Identification of Urban Functional Areas Based on POI Data: A Case Study of the Guangzhou Economic and Technological Development Zone

被引:130
作者
Hu, Yunfeng [1 ]
Han, Yueqi [1 ,2 ]
机构
[1] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
来源
SUSTAINABILITY | 2019年 / 11卷 / 05期
关键词
point of interest; data mining; function identification; spatial distribution; regional planning; CHINA;
D O I
10.3390/su11051385
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Functional areas are the basic spatial units in which cities or development zones implement urban plans and provide functions. Internet map big data technology provides a new method for the identification and spatial analysis of functional areas. Based on the POI (point of interest) data from AMap (a map application of AutoNavi) from 2017, this paper proposes an urban functional areas recognition and analysis method based on the frequency density and the ratio of POI function types. It takes the Guangzhou Economic and Technological Development Zone as a case study to analyze the main function and spatial distribution characteristics of the detailed functional areas. The research shows the following: (1) The POI frequency density index and the function type ratio can effectively distinguish the functions of the grid units and analyze the spatial distribution characteristics of a complex functional area. (2) The single functional area is the most common area type in the Guangzhou Economic and Technological Development Zone. The largest proportion of all areas is allocated to traditional manufacturing industry functional areas, followed by high-tech enterprises, catering and entertainment, real estate, and education and health care, in descending order. The smallest proportion is allocated to finance and insurance functional areas. (3) The current layout of the functional areas in the Guangzhou Economic and Technological Development Zone conforms to the overall requirements and planning objectives of the central and local government. The layout and agglomeration of different blocks within the economic development zone are consistent with local industry's target orientation and development history.
引用
收藏
页数:15
相关论文
共 51 条
[1]  
[Anonymous], 2006, OUTL 11 5 YEAR PLAN
[2]  
[Anonymous], 2017, SOM OP GEN OFF STAT
[3]  
[Anonymous], 2015, ACTA GEOD CARTOGR SI
[4]  
AutoNavi, AM AP
[5]   Comparison of Approaches for Urban Functional Zones Classification Based on Multi-Source Geospatial Data: A Case Study in Yuzhong District, Chongqing, China [J].
Cao, Kai ;
Guo, Hui ;
Zhang, Ye .
SUSTAINABILITY, 2019, 11 (03)
[6]   Effective successive POI recommendation inferred with individual behavior and group preference [J].
Chen, Jialiang ;
Li, Xin ;
Cheung, William K. ;
Li, Kan .
NEUROCOMPUTING, 2016, 210 :174-184
[7]   Urban Land Intensive Use Evaluation Study Based on Nighttime LightA Case Study of the Yangtze River Economic Belt [J].
Cheng, Xin ;
Shao, Hua ;
Li, Yang ;
Shen, Chao ;
Liang, Peipei .
SUSTAINABILITY, 2019, 11 (03)
[8]  
[陈蔚珊 Chenweishan], 2016, [地理研究, Geographical Research], V35, P703
[9]   基于POI数据的城市功能区定量识别及其可视化 [J].
池娇 ;
焦利民 ;
董婷 ;
谷岩岩 ;
马雅兰 .
测绘地理信息, 2016, 41 (02) :68-73
[10]   Network-based functional regions [J].
Farmer, Carson J. Q. ;
Fotheringham, A. Stewart .
ENVIRONMENT AND PLANNING A-ECONOMY AND SPACE, 2011, 43 (11) :2723-2741