The development of cities and regions emerges from the complex associations at various spatial levels, highlighting the importance of a multi-scale approach to analyzing regional urban networks. This study attempts to establish a new analysis framework encompassing national, regional, and local dimensions by employing a population flow network in the Yangtze River Delta in China. It explores the inter-city connections and spatial structures of regional urban networks as well as the correlations and differentiations of urban functions under multi-scale interaction. The results indicate that: (1) Regional network demonstrates notable multi-scale interactions with an explicit hierarchical structure; (2) The roles and positions of different cities vary significantly across scales due to economic, administrative, locational, and transportation differences; (3) Different city types can drive their evolution by navigating through rescaling in a diverse multi-scale environment; (4) A positive correlation is observed when comparing the functional behaviors of cities across various scales. This study provides insights for cities to identify their strategic roles and adapt development strategies within the wider network framework, offering theoretical and practical contributions to multi-scale urban networks analysis.

Walking is the primary mode of reaching metro stations, yet the quality of pedestrian networks around these stations has not been well researched. Considering the objective physical characteristics of pedestrian networks and the subjective assessments of walkers on the routes, this study developed an evaluation model that integrated the Analytic Hierarchy Process and Entropy Weight Method with human–machine adversarial scoring and cosine similarity to validate the reliability. Nineteen indicators concerning four fundamental criteria, including accessibility, convenience, safety, and comfort, were applied with data acquired from eight stations in Tianjin, China. Results reveal that accessibility and safety indicators weigh more than convenience and comfort indicators. The quality of pedestrian networks around the public-service and comprehensive stations scores higher than that around residential stations, while walking environment quality near commercial stations shows significant disparities. These findings highlight the importance of prioritizing accessibility and safety while enhancing convenience and comfort in the renewal of the pedestrian network in Tianjin. The assessment model provides a valuable tool for urban policymakers and planners, enabling the formulation of sound pedestrian-network policies, facilitating higher-quality walking access and egress trips to stations, and encouraging transit-oriented development.

Cycling significantly contributes to improving metro accessibility; however, the quality of bicycle environments surrounding metro stations remains insufficiently studied. This study develops a criteria–indicators assessment framework that incorporates both objective characteristics of bicycle infrastructure and subjective perceptions of bicycle access to metro stations. The framework consists of four primary criteria—accessibility, convenience, safety, and comfort—along with eighteen sub-level indicators. Taking central Tianjin as the study area, the study evaluated the cycling environment quality around eight representative metro stations by employing information entropy and the analytic hierarchy process, with cosine similarity used to compare the outcomes against human–machine adversarial scoring result to ensure analytical robustness. The findings reveal substantial disparities in cycling infrastructure, with safety and accessibility exhibiting higher scores than convenience and comfort. Additionally, cycling environment quality is higher around comprehensive and public-service stations compared to residential stations, while commercial stations exhibit the lowest quality. The study underscores the necessity of expanding protected bike lanes, enhancing route directness, and improving parking and wayfinding facilities to promote cycling as an effective first- and last-mile metro access mode.

With increasing concerns over climate change and air pollution, sustainable transportation has become a critical component of modern city planning. Bike-sharing systems have emerged as an eco-friendly alternative to motorized transport, contributing to energy conservation and emission reduction. To elaborate on bike-sharing’s contribution to urban sustainable development, this study conducts a quantitative analysis of its environmental benefits through a case study of the Bluebikes program in the Boston area, using a longitudinal dataset of 20.07 million bike trips from January 2015 to December 2024, with data between January 2020 and December 2021 excluded. A combination of Scheiner’s model and Multinomial Logit model was adopted to evaluate the substitution of Bluebikes trips, an optimized Seasonal Autoregressive Integrated Moving Average (SARIMA) model was employed to predict future usage, while energy savings were calculated by estimating reductions in gasoline and diesel consumption. The findings reveal that during the analyzed period, Bluebikes trips saved 2616.44 tons of oil equivalent and reduced CO₂ and NO_X emissions by 7614.96 and 16.43 tons, respectively. Furthermore, based on the historical trends, it is forecasted that the Bluebikes program will annually save an average of 723.66 tons of oil equivalent and decrease CO₂ and NO_X emissions by 2422.65 and 4.52 tons between 2025 and 2027. The results highlight the substantial environmental impact of Bluebikes and support policies that encourage their usage.