Spatial scale increment identification and dynamic simulation of network resilience disturbances in landscape infrastructure: A comprehensive approach for optimizing regional planning
IF 10.5 1区 工程技术Q1 CONSTRUCTION & BUILDING TECHNOLOGY
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引用次数: 0
Abstract
Human-driven material production has brought social and economic benefits. However, it has also exacerbated environmental degradation, posing considerable challenges to the functional attributes and network structures that some communities rely on and threatening their service supply. The current development model continues to compress limited landscape space, and infrastructure has become a characteristic feature of high-density cities, urgently requiring integrated solutions to plan them synergistically. Landscape Infrastructure (LI)-oriented regional planning offer the possibility of integrating social, cultural, and ecosystem services into urban planning. Therefore, this study utilized Genetic Algorithms (GA) to optimize LI distribution, combined with network node testing to assess the rationality of spatial configuration and dynamically simulated urban disturbance scenarios. Using Chongqing as a typical case, the optimized LI area increased by 47.5%, and network efficiency and connectivity indicators significantly improved. While completing the scale increment and structural stability requirements, the model calculations revealed a regional network resilience threshold of 0.36, effectively guiding priority areas for construction and protection. The study provides a replicable Landscape Infrastructure System (LIS) framework, integrating GA and network theory to develop a multi-objective optimization approach. The results support targeted spatial management policies and contribute to sustainable urban development and resilience of socio-ecological systems.
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;