基于深度学习和多准则决策方法的城市绿色弹性评价——以广东省为例

IF 12 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
Minglong Han , Yupeng Liu
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引用次数: 0

摘要

极端气候条件给城市系统带来了巨大的环境压力。因此,确定如何评价和增强城市绿色弹性(UGR)对于实现可持续发展至关重要。本文介绍了一种结合深度学习和多准则决策(MCDM)方法的方法框架,用于评估UGR并研究其时空特征。定义了UGR的概念,并建立了相应的评价指标体系。此外,我们还使用了一个改进的基于图卷积网络和门控循环单元结构优化的评估模型来评估广东省城市的绿色弹性。通过空间异质性和城市网络分析,探讨城市绿色弹性的空间分布。我们的结果表明:首先,生态作为一种源驱动因素,对绿色弹性具有重要影响。其次,新能源渗透率、水污染压力、城市绿化和低碳基础设施对UGR的影响较大。三是广东省城市绿色韧性不断增强,北部山区绿色韧性增长较快。第四,珠江三角洲城市在基础设施和社会参与方面表现突出,而北部山区在治理方面表现突出。本文还提出了三个代表性城市的优化路径,为今后的研究提供理论基础和实践指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating urban green resilience through deep learning and multicriterion decision-making approaches: A spatiotemporal analysis of Guangdong Province
Extreme climate conditions place considerable environmental pressure on urban systems. Therefore, determining how to evaluate and enhance urban green resilience (UGR) is crucial to achieving sustainable development. This paper introduces a methodological framework that combines deep learning and multicriterion decision-making (MCDM) approaches to evaluate UGR and examine its spatiotemporal characteristics. We defined the concept of UGR and developed a corresponding evaluation index system. Additionally, we used a modified assessment model optimized by graph convolutional network and gated recurrent unit architectures to evaluate the green resilience of Guangdong Province’s cities. We conducted spatial heterogeneity and city network analyses to explore the spatial distribution of green resilience. Our results indicate the following. First, ecology has a major effect on green resilience, acting as a source-driven factor. Second, new energy penetration, water pollution pressure, urban greening, and low-carbon infrastructure considerably influence UGR. Third, the green resilience of cities in Guangdong Province is improving, with northern mountainous areas experiencing considerably high growth. Fourth, Pearl River Delta cities excel in terms of infrastructure and social engagement, whereas northern mountainous regions excel in terms of governance. This paper also outlines optimization paths for three representative cities, providing a theoretical basis and practical guidance for future studies.
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来源期刊
Sustainable Cities and Society
Sustainable Cities and Society Social Sciences-Geography, Planning and Development
CiteScore
22.00
自引率
13.70%
发文量
810
审稿时长
27 days
期刊介绍: Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including: 1. Smart cities and resilient environments; 2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management; 3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management); 4. Energy efficient, low/zero carbon, and green buildings/communities; 5. Climate change mitigation and adaptation in urban environments; 6. Green infrastructure and BMPs; 7. Environmental Footprint accounting and management; 8. Urban agriculture and forestry; 9. ICT, smart grid and intelligent infrastructure; 10. Urban design/planning, regulations, legislation, certification, economics, and policy; 11. Social aspects, impacts and resiliency of cities; 12. Behavior monitoring, analysis and change within urban communities; 13. Health monitoring and improvement; 14. Nexus issues related to sustainable cities and societies; 15. Smart city governance; 16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society; 17. Big data, machine learning, and artificial intelligence applications and case studies; 18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems. 19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management; 20. Waste reduction and recycling; 21. Wastewater collection, treatment and recycling; 22. Smart, clean and healthy transportation systems and infrastructure;
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