Exploring the Spatial Pattern of Urban Block Development Based on POI Analysis: A Case Study in Wuhan, China

被引:13
|
作者
Xu, Hailing [1 ]
Zhu, Jianghong [1 ]
Wang, Zhanqi [1 ]
机构
[1] China Univ Geosci, Sch Publ Adm, Wuhan 430074, Peoples R China
基金
中国国家自然科学基金;
关键词
POI data; diversity index; kernel density analysis; spatial pattern of urban block development; Wuhan city; KERNEL DENSITY-ESTIMATION; NETWORK;
D O I
10.3390/su11246961
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As a kind of geospatial big data, point of interest (POI) with useful information has become a hot research topic. Compared with traditional methods, big data has great potential in developing a more accurate method for identifying the urban spatial pattern. This paper uses diversity index and kernel density analysis of POI data on several types of urban infrastructure to investigate the identification of urban block development stages in Wuhan, and divides them into the primary, growth, and mature stage. Its accuracy is verified by exploring urban micro-centers. Results show that: (1) the spatial pattern of urban blocks in Wuhan presents the distribution of "mature blocks concentrated like a core, growth blocks distributed like two wings, and primary blocks with wide range distributed surround"; (2) areas with more connected construction land and streets with better socio-economic status tend to have a higher level of maturity, vice versa; (3) balancing the number of micro-centers at different stages is beneficial to promote the flattened urban development of Wuhan in the future. The research proves that this method is feasible, and it is also applicable to the study of urban spatial pattern in other cities.
引用
下载
收藏
页数:25
相关论文
共 50 条
  • [21] Complex Spatial Morphology of Urban Housing Price Based on Digital Elevation Model: A Case Study of Wuhan City, China
    Zhang, Zuo
    Lu, Xinhai
    Zhou, Min
    Song, Yan
    Luo, Xiang
    Kuang, Bing
    SUSTAINABILITY, 2019, 11 (02)
  • [22] Identification method and empirical study of urban industrial spatial relationship based on POI big data: a case of Shenyang City, China
    Xue, Bing
    Xiao, Xiao
    Li, Jingzhong
    GEOGRAPHY AND SUSTAINABILITY, 2020, 1 (02) : 152 - 162
  • [23] Research on the Spatial Pattern of the Logistics Industry Based on POI Data: A Case Study of Zhengzhou City
    Zhao, Xiuyan
    Miao, Changhong
    SUSTAINABILITY, 2023, 15 (21)
  • [24] Quantifying the spatiality of urban leisure venues in Wuhan, Central China - GIS-based spatial pattern metrics
    Jing, Ying
    Liu, Yaolin
    Cai, Enxiang
    Liu, Yi
    Zhang, Yang
    SUSTAINABLE CITIES AND SOCIETY, 2018, 40 : 638 - 647
  • [25] Spatial pattern and influencing factors of tourism based on POI data in Chengdu, China
    Wen Liang
    Yahaya Ahmad
    Hazrina Haja Bava Mohidin
    Environment, Development and Sustainability, 2024, 26 : 10127 - 10143
  • [26] Spatial pattern and influencing factors of tourism based on POI data in Chengdu, China
    Liang, Wen
    Ahmad, Yahaya
    Mohidin, Hazrina Haja Bava
    ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2024, 26 (04) : 10127 - 10143
  • [27] The spatial pattern and influence mechanism of urban vitality: A case study of Changsha, China
    Xia, Xiaojiang
    Zhang, Yang
    Zhang, Yue
    Rao, Tiechuan
    FRONTIERS IN ENVIRONMENTAL SCIENCE, 2022, 10
  • [28] Multi-Scenario Simulation of Urban Growth under Integrated Urban Spatial Planning: A Case Study of Wuhan, China
    Wang, Haofeng
    Liu, Yaolin
    Zhang, Guangxia
    Wang, Yiheng
    Zhao, Jun
    SUSTAINABILITY, 2021, 13 (20)
  • [29] Causal inference of urban heat island effect and its spatial heterogeneity: A case study of Wuhan, China
    Zhong, Yingqiang
    Li, Shaochun
    Liang, Xun
    Guan, Qingfeng
    Sustainable Cities and Society, 2024, 115
  • [30] Spatial and Temporal Evolution of the Characteristics of Spatially Aggregated Elements in an Urban Area: A Case Study of Wuhan, China
    Sun, Zhihao
    Kang, Dezhi
    Jiao, Hongzan
    Yang, Ya
    Xue, Wei
    Wu, Hao
    Liu, Lingbo
    Su, Yuwei
    Peng, Zhenghong
    Kainz, Wolfgang
    Arsanjani, Jamal Jokar
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2023, 12 (11)