Running can promote public health. However, the association between running and the built environment, especially in terms of micro street-level factors, has rarely been studied. This study explored the influence of built environments at different scales on running in Inner London. The 5Ds framework (density, diversity, design, destination accessibility, and distance to transit) was used to classify the macro-scale features, and computer vision (CV) and deep learning (DL) were used to measure the micro-scale features. We extracted the accumulated GPS running data of 40,290 sample points from Strava. The spatial autoregressive combined (SAC) model revealed the spatial autocorrelation effect. The result showed that, for macro-scale features: (1) running occurs more frequently on trunk, primary, secondary, and tertiary roads, cycleways, and footways, but runners choose tracks, paths, pedestrian streets, and service streets relatively less; (2) safety, larger open space areas, and longer street lengths promote running; (3) streets with higher accessibility might attract runners (according to a spatial syntactic analysis); and (4) higher job density, POI entropy, canopy density, and high levels of PM 2.5 might impede running. For micro-scale features: (1) wider roads (especially sidewalks), more streetlights, trees, higher sky openness, and proximity to mountains and water facilitate running; and (2) more architectural interfaces, fences, and plants with low branching points might hinder running. The results revealed the linkages between built environments (on the macro- and micro-scale) and running in Inner London, which can provide practical suggestions for creating running-friendly cities.

Urban parks have been proven to effectively reduce mental fatigue among city residents; however, there has been less focus on the mental health benefits offered by pocket parks in densely populated areas from a field experiment perspective. Additionally, there is insufficient evidence providing information on the environmental characteristics that support recovery from mental fatigue. This study was based on 80 young adults aged 19–25 years. Three types of pocket parks were selected: street corners, interblock spaces, and intrablock spaces. Through a field experiment with questionnaire collection, physiological (BP, HR, and LF/HF) and psychological indicators (FS-14 and VAS) were used to explore the relationship between various pocket park features and respondents’ mental fatigue recovery. This study investigated the restorative effects of 10 environmental features by collecting questionnaires. The results suggested that different types of pocket parks have the recovery effect of pocket parks. Four environmental factors, namely, vegetation colour (β = −0.472, p = 0.002), vegetation coverage (β = 0.298, p = 0.046), resting facility comfort (β = −0.336, p = 0.028), and plant species (β = −0.437, p = 0.003), were more predictive of mental fatigue recoverability. However, factors such as neighbourhood hygiene and spatial privacy did not show significant predictive effects. Our findings provide robust evidence for urban park planning and design. In the future landscape design of high-density urban areas, greater emphasis can be placed on the construction of pocket parks. The rational selection and configuration of environmental factors that contribute to recovery effects in pocket parks will contribute to meeting the psychological health service needs of high-density urban populations.

Landmark landscapes, as visual representations of cities, are readily identifiable to urban residents. Observing and visiting these landscapes fosters a cultural connection and identity with the locale, enhances urban character, and promotes tourism. A place’s identity is instrumental in urban development and improvement. Urban planners and managers should thus prioritize fostering residents’ place identity within city environments. In this study, we explored the influence of landmark landscapes on the place identity of residents in Nanjing—a rapidly urbanizing city with both historic and modern districts. Our methodology included on-site surveys and the application of a structural equation model to discern the relationships between various landmark landscape elements and place identity. The findings revealed the following: (1) landmark landscapes positively influence residents’ construction of place identity; (2) the characteristics, function, and historical–cultural importance of these landmark landscapes contribute to place identity formation; and (3) the duration of residence moderates the relationship between historical–cultural importance and place identity. These insights elucidate the role of landmark landscapes in shaping place identity, which in turn enhances urban characteristics and bolsters residents’ sense of belonging. The strategic planning and design of landmark landscapes are instrumental in building public consensus, fostering distinctive urban characteristics, and strengthening residents’ sense of identity, thereby catalyzing tourism development.

While urban green spaces (UGSs) are important places for residents’ leisure activities, studies describing the long-term daily UGS usage of residents (including the total number of activities, the types of activities, and the touring experience) have not been conducted due to difficulties in data collection. Based on social media text data (SMTD), in this study, the total number of daily activities, the intensities of optional and social activities, and the daily touring experience in 100 UGSs in Xiamen, China, were inferred based on the ERNIE 3.0 text pre-training semantic classification model. Based on this, linear regression modeling was applied to analyze the internal environmental factors of the effects of places and external urban form factors regarding daily UGS usage. The research results revealed the following. (1) A descriptive study was conducted on the total numbers, types, and touring experience of activities using SMTD, and the results were verified by line transect surveys, management statistics, and a publicly available dataset. (2) The number of human activities in UGSs was found to be significantly influenced by historical and cultural facilities, nighttime lighting, population density, and the proportion of the floating population. (3) During the daytime, optional activities were found to be significantly influenced by the park type and historical and cultural facilities, and social activities were found to be significantly influenced by historical and cultural facilities and population density. In the evening, optional activities were found to be significantly influenced by the park type, historical and cultural facilities, nighttime lighting, and the proportion of the floating population, and social activities were found to be influenced by the proportion of the floating population. (4) Regarding the touring experience, in the daytime, the park type, green space ratio, and proportion of the floating population had significant effects on the touring experience. In the evening, the park type, historical and cultural facilities, and security factors were found to have significant effects on the touring experience. The methodology and findings of this study aid in the understanding of the differences in daytime and nighttime activities, and in the discovery of planning tools to promote human leisure activities in UGSs.

Rapid urbanization, which often overlooks the socio-cultural attributes and values embedded in urban space, has intensified problems of “placelessness” and a weakened sense of public identity. Examining city–public interactions through the concept of urban collective memory helps forge an operational, quantifiable link among the built environment, social identity, and historical continuity. Using Nanjing as a case study, this research integrates collective-memory theory with the urban-image framework. Drawing on geotagged “digital network memory” data from social media, we apply natural-language processing (NLP) and geographic information system (GIS) techniques to aggregate individuals’ spatial images and construct an urban collective-memory map comprising paths, nodes, landmarks, districts, and edges. The findings show that collective memory can be both spatially visualized and quantified, while revealing clear regional differentiation. Consequently, the study provides a sociologically grounded method for assessing urban spatial value that informs evaluations of urban resilience and cultural continuity.