GU Yanyan, JIAO Limin, DONG Ting, WANG Yandong, XU Gang. Spatial Distribution and Interaction Analysis of Urban Functional Areas Based on Multi-source Data[J]. Geomatics and Information Science of Wuhan University, 2018, 43(7): 1113-1121. DOI: 10.13203/j.whugis20160192
Citation: GU Yanyan, JIAO Limin, DONG Ting, WANG Yandong, XU Gang. Spatial Distribution and Interaction Analysis of Urban Functional Areas Based on Multi-source Data[J]. Geomatics and Information Science of Wuhan University, 2018, 43(7): 1113-1121. DOI: 10.13203/j.whugis20160192

Spatial Distribution and Interaction Analysis of Urban Functional Areas Based on Multi-source Data

Funds: 

The National Natural Science Foundation of China 41571385

The National Natural Science Foundation of China 41271399

China Special Fund for Surveying, Mapping and Geoinformation Research in the Public Interest 201512015

the National Key Research and Development Program of China 2016YFB0501400

More Information
  • Author Bio:

    GU Yanyan, PhD candidate, specializes in spatial data mining and urban spatial structure. E-mail: yyg@whu.edu.cn

  • Corresponding author:

    JIAO Limin, PhD, professor. E-mail:lmjiao027@163.com

  • Received Date: September 04, 2016
  • Published Date: July 04, 2018
  • With the rapid development of economy, urban internal space structure has been optimized significantly. It is of great significance to identify the spatial distribution and interaction rules of diffe-rent functional regions (DFR) for urban structure analysis and rational planning. We identify the spatial distribution of DFR by analyzing points of interest(POI) data based on kernel density estimation and head/tail breaks. On this basis, we analyze the spatio-temporal discipline of attraction and mutual relationship between typical DFR based on taxi trajectory data. Inside the 5th ring road of urban region of Beijing, the study reveals that:①Typical DFR Xidan, Guomao, Zhongguancun are business-oriented districts, Wangjing is a residential district with a significantly commuting characteristic. ②Guomao has the robust gravity (39.4%) on itself, which indicates that Guomao has more comprehensive urban functions. ③The attraction of DFR within the scope of resident trip distance decreases with the increase of distance, which conforms to the experience cognition and geographic spatial attenuation law. The results show that using kernel density estimation and head/tail breaks to analyze POI data and taxi trajectory data and identify the spatial distribution of DFR is reasonable and effective.
  • [1]
    Batty M. The Size, Scale, and Shape of Cities[J]. Science, 2008, 319(5864):769-771 doi: 10.1126/science.1151419
    [2]
    Jiao L, Liu Y. Analyzing the Spatial Autocorrelation of Regional Urban Datum Land Price[J]. Geo-spatial Information Science, 2012, 15(4):263-269 doi: 10.1080/10095020.2012.714103
    [3]
    郑宇.城市计算概述[J].武汉大学学报·信息科学版, 2015, 40(1):1-13 http://ch.whu.edu.cn/CN/abstract/abstract3172.shtml

    Zheng Yu. Introduction to Urban Computing[J].Geomatics and Information Science of Wuhan University, 2015, 40(1):1-13 http://ch.whu.edu.cn/CN/abstract/abstract3172.shtml
    [4]
    池娇, 焦利民, 董婷, 等.基于POI数据的城市功能区定量识别及其可视化[J].测绘地理信息, 2016, 41(2):68-73 http://www.cqvip.com/QK/93326X/201602/668486509.html

    Chi Jiao, Jiao Limin, Dong Ting, et al. Quantitative Identification and Visualization of Urban Functional Area Based on POI Data[J]. Journal of Geoma-tics, 2016, 41(2):68-73 http://www.cqvip.com/QK/93326X/201602/668486509.html
    [5]
    张云菲, 杨必胜, 栾学晨.语义知识支持的城市POI与道路网集成方法[J].武汉大学学报·信息科学版, 2013, 38(10):1229-1233 http://ch.whu.edu.cn/CN/abstract/abstract2762.shtml

    Zhang Yunfei, Yang Bisheng, Luan Xuechen. Integrating Urban POI and Road Networks Based on Semantic Knowledge[J]. Geomatics and Information Science of Wuhan University, 2013, 38(10):1229-1233 http://ch.whu.edu.cn/CN/abstract/abstract2762.shtml
    [6]
    Long Y, Shen Z. Geospatial Analysis to Support Urban Planning in Beijing[M]. Beijing:Springer International Publishing, 2015
    [7]
    蒋波涛, 王艳东, 叶信岳.使用点评数据探测城市商业服务设施的发展规律[J].测绘学报, 2015, 44(9):1022-1028 doi: 10.11947/j.AGCS.2015.20140556

