Sena Kaynarkaya , Aslı Çekmiş , İsmail Çetin , Yusuf Hüseyin Şahin , Gözde Ünal
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引用次数: 0
Abstract
Walkability, shaped by features of built environment, contributes to healthier communities and more sustainable urban mobility. Well-designed streetscapes encourage pedestrian activity, making individuals’ perceptions of safety, accessibility, and aesthetics central to understanding walkable environments. Existing studies typically evaluate walkability through either objective spatial data or perceptual assessments based on human experiences. However, comprehensive approaches that combines both perspectives remain limited. This study presents an AI-driven framework for evaluating urban walkability by integrating objective built environment features with subjective perceptions in the context of Cittaslow-certified neighborhoods. The research employs the Segment Anything Model 2(SAM2) for high-resolution and class-agnostic segmentation of street-level imagery. It is created: “Urban Walkability Dataset” (UWD) which contains 5,440 labeled images by experts with a question set generated based on the key parameters affecting walkability. A neural network pipeline is designed to understand the underlying process. By bridging perceptual insights and objective metrics, this research contributes a replicable methodology for walkability assessment that supports human-centered urban design strategies, particularly in slow-city contexts prioritizing sustainability and quality of life.
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;