Cities beyond proximity DOI
David J. Hill, Matteo Bruno, Hygor P. M. Melo

et al.

Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Journal Year: 2024, Volume and Issue: 382(2285)

Published: Nov. 13, 2024

The concept of ‘proximity-based cities’ has gained attention as a new urban organizational model. Most prominently, the 15-minute city contends that cities can function more effectively, equitably and sustainably if essential, everyday services key amenities are within walk or cycle. However, focusing solely on travel time risks overlooking disparities in service quality, proximity paradigm tends to emphasize mere presence an element location rather than bringing up complex questions identity, diversity, value relationships. Transitioning value-based by considering just enhance local resilience democracy. Fostering bottom–up initiatives create culture care value, while predominantly top–down governing strategies lead large inequalities. Balancing these approaches maximize resilience, health sustainability. This equilibrium potential accompany sustainable growth, encouraging creation innovative solutions reducing article is part theme issue ‘Co-creating future: participatory digital governance’.

Language: Английский

How does spatial structure affect psychological restoration? A method based on graph neural networks and street view imagery DOI
Haoran Ma, Yan Zhang, Pengyuan Liu

et al.

Landscape and Urban Planning, Journal Year: 2024, Volume and Issue: 251, P. 105171 - 105171

Published: Aug. 1, 2024

Language: Английский

Citations

10
Evaluating and Comparing Human Perceptions of Streets in Two Megacities by Integrating Street-View Images, Deep Learning, and Space Syntax DOI Creative Commons
Yalun Lei, Hongtao Zhou, Liang Xue

et al.

Buildings, Journal Year: 2024, Volume and Issue: 14(6), P. 1847 - 1847

Published: June 18, 2024

Street quality plays a crucial role in promoting urban development. There is still no consensus on how to quantify human street perception large scale or explore the relationship between and composition elements. This study investigates new approach for evaluating comparing accessibility Shanghai Chengdu, two megacities with distinct geographic characteristics, using street-view images, deep learning, space syntax. The result indicates significant differences Chengdu. In there curvilinear distribution of highest positive perceptions along riverfront radioactive spatial negative ring road main roads. displays fragmented cross-aggregation polycentric streets perceptions. Thus, it reasonable hypothesize that closely correlates planning construction process streets. Moreover, we used multiple linear regression explain results show buildings trees, pavement, grass Chengdu were positively associated Walls both consistent correlation other perceptions, are most likely contribute low quality. Ceilings but not major elements while opposite above results. Our research can provide cost-effective rapid solution large-scale, highly detailed assessments inform human-scale planning.

Language: Английский

Citations

4
Research on the Factors Influencing the Spatial Quality of High-Density Urban Streets: A Framework Using Deep Learning, Street Scene Images, and Principal Component Analysis DOI Creative Commons

Kerun Li

Land, Journal Year: 2024, Volume and Issue: 13(8), P. 1161 - 1161

Published: July 29, 2024

Urban space constitutes a complex system, the quality of which directly impacts life for residents. In high-density cities, factors such as green coverage in street spaces, color richness, and accessibility services are crucial elements affecting daily life. Moreover, application advanced technologies, deep learning combined with view image analysis, has certain limitations, especially context urban streets. This study focuses on within fabric Macau Peninsula, exploring characteristics environments. By leveraging imagery multi-source data, this research employs principal component analysis (PCA) deep-learning techniques to conduct comprehensive evaluation key indicators quality. Utilizing semantic segmentation ArcGIS technology, quantifies 16 indicators. The findings reveal significant variations service-related DLS, ALS, DCE, MFD, reflecting uneven distribution service facilities. index richness index, along other indicators, notably influenced by tourism commercial activities. Correlation indicates presence land-use conflicts between spaces facilities settings. Principal uncovers diversity complexity cluster categorizing them into four distinct groups, representing different combinations spatial characteristics. innovatively provides quantitative assessment quality, emphasizing importance considering multiple achieve coordinated development enhance results offer new perspectives methodologies

Language: Английский

Citations

4
Constructing child-friendly cities: Comprehensive evaluation of street-level child-friendliness using the method of empathy-based stories, street view images, and deep learning DOI
Yihong Yang, Qi Wang,

Dongchen Wu

et al.