    Jiang Botao, Wang Yandong, Ye Xinyue. Detecting Development Pattern of Urban Business Facilities Using Reviews Data[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(9):1022-1028 doi: 10.11947/j.AGCS.2015.20140556
    [8]
    李德仁, 姚远, 邵振峰.智慧城市中的大数据[J].武汉大学学报·信息科学版, 2014, 39(6):631-640 http://ch.whu.edu.cn/CN/abstract/abstract2999.shtml

    Li Deren, Yao Yuan, Shao Zhenfeng. Big Data in Smart City[J]. Geomatics and Information Science of Wuhan University, 2014, 39(6):631-640 http://ch.whu.edu.cn/CN/abstract/abstract2999.shtml
    [9]
    Liu Y, Wang F, Xiao Y, et al. Urban Land Uses and Traffic 'Source-Sink Areas':Evidence from GPS-enabled Taxi Data in Shanghai[J]. Landscape and Urban Planning, 2012, 106(1):73-87 doi: 10.1016/j.landurbplan.2012.02.012
    [10]
    Yuan J, Zheng Y, Xie X. Discovering Regions of Different Functions in a City Using Human Mobility and POIs[C]. The 18th ACM SIGKDD Interna-tional Conference on Knowledge Discovery and Data Mining, New York, USA, 2012
    [11]
    周素红, 郝新华, 柳林.多中心化下的城市商业中心空间吸引衰减率验证——深圳市浮动车GPS时空数据挖掘[J].地理学报, 2015, 69(12):1810-1820 http://www.cqvip.com/QK/90059X/201412/663525091.html

    Zhou Suhong, Hao Xinhua, Liu Lin. Validation of Spatial Decay Law Caused by Urban Commercial Center's Mutual Attraction in Polycentric City:Spatio-Temporal Data Mining of Floating Cars' GPS Data in Shenzhen[J].Acta Geographica Sinica, 2015, 69(12):1810-1820 http://www.cqvip.com/QK/90059X/201412/663525091.html
    [12]
    王汉东, 乐阳, 李宇光, 等.城市商业服务设施吸引力的空间相关性分析[J].武汉大学学报·信息科学版, 2011, 36(9):1102-1106 http://ch.whu.edu.cn/CN/abstract/abstract653.shtml

    Wang Handong, Yue Yang, Li Yuguang, et al. Spatial Correlation Analysis of Attractiveness of Commercial Facilities[J]. Geomatics and Information Science of Wuhan University, 2011, 36(9):1102-1106 http://ch.whu.edu.cn/CN/abstract/abstract653.shtml
    [13]
    Krosche J, Boll S. The xPOI Concept[C]. First International Workshop on Location and Context Awareness, Oberpfaffenhofen, Germany, 2005
    [14]
    彭明军.利用层次空间推理进行城市空间信息多级网格划分[J].武汉大学学报·信息科学版, 2010, 35(9):1112-1115 http://ch.whu.edu.cn/CN/abstract/abstract1053.shtml

    Peng Mingjun. Division of Urban Spatial Information Multi-grid Based on Hierarchical Spatial Reasoning[J].Geomatics and Information Science of Wuhan University, 2010, 35(9):1112-1115 http://ch.whu.edu.cn/CN/abstract/abstract1053.shtml
    [15]
    禹文豪, 艾廷华, 杨敏, 等.利用核密度与空间自相关进行城市设施兴趣点分布热点探测[J].武汉大学学报·信息科学版, 2016, 41(2):221-227 http://ch.whu.edu.cn/CN/abstract/abstract3459.shtml

    Yu Wenhao, Ai Tinghua, Yang Min, et al. Detecting "Hot Spots" of Facility POIs Based on Kernel Density Estimation and Spatial Autocorrelation Technique[J]. Geomatics and Information Science of Wuhan University, 2016, 41(2):221-227 http://ch.whu.edu.cn/CN/abstract/abstract3459.shtml
    [16]
    Jiang B. Head/Tail Breaks:A New Classification Scheme for Data with a Heavy-Tailed Distribution[J].The Professional Geographer, 2013, 65(3):482-494 doi: 10.1080/00330124.2012.700499
    [17]
    中华人民共和国住房和城乡建设部. GB50137-2011城市用地分类与规划建设用地标准[S]. 北京: 中国建筑工业出版社, 2011

