ma Xiujun, et al. The collection and management of space-time data of individual behavior based on location-based technologies:A case study of activity-travel survey in Beijing[J]. Geographical Research, 2013,32(3):441-451.]
[2] Horton F E, Reynolds D R. Effects of urban spatial structure on individual behavior[J]. Economic Geography, 1971,47(1):36-48.
[3] Chapin F S. Human activity patterns in the city[J]. Queen's Quarterly, 1974,29(12):463-469.
[4] Carpenter S, Jones P M. Recent Advances in Travel Demand Analysis[M]. Alder-shot:Gower, 1983:385-400.
[5] Hanson S, Johnston I. Gender differences in work-trip length:Explanations and implications[J]. Urban Geography, 2010,6(3):193-219.
[6] Gordon P, Kumar A, Richardson H W. Gender differences in metropolitan travel behaviour[J]. Regional Studies, 1989,23(6):499-510.
[7] Bromley R D, Tallon A R, Thomas C J. Disaggregating the spacetime layers of city-center activities and their users[J]. Environment and Planning A, 2003,35(10):1831-1852.
[8] Naess P. Accessibility, activity participation and location of activities:Exploring the links between residential location and travel behaviour[J].Urban Studies, 2006,43(3):627-652.
[9] Song C M, Qu Z H, Nicholas B, et al. Limits of predictability in human mobility[J]. Science, 2010,327(5968):1018-1021.
[10] González M C, Hidalgo C A, Barabási A L. Understanding individual human mobility patterns[J]. Nature, 2008,453(7196):779-782.
[11] Golledge R G, Stimson R J. Spatial behavior:A geographic perspective[J]. Economic Geography, 1998,74(1):83-85.
[12] 柴彦威,沈洁.基于活动分析法的人类空间行为研究[J].地理科学, 2008,28(5):594-600.[Chai Yanwei, Shen Jie. Activity-based approach to human spatial behavior research[J]. Scientia Geographica Sinica, 2008,28(5):594-600.]
[13] 沈洁,柴彦威.郊区化背景下北京市民城市中心商业区的利用特征[J].人文地理.2006,21(5):113-116.[Shen Jie, Chai Yanwei. Study on residents' utilization of downtown retail center in Beijing in the context of city suburbanization[J]. Human Geography, 2006,21(5):113-116.]
[14] Wang D, Chai Y. The jobs-housing relationship and commuting in Beijing, China:The legacy of Danwei[J]. Journal of Transport Geography, 2009,17(1):30-38.
[15] 王波,甄峰,魏宗财.南京市区活动空间总体特征研究——基于大数据的实证分析[J].人文地理,2014,29(3):14-21,55.[Wang Bo, Zhen Feng, Wei Zongcai. The research on characteristics of urban activity space in Nanjing:An empirical analysis based on big data[J]. Human Geography, 2014,29(3):14-21,55.]
[16] 丁亮,钮心毅,宋小冬.基于移动定位大数据的城市空间研究进展[J].国际城市规划,2015,30(4):53-58.[Ding Liang, Niu Xinyi, Song Xiaodong. Urban spatial studies with big data of mobile location:A progress review[J]. Urban Planning International, 2015,30(4):53-58.]
[17] 丁亮,钮心毅,宋小冬.利用手机数据识别上海中心城的通勤区[J]. 城市规划,2015,39(9):100-106.[Ding Liang, Niu Xinyi, Song Xiaodong. Identifying the commuting area of Shanghai central city using mobile phone data[J]. City Planning Review, 2015,39(9):100-106.]
[18] Schwanen T, Dijst M, Dieleman F M. A microlevel analysis of residential context and travel time[J]. Environment and Planning A, 2002,34(8):1487-1508.
[19] Becker R A, Caceres R, Hanson K, et al. A tale of one city:Using cellular network data for urban planning[J]. IEEE Pervasive Computing, 2011,10(4):18-26.
[20] 田金玲,王德,谢栋灿,等.上海市典型就业区的通勤特征分析与模式总结——张江、金桥和陆家嘴的案例比较[J].地理研究,2017,36(1):134-148.[Tian Jinling, Wang De, Xie Dongcan, et al. Identifying the commuting features and patterns of typical employment areas in Shanghai using cellphone signaling data:A case study in Zhangjiang, Jinqiao and Lujiazui[J]. Geographical Research, 2017, 36(1):134-148.]
