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Distribution of Urban Blue and Green Space in Beijing and Its Influence Factors

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  • Haoying Wang

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    School of Civil Engineering and Architecture, Jishou University, Hunan 427000, China)

  • Yunfeng Hu

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Li Tang

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    School of Civil Engineering and Architecture, Jishou University, Hunan 427000, China)

  • Qi Zhuo

    (School of Civil Engineering and Architecture, Jishou University, Hunan 427000, China)

Abstract

Urban blue and green space is a key element supporting the normal operation of urban landscape ecosystems and guaranteeing and improving people's lives. In this paper, 97.1k photos of Beijing were captured by using web crawler technology, and the blue sky and green vegetation objects in the photos were extracted by using the Image Cascade Network (ICNet) neural network model. We analyzed the distribution characteristics of the blue–green space area proportion index and its relationships with the background economic and social factors. The results showed the following. (1) The spatial distribution of Beijing's blue–green space area proportion index showed a pattern of being higher in the west and lower in the middle and east. (2) There was a positive correlation between the satellite remote sensing normalized difference vegetation index (NDVI) and the proportion index of green space area, but the fitting degree of geospatial weighted regression decreased with an increasing analysis scale. (3) There were differences in the relationship between the housing prices in different regions and the proportion index of blue–green space, but the spatial fitting degree of the two increased with the increase of study scale. (4) There was a negative correlation between the proportion index of blue–green space and population density, and the low-population areas per unit blue–green space were mainly distributed in the south of the city and the urban fringe areas beyond the Third Ring Road. The urban blue–green space analysis that was constructed by this study provides new aspect for urban landscape ecology study, and the results proposed here also provide support for government decision-makers to optimize urban ecological layouts.

Suggested Citation

  • Haoying Wang & Yunfeng Hu & Li Tang & Qi Zhuo, 2020. "Distribution of Urban Blue and Green Space in Beijing and Its Influence Factors," Sustainability, MDPI, vol. 12(6), pages 1-20, March.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:6:p:2252-:d:332135
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    References listed on IDEAS

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    1. Amirafshar Vaeztavakoli & Azadeh Lak & Tan Yigitcanlar, 2018. "Blue and Green Spaces as Therapeutic Landscapes: Health Effects of Urban Water Canal Areas of Isfahan," Sustainability, MDPI, vol. 10(11), pages 1-20, November.
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    2. Zhiqiao Li & Qin Liu & Yuxin Zhang & Kun Yan & Yangyang Yan & Pei Xu, 2022. "Characteristics of Urban Parks in Chengdu and Their Relation to Public Behaviour and Preferences," Sustainability, MDPI, vol. 14(11), pages 1-16, May.
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