    Ministry of Housing and Urban-Rural Development of the People's Republic of China. GB50137-2011 Code for Urban Land Use Classes and Standards of Planning Construction Land[S]. Beijing: China Architecture & Building Press, 2011
    [18]
    张景秋, 贾磊, 孟斌.北京城市办公活动空间集聚区研究[J].地理研究, 2010, 29(4):675-682 doi: 10.13249/j.cnki.sgs.2015.02.151

    Zhang Jingqiu, Jia Lei, Meng Bin. A Study on Office Activities Cluster in Beijing City[J]. Geographical Research, 2010, 29(4):675-682 doi: 10.13249/j.cnki.sgs.2015.02.151
  • Related Articles

    [1]SHI Pengcheng, LI Jiayuan, LIU Xinyi, ZHANG Yongjun. Indoor Cylinders Guided LiDAR Global Localization and Loop Closure Detection[J]. Geomatics and Information Science of Wuhan University, 2024, 49(7): 1088-1099. DOI: 10.13203/j.whugis20220761
    [2]WANG Fuhong, LUAN Mengjie, CHENG Yuxin, ZHU Haoqi, ZHAO Guangyue, ZHANG Wanwei. Smartphone GNSS/MEMS IMU Tightly-Coupled Integration Positioning Method for Vehicular Navigation in Urban Conditions[J]. Geomatics and Information Science of Wuhan University, 2023, 48(7): 1106-1116. DOI: 10.13203/j.whugis20230010
    [3]ZHANG Xiaohong, TAO Xianlu, WANG Yingzhe, LIU Wanke, ZHU Feng. MEMS-Enhanced Smartphone GNSS High-Precision Positioning for Vehicular Navigation in Urban Conditions[J]. Geomatics and Information Science of Wuhan University, 2022, 47(10): 1740-1749. DOI: 10.13203/j.whugis20220611
    [4]LIU Jingbin, ZHAO Zhibo, HU Ningsong, HUANG Gege, GONG Xiaodong, YANG Sheng. Summary and Prospect of Indoor High-Precision Positioning Technology[J]. Geomatics and Information Science of Wuhan University, 2022, 47(7): 997-1008. DOI: 10.13203/j.whugis20220029
    [5]WANG Yingzhe, TAO Xianlu, ZHU Feng, LIU Wanke, ZHANG Xiaohong, WU Mingkui. High Accuracy Differential Positioning with Smartphone GNSS Raw Measurements[J]. Geomatics and Information Science of Wuhan University, 2021, 46(12): 1941-1950. DOI: 10.13203/j.whugis20210280
    [6]LUO Huan, WENG Duojie, CHEN Wu. An Improved Shadow Matching Method for Smartphone Positioning[J]. Geomatics and Information Science of Wuhan University, 2021, 46(12): 1907-1915. DOI: 10.13203/j.whugis20210275
    [7]LIU Wanke, TAO Xianlu, ZHANG Chuanming, YAO Yibin, WANG Fuhong, JIA Hailu, LOU Yidong. Pedestrian Indoor and Outdoor Seamless Positioning Technology and Prototype System Based on Cloud-End Collaboration of Smartphone[J]. Geomatics and Information Science of Wuhan University, 2021, 46(12): 1808-1818. DOI: 10.13203/j.whugis20210310
    [8]GUO Fei, WU Weiwang, ZHANG Xiaohong, LIU Wanke. Realization and Precision Analysis of Real-Time Precise Point Positioning with Android Smartphones[J]. Geomatics and Information Science of Wuhan University, 2021, 46(7): 1053-1062. DOI: 10.13203/j.whugis20200527
    [9]BI Jingxue, ZHEN Jie, YAO Guobiao, SANG Wengang, NING Yipeng, GUO Qiuying. Improved Finite State Machine Step Detection Algorithm for Smartphone[J]. Geomatics and Information Science of Wuhan University. DOI: 10.13203/j.whugis20200186
    [10]WANG Fuhong, CHENG Yuxin, ZHAO Guangyue, ZHANG Wanwei. Estimate the Mounting Angles of the IMU for the Smartphone-Based Vehicular GNSS/MEMS IMU Integrated System[J]. Geomatics and Information Science of Wuhan University. DOI: 10.13203/j.whugis20230381

Catalog

    Article views (4234) PDF downloads (757) Cited by()
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return