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Identification and Characterization of Production–Living–Ecological Space in a Central Urban Area Based on POI Data: A Case Study for Wuhan, China

Author

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  • Chun Fu

    (School of Management, Nanchang University, Nanchang 330031, China)

  • Xiaoqiang Tu

    (School of Management, Nanchang University, Nanchang 330031, China)

  • An Huang

    (School of Architecture, Tsinghua University, Beijing 100084, China)

Abstract

Cities are the main carriers of high population agglomeration and socio-economic activities and are also the areas where contradictions among production, living, and ecological space are concentrated. Effective identification of production–living–ecological space is conducive to the balanced and sustainable development of urban space. First, this paper analyzes the formation mechanism and connotation of urban production–living–ecological space and constructs the classification system of point-of-interest (POI) data. Then, it identifies the production–living–ecological space in the central urban area of Wuhan effectively by using the analytic hierarchy process, spatial analysis method, and the quadrat proportion method and verifies the accuracy of production–living–ecological space by the sampling verification method. Last but not least, it adopts spatial auto-correlation analysis and Geo-detector to reveal spatial heterogeneity and its driving factors. The results indicate that: (1) The overall accuracy of the identification accuracy test of production–living–ecological space in Wuhan is 92.86%. (2) There is a significant spatial correlation among production space, living space, and ecological space in the central urban area of Wuhan with living space being the dominant space and production space the secondary space intersected and embedded in the north and south banks of the Yangtze River. (3) Results of the analysis of the driving factor show that elements comprising life services, corporate enterprises, and scenic spots play a leading role in realizing the living space, the production space, and the ecological space, respectively, and the interactions between these elements have a significant driving effect on the three types of space. The results prove that POI big data are more scientific and practical in urban spatial planning, and it can provide a useful reference for the sustainable development of spatial planning.

Suggested Citation

  • Chun Fu & Xiaoqiang Tu & An Huang, 2021. "Identification and Characterization of Production–Living–Ecological Space in a Central Urban Area Based on POI Data: A Case Study for Wuhan, China," Sustainability, MDPI, vol. 13(14), pages 1-25, July.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:14:p:7691-:d:591462
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    References listed on IDEAS

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    1. Liu, G.Y. & Yang, Z.F. & Chen, B. & Zhang, Y., 2011. "Ecological network determination of sectoral linkages, utility relations and structural characteristics on urban ecological economic system," Ecological Modelling, Elsevier, vol. 222(15), pages 2825-2834.
    2. Guido Marseglia & Carlo Maria Medaglia & Francisco A. Ortega & Juan A. Mesa, 2019. "Optimal Alignments for Designing Urban Transport Systems: Application to Seville," Sustainability, MDPI, vol. 11(18), pages 1-14, September.
    3. Bantis, Thanos & Haworth, James, 2020. "Assessing transport related social exclusion using a capabilities approach to accessibility framework: A dynamic Bayesian network approach," Journal of Transport Geography, Elsevier, vol. 84(C).
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    Cited by:

    1. Lanyi Wei & Yanjun Zhang & Lingzhi Wang & Zilang Cheng & Xuying Wu, 2022. "Obstacle Indicators Diagnosis and Advantage Functions Zoning Optimization Based on “Production-Living-Ecological” Functions of National Territory Space in Jilin Province," Sustainability, MDPI, vol. 14(7), pages 1-23, April.
    2. Mingyan Ni & Yindi Zhao & Caihong Ma & Wenzhi Jiang & Yanmei Xie & Xiaolin Hou, 2023. "Spatial Identification and Change Analysis of Production-Living-Ecological Space Using Multi-Source Geospatial Data: A Case Study in Jiaodong Peninsula, China," Land, MDPI, vol. 12(9), pages 1-27, September.
    3. Xiaoqiang Tu & Chun Fu & An Huang & Hailian Chen & Xing Ding, 2022. "DBSCAN Spatial Clustering Analysis of Urban “Production–Living–Ecological” Space Based on POI Data: A Case Study of Central Urban Wuhan, China," IJERPH, MDPI, vol. 19(9), pages 1-21, April.
    4. Yingzi Chen & Yaqi Hu & Lina Lai, 2022. "Demography-Oriented Urban Spatial Matching of Service Facilities: Case Study of Changchun, China," Land, MDPI, vol. 11(10), pages 1-22, September.
    5. Rong Guo & Xiaochen Wu & Tong Wu & Chao Dai, 2023. "Spatial–Temporal Pattern Characteristics and Impact Factors of Carbon Emissions in Production–Living–Ecological Spaces in Heilongjiang Province, China," Land, MDPI, vol. 12(6), pages 1-19, May.
    6. Yanzhen Hou & Zhenlong Zhang & Yuerong Wang & Honghu Sun & Chang Xu, 2022. "Function Evaluation and Coordination Analysis of Production–Living–Ecological Space Based on the Perspective of Type–Intensity–Connection: A Case Study of Suzhou, China," Land, MDPI, vol. 11(11), pages 1-21, November.
    7. Xiaowen Zhou & Hongwei Li & Huili Zhang & Rongrong Zhang & Huan Li, 2022. "A Study on the Cognition of Urban Spatial Image at Community Scale: A Case Study of Jinghu Community in Zhengzhou City," Land, MDPI, vol. 11(10), pages 1-23, September.

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