[21] 丁亮,钮心毅,宋小冬.上海中心城就业中心体系测度——基于手机信令数据的研究[J].地理学报,2016,71(3):484-499.[Ding Liang, Niu Xinyi, Song Xiaodong. Measuring the employment center system in Shanghai central city:A study using mobile phone signaling data[J]. Acta Geographica Sinica, 2016,71(3):484-499.]
[22] 王德,王灿,谢栋灿,等.基于手机信令数据的上海市不同等级商业中心商圈的比较——以南京东路、五角场、鞍山路为例[J].城市规划学刊,2015(3):50-60.[Wang De, Wang Can, Xie Dongcan, et al. Comparison of retail trade areas of retail centers with different hierarchical levels:A case study of east Nanjing road, Wujiaochang, Anshan road in Shanghai[J]. Urban Planning Forum, 2015(3):50-60.]
[23] Ahas R, Mark Ü. Location based services:New challenges for planning and public administration[J]. Futures, 2005,37(6):547-561.
[24] 钮心毅,丁亮,宋小冬.基于手机数据识别上海中心城的城市空间结构[J].城市规划学刊,2014(6):61-67.[Niu Xinyi, Ding Liang, Song Xiaodong. Understanding urban spatial structure of Shanghai central city based on mobile phone data[J]. Urban Planning Forum, 2014(6):61-67.]
[25] 钟炜菁,王德,谢栋灿,等.上海市人口分布与空间活动的动态特征研究——基于手机信令数据的探索[J].地理研究,2017,36(5):972-984.[Zhong Weijing, Wang De, Xie Dongcan, et al. Dynamic characteristics of Shanghai's population distribution using cell phone signaling data[J]. Geographical Research, 2017,36(5):972-984.]
[26] Wang P. Understanding the spreading patterns of mobile phone viruses[J]. Proceedings of the National Academy of Sciences, 2009, 106(20):8380-8385.
[27] 湛东升,张文忠,孟斌,等.北京城市居住和就业空间类型区分析[J]. 地理科学,2017,37(3):356-366.[Zhan Dongsheng, Zhang Wenzhong, Meng Bin, et al. Spatial structure of urban residence and employment in Beijing[J]. Scientia Geographica Sinica, 2017,37(3):356-366.]
[28] ESRI. ArcGIS帮助10.1.分组分析的工作原理[EB/OL].(2014-05-01)[2017-10-15]. http://resources.arcgis.com/zh-cn/help/main/10.1/index.html#/na/005p0000004w000000/.[ESRI. ArcGIS Help10.1. Working principle of grouping analysis[EB/OL].(2014-05-01)[2017-10-15]. http://resources.arcgis.com/zh-cn/help/main/10.1/index.html#/na/005p0000004w000000/.]
[29] 张鸿雁.城市形象与城市文化资本论——中外城市形象比较的社会学研究[M].南京:东南大学出版社, 2002:21.[Zhang Hongyan. Urban Image and Urban Cultural Capital:A Sociological Study of Urban Image Comparison Between China and Foreign Countries[M]. Nanjing:Southeast University Press, 2002:21.]
[30] 王兴中,王立,谢利娟,等.国外对空间剥夺及其城市社区资源剥夺水平研究的现状与趋势[J].人文地理,2008,23(6):7-12.[Wang Xingzhong, Wang Li, Xie Lijuan, et al. The status and trend of researches on deprivation of space and city community resources abroad[J]. Human Geography, 2008,23(6):7-12.]
[31] 申庆喜,李诚固,胡述聚.长春市居住与工业空间演进的耦合性测度及影响因素[J].人文地理,2017,32(1):62-67.[Shen Qingxi, Li Chenggu, Hu Shuju. The coupling measure and driving forces of the evolution of residential and industrial space in Changchun[J]. Human Geography, 2017,32(1):62-67.]
[32] 廖邦固,徐建刚,宣国富,等.1947-2000年上海中心城区居住空间结构演变[J].地理学报,2008,63(2):195-206.[Liao Banggu, Xu Jiangang, Xuan Guofu, et al. Evolution of residential space structure in Shanghai central city based on land use[J]. Acta Geographica Sinica, 2008,63(2):195-206.]