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Integrating Dark Sky Conservation into Sustainable Regional Planning: A Site Suitability Evaluation for Dark Sky Parks in the Guangdong–Hong Kong–Macao Greater Bay Area

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  • Deliang Fan

    (Guangzhou Urban Planning & Design Survey Research Institute Co., Ltd., Guangzhou 510060, China
    Collaborative Innovation Center for Natural Resources Planning and Marine Technology of Guangzhou, Guangzhou 510060, China
    Guangdong Enterprise Key Laboratory for Urban Sensing, Monitoring and Early Warning, Guangzhou 510060, China
    These authors contribute equally to this work.)

  • Zidian Chen

    (School of Architecture and Urban Planning, Guangdong University of Technology, Guangzhou 510090, China
    These authors contribute equally to this work.)

  • Yang Liu

    (Guangzhou Urban Planning & Design Survey Research Institute Co., Ltd., Guangzhou 510060, China
    Collaborative Innovation Center for Natural Resources Planning and Marine Technology of Guangzhou, Guangzhou 510060, China
    Guangdong Enterprise Key Laboratory for Urban Sensing, Monitoring and Early Warning, Guangzhou 510060, China)

  • Ziwen Huo

    (Guangzhou Urban Planning & Design Survey Research Institute Co., Ltd., Guangzhou 510060, China
    Collaborative Innovation Center for Natural Resources Planning and Marine Technology of Guangzhou, Guangzhou 510060, China
    Guangdong Enterprise Key Laboratory for Urban Sensing, Monitoring and Early Warning, Guangzhou 510060, China)

  • Huiwen He

    (Guangzhou Urban Planning & Design Survey Research Institute Co., Ltd., Guangzhou 510060, China
    Collaborative Innovation Center for Natural Resources Planning and Marine Technology of Guangzhou, Guangzhou 510060, China
    Guangdong Enterprise Key Laboratory for Urban Sensing, Monitoring and Early Warning, Guangzhou 510060, China)

  • Shijie Li

    (School of Architecture and Urban Planning, Guangdong University of Technology, Guangzhou 510090, China)

Abstract

Dark skies, a vital natural and cultural resource, have been increasingly threatened by light pollution due to rapid urbanization, leading to ecological degradation and biodiversity loss. As a key strategy for sustainable regional development, dark sky parks (DSPs) not only preserve nocturnal environments but also enhance livability by balancing urban expansion and ecological conservation. This study develops a novel framework for evaluating DSP suitability, integrating ecological and socio-economic dimensions, including the resource base (e.g., nighttime light levels, meteorological conditions, and air quality) and development conditions (e.g., population density, transportation accessibility, and tourism infrastructure). Using the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) as a case study, we employ Delphi expert consultation, GIS spatial analysis, and multi-criteria decision-making to identify optimal DSP locations and prioritize conservation zones. Our key findings reveal the following: (1) spatial heterogeneity in suitability, with high-potential zones being concentrated in the GBA’s northeastern, central–western, and southern regions; (2) ecosystem advantages of forests, wetlands, and high-elevation areas for minimizing light pollution; (3) coastal and island regions as ideal DSP sites due to the low light interference and high ecotourism potential. By bridging environmental assessments and spatial planning, this study provides a replicable model for DSP site selection, offering policymakers actionable insights to integrate dark sky preservation into sustainable urban–regional development strategies. Our results underscore the importance of DSPs in fostering ecological resilience, nighttime tourism, and regional livability, contributing to the broader discourse on sustainable landscape planning in high-urbanization contexts.

Suggested Citation

  • Deliang Fan & Zidian Chen & Yang Liu & Ziwen Huo & Huiwen He & Shijie Li, 2025. "Integrating Dark Sky Conservation into Sustainable Regional Planning: A Site Suitability Evaluation for Dark Sky Parks in the Guangdong–Hong Kong–Macao Greater Bay Area," Land, MDPI, vol. 14(8), pages 1-19, July.
  • Handle: RePEc:gam:jlands:v:14:y:2025:i:8:p:1561-:d:1712933
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    References listed on IDEAS

    as
    1. Xiaoxiang Tang & Cheng Zou & Chang Shu & Mengqing Zhang & Huicheng Feng, 2024. "Research on Site Selection Planning of Urban Parks Based on POI and Machine Learning—Taking Guangzhou City as an Example," Land, MDPI, vol. 13(9), pages 1-18, August.
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