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Evaluation of Urban Green Space Supply and Demand Based on Mobile Signal Data: Taking the Central Area of Shenyang City as an Example

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  • Yukuan Dong

    (School of Architecture and Urban Planning, Shenyang Jianzhu University, Shenyang 110168, China
    Key Laboratory of City Informatoin and Spatial Perception, Shenyang 110168, China)

  • Xi Chen

    (School of Architecture and Urban Planning, Shenyang Jianzhu University, Shenyang 110168, China
    Key Laboratory of City Informatoin and Spatial Perception, Shenyang 110168, China
    Department of Art and Design, Dalian Art College, Dalian 116120, China)

  • Dongyang Lv

    (Shenyang Geotechnical Investigation & Surveying Research Institute Co., Ltd., Shenyang 110058, China)

  • Qiushi Wang

    (School of Architecture and Urban Planning, Shenyang Jianzhu University, Shenyang 110168, China
    Key Laboratory of City Informatoin and Spatial Perception, Shenyang 110168, China)

Abstract

The degree of coordination between the supply and demand for urban green spaces serves as a vital metric for evaluating urban ecological development and the well-being of residents. An essential principle in assessing this coordination is the precise quantification of both the demand and supply of green spaces, as well as the differential representation of their spatiotemporal structures. This study utilizes the entropy weight method (EWM) and principal component analysis (PCA) to comprehensively measure supply indicators for green space quantity and quality in the central urban area of Shenyang, China. To establish reliable and quantifiable demand indicators, mobile signaling spatial-temporal data are corrected by incorporating static population cross-sectional data. The Gaussian two-step floating catchment area method (Ga2SFCA) is employed to calculate the accessibility of green spaces in each community with ArcGIS 10.2 software, while the Gini coefficient is utilized to assess the equity of green space distribution within the study area. This study employs location entropy to determine the levels of supply and demand for green spaces in each subdistrict. Furthermore, the priority of community-scale green space regulation is accurately determined by balancing vulnerable areas of green space supply and replenishing green space resources for the ageing population. The findings suggest a Gini coefficient of 0.58 for the supply and demand of green spaces in Shenyang’s central metropolitan region, indicating a relatively low level of equalization in overall green space allocation. Based on location entropy, the classification of supply and demand at the street level yields the following outcomes: balanced areas comprise 21.98%, imbalanced areas account for 26.37%, and highly imbalanced regions represent 51.65%. After eliminating the balanced regions, the distribution of the elderly population is factored in, highlighting the spatial distribution and proportions of communities with distinct regulatory priorities: Level 1 (S1) constitutes 7.4%, Level 2 (S2) accounts for 60.9%, and Level 3 (S3) represents 31.7%. Notably, the communities in the S1 category exhibit spatial distribution characteristics of aggregation within the inner ring and the northern parts of the third ring. This precise identification of areas requiring urgent regulation and the spatial distribution of typical communities can provide reliable suggestions for prioritizing green space planning in an age-friendly city.

Suggested Citation

  • Yukuan Dong & Xi Chen & Dongyang Lv & Qiushi Wang, 2023. "Evaluation of Urban Green Space Supply and Demand Based on Mobile Signal Data: Taking the Central Area of Shenyang City as an Example," Land, MDPI, vol. 12(9), pages 1-20, September.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:9:p:1742-:d:1235360
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    References listed on IDEAS

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    Cited by:

    1. Tianlin Zhai & Yuanbo Ma & Ying Fang & Mingyuan Chang & Longyang Huang & Ziyi Ma & Ling Li & Chenchen Zhao, 2024. "Research on the Optimization of Urban Ecological Infrastructure Based on Ecosystem Service Supply, Demand, and Flow," Land, MDPI, vol. 13(2), pages 1-25, February.
    2. Hancheng Xia & Rui Yin & Tianyu Xia & Bing Zhao & Bing Qiu, 2024. "People-Oriented: A Framework for Evaluating the Level of Green Space Provision in the Life Circle from a Supply and Demand Perspective: A Case Study of Gulou District, Nanjing, China," Sustainability, MDPI, vol. 16(3), pages 1-18, January.
    3. Xi Chen & Yukuan Dong & Xiaoshi Wang & Qiushi Wang, 2024. "Optimization of an Urban Microgreen Space Distribution Based on the PS-ACO Algorithm: A Case Study of Shenyang, China," Land, MDPI, vol. 13(10), pages 1-22, September.
    4. Xin Wang & Xiwen Bao & Ziao Ge & Jiayao Xi & Yinghui Zhao, 2024. "Identification and Redevelopment of Inefficient Residential Landuse in Urban Areas: A Case Study of Ring Expressway Area in Harbin City of China," Land, MDPI, vol. 13(8), pages 1-24, August.

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