Walking and running activities (W&RAs), encompassing strolling, slow walking, brisk walking, jogging, and running, hold significant importance as popular forms of exercise within urban parks. Recognized for their efficacy in promoting public health and preventing chronic diseases, understanding the nuanced impact of pathway features on W&RAs is crucial for advancing health-centric urban park planning. Based on extensive, high-frequency field observation data, we utilize multiple OLS regression models and univariate OLS regression models to investigate the relationship between urban park pathway features and variations in W&RAs, specifically examining activity density and intensity. Subsequently, we propose corresponding pathway optimization strategies. Our findings highlight the primary determinants, with vegetation coverage ratio, path type, and security facility density influencing activity density; and control value, time required to reach the nearest entrance, and pavement type influencing activity intensity. Significantly, increased vegetation coverage enhances density, while interconnected spaces and improved accessibility elevate intensity. In conclusion, our study delineates key features that merit prioritization, specifies their optimal ranges and proposes optimization design strategies for urban park pathways. By shedding light on these considerations, our research contributes valuable insights to the realm of health-oriented urban park planning and design.

Ancient canal towns in Jiangnan have become important tourist destinations due to their unique water town scenery and historical value. Creating a unique tourist image boosts these ancient towns’ competitive edge in tourism and contributes significantly to their preservation and growth. The vast amount of data from social media has become an essential source for uncovering tourism perceptions. This study takes two ancient towns in Shanghai, Zhaojialou and Fengjing, as case study areas. In order to explore and compare the destination images of the towns, in the perception of tourists and in official publicity, machine learning approaches like word embedding and K-means clustering are adopted to process the comments on Sina Weibo and publicity articles, and statistical analysis and correspondence analysis are used for comparative study. The results reveal the following: (1) Using k-means clustering, destination perceptions were categorized into 16 groups spanning three dimensions, “space, activity, and sentiment”, with the most keywords in “activity” and the fewest in “sentiment”. (2) The perception of tourists often differs significantly from the official promotional materials. Official promotions place a strong emphasis on shaping the image of ancient towns based on their historical resources, presenting a more general picture. Tourist perception, which is fragmented, highlights emerging elements and the experiential activities, along with the corresponding emotional experiences. (3) Comparing the two towns, Fengjing Ancient Town stands out, with more diverse tourist perceptions and richer emotional experiences. This underscores the effectiveness of tourism activities that use space as a media to evoke emotions, surpassing the impact of the spaces themselves.

Urban parks play a pivotal role in shaping physical activity (PA), yet our comprehension of the specific influence of park greenery remains limited. In this study, we focused on three Shanghai urban parks, conducting a comprehensive year-long on-site observation to delve into greenery’s impact on PA. By employing the hierarchical linear model analysis, we uncovered a robust correlation between internal and surrounding park greenery and PA density and diversity. Within a 400 m radius, indicators such as normalized difference vegetation index, green view ratio, Shannon’s diversity index, and color-leaf plant ratio demonstrated a negative relationship with PA density. Conversely, the green coverage ratio and green view ratio within the 400 m radius exhibited a positive link with PA density. In terms of PA diversity, factors such as green visibility rate, color-leaf plants, and green coverage ratio displayed negative associations, while the 400 m green view ratio showcased a positive impact. Notably, our study revealed a dual interplay between internal and surrounding greenery, manifesting as both collaborative and competitive dynamics that collectively shape PA. Additionally, we subjected greenery indicators to seasonal assessments, yielding insights that illuminate how urban park greenery shapes PA. These findings offer valuable guidance for future park planning and fostering environments conducive to PA.

China's growth over recent decades rapidly transformed the urban landscapes. Green spaces provide numerous health benefits including acting as nature-based solutions for climate change risks. Our study aims to track greenness trends in urban areas in China and quantify the health impact of greenness on adult mortality. In China, we mapped the urban human population distribution aged 20 and above with a 1 km grid (30 arc-second) and used satellite-based remote sensing to measure green space over time to create population-weighted normalized difference vegetation index (NDVI). We tracked changes in greenness in the urban area over time and created a spatial–temporal map. Based on counterfactual scenarios, we calculated averted deaths attributed to NDVI changes from 2000 to 2020. We analyzed and mapped 390 cities or urban areas in China, covering an urban population of nearly 500 million. We found population-weighted NDVI exhibiting an overall increase from 2000 to 2020 for most cities. Our analysis calculated urban areas that experienced decrease in urban NDVI from 2000 to 2010 could have had an estimated 9951 additional deaths annually (95% CI: 3346–18,106), while increase in NDVI from 2010 to 2020 could have averted an estimated 37,653 deaths annually (95% CI: 26,327–60,135). If the NDVI were increased to the target level in 2000 and 2010, the number of deaths would be reduced by 110,976 (95% CI: 82,010–171,561) and 118,330 (95% CI: 87,362–183,283), respectively. Greenness has increased in most urban in China since 2000. Considering the ongoing impacts of climate change and urbanization, sustained efforts in greenness management could serve as an effective resilience factor for protecting population health. Natural Science Foundation of Beijing (IS23105), 10.13039/501100001809 National Natural Science Foundation of China (82250610230, 72061137004), 10.13039/100004423 World Health Organization (2024/1463606-0), Research Fund Vanke School of Public Health 10.13039/501100004147 Tsinghua University (2024JC002).

As urban parks become vital settings for public health, understanding how spatial features influence physical activity is essential. This study addresses a research gap by examining how park attributes affect walking and running across different space types (paths vs. plazas) and time periods. Analyzing 30 spatial units in three Shanghai parks (2021–2023) via OLS regression, the research identifies several key findings. Results indicate that paths facilitate significantly higher activity levels than plazas. While safety facilities, single-layer vegetation, and stone paving consistently promote activity, seat density and complex vegetation show divergent effects across space types. Temporally, connectivity, lighting, and simple vegetation structures encourage activity throughout the day, whereas high choice values and long entrance distances consistently act as suppressors. Other features, such as sky openness and water proximity, exhibit time-specific influences. These findings provide empirical evidence of the dynamic, context-dependent relationship between park design and exercise, offering actionable insights for urban planners to optimize green spaces for public health.