Cities, Journal Year: 2024, Volume and Issue: 154, P. 105385 - 105385

Published: Aug. 20, 2024

Language: Английский

Citations

4
Predicting the Impact of Integrated Audio-Visual Environments on Perceived Restorative Benefits Across Different Park types: A Field Study Based on Seven Parks in Hangzhou, China DOI
Wenbo Li, Yang Liu

Urban forestry & urban greening, Journal Year: 2024, Volume and Issue: unknown, P. 128517 - 128517

Published: Sept. 1, 2024

Language: Английский

Citations

4
Combined effects of the visual-thermal environment on restorative benefits in hot outdoor public spaces: A case study in Shenzhen, China DOI
Wen Dong, Donghui Dai, Liu Mei

et al.

Building and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 112690 - 112690

Published: Feb. 1, 2025

Language: Английский

Citations

0
How far and discernible are public toilets? A city-scale study using spatial analytics and deep learning in Nanjing, China DOI Creative Commons

Dai Yue,

Lifei Wang, Zhen Xu

et al.

Journal of Urban Management, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

Citations

0
Measuring and understanding changes in the physical built environment of cities with street view images DOI Creative Commons
Yang Zhou, Jean‐Claude Thill, Xingjian Liu

et al.

Urban Informatics, Journal Year: 2025, Volume and Issue: 4(1)

Published: Feb. 24, 2025

Language: Английский

Citations

0
Bridging the Green Space Divide: A Big Data-Driven Analysis of Park Accessibility Inequities in Chinese Megacities Using Enhanced 3SFCA Modeling DOI Open Access
Yiwen Sun, Hang Li,

Xianhua Guo

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(5), P. 2059 - 2059

Published: Feb. 27, 2025

This study enhances our understanding of urban park accessibility and social equity through a novel methodological framework in Chengdu, China. By improving the three-step floating catchment area (3SFCA) method with space syntax metrics multi-modal transportation analysis, we identify spatial disparities green access. Our methodology, validated Baidu heat map data, demonstrates improved accuracy estimating population demand patterns. Key findings include: (1) The enhanced 3SFCA outperforms traditional approaches predicting accessibility, providing reliable evidence for planning; (2) significant exist across modes, particularly affecting non-motorized transport users; (3) newly developed areas show greater access inequities than established neighborhoods; (4) important mismatches between vulnerable distributions. research provides targeted recommendations reducing all residents, benefiting children elderly populations rapidly urbanizing contexts.

Language: Английский

Citations

0
Integrating Street View Images, Deep Learning, and sDNA for Evaluating University Campus Outdoor Public Spaces: A Focus on Restorative Benefits and Accessibility DOI Creative Commons

Tingjin Wu,

Deqing Lin,

Yi Chen

et al.

Land, Journal Year: 2025, Volume and Issue: 14(3), P. 610 - 610

Published: March 13, 2025

The mental health of university students has received much attention due to the various pressures studies, life, and employment. Several studies have confirmed that campus public spaces contain multiple restorative potentials. Yet, space is still not ready meet students’ new need for percetions. Renewal practices integrate multi-issues are becoming more important, further clarification measurement methods optimization pathways also needed. This study applied semantic segmentation technique deep learning model extract feature indicators outdoor based on street view image (SVI) data. subjective evaluation small-scale SVIs was obtained using perceived scale-11 (PRS-11) questionnaire. On this basis, benefit models were established, including explanatory predictive models. used Pearson’s correlation linear regression analysis identify key affecting benefits, XGBoost 1.7.3 algorithm predict scores scale. accessibility results from sDNA then overlayed form a comprehensive assessment matrix restoration benefits dimensions “areas with potential”. In way, three types spatial (LRB-HA, HRB-LA, LRB-LA) sequential orders temporal (short-term, medium-term, long-term) combined propose dual control accessibility. provides methodological guidelines empirical data regeneration promotes efficiency. addition, it can offer positive references neighborhood-scale urban design sustainable development.

Language: Английский

Citations

0