This study seeks to address the gap in knowledge regarding the varying effects of vegetation on human perception and preference, and to comprehend how green spaces can better serve community needs. The research assessed the impact of different vegetation structures on physiological responses during two types of on-site perceptions: sitting and walking, in both winter and summer. The green spaces included single-layer grassland, single-layer woodland, tree-shrub-grass composite woodlands, and tree-grass composite woodlands, and a non-vegetated square. The findings indicated the following. (1) The physiological recovery effect of walking in green spaces is relatively greater than that of sitting; walking in green spaces with different vegetation types was found to enhance participants’ pNN50 values (p = 0). (2) During the summer, sitting and observing provided a better physiological recovery effect (p < 0.05), whereas in the winter, walking was more beneficial (p < 0.05). (3) Green spaces with vegetation were more beneficial for physiological recovery than the non-vegetated square, which could not sustain recovery effects for more than 1 min. Single-layer grassland and tree-shrub-grass composite woodlands had the most significant physiological recovery effects on health (p < 0.01). (4) Based on these conclusions, it is suggested that a combination of sitting and walking can lead to improved recovery outcomes. Therefore, when visiting parks during extreme weather conditions, individuals should adjust the duration of their sitting and walking experiences to enhance their overall experience.

Travelers’ attention to high-quality human habitats is increasing, and the role of urban greenways in improving the quality of travelling spaces has also been appreciated. This research aims at making the weight calculation of suitability more scientific and reasonable, clustering the shared bicycle travelling OD points according to suitability, and analyzing the distribution of OD points. Taking Xiamen as an example, multiscale geographically weighted regression and entropy weight methods were used to calculate the weights of variables using multi-source big data. The clustering of origin-destination (OD) points for shared bicycle travel are identified using the DBSCAN clustering algorithm, which can provide accurate support for greenway planning and shared bicycle placement. The results show that the density of tourist attractions, POI entropy index, road density, and intermediate are four important factors affecting the suitability of greenways. The clustering results of the shared bicycle OD points show that the high-aggregation areas of origin and destination points are located in the northeast and southwest directions as well as west and east directions. This study provides a theoretical and modelling analysis reference for greenway planning and design.

Amidst global urbanization and rising psychological stress, urban green spaces are increasingly recognized as critical infrastructure for sustainable urban development and public health. However, the mechanisms by which summer vegetation structure mediates both physiological and psychological restoration, and the interplay between these two dimensions, remain poorly understood. Understanding these mechanisms is essential for designing sustainable, health-promoting urban environments that can support growing urban populations in a warming climate. This study employed a controlled field experiment in Xi’an during summer to examine the effects of five vegetation structure types (Single-Layer Grassland, single-layer woodland, tree–shrub–grass composite woodland, tree–grass composite woodland, and a non-vegetated square) on university students’ physiological (heart rate variability) and psychological (perceived restorativeness and affective states) restoration. Following stress induction, 300 participants engaged with the green spaces through both quiet sitting and walking. The results revealed three key findings: (1) the tree–shrub–grass composite woodland consistently showed the most favorable trends other vegetation types across all psychological restoration dimensions, while also showing favorable trends in physiological recovery, underscoring the importance of structural complexity for restorative quality; (2) walking significantly enhanced physiological recovery compared to seated observation across all settings, confirming the role of physical activity as a critical activator of green space benefits; (3) correlation analysis identified a specific cross-system association: the R-R interval recovery value showed a weak but significant correlation with positive affect (PA) scores, suggesting that physiological calmness and positive emotional experience are linked, yet their weak coupling under short-term exposure indicates they may operate as parallel processes with distinct temporal dynamics. These findings indicate that the restorative potential of summer green spaces emerges from an integrated framework combining vegetation complexity and activity support. We propose that future sustainable landscape design should prioritize multi-layered vegetation structures as nature-based solutions that simultaneously enhance human well-being and urban resilience. These findings provide empirical evidence for integrating health-promoting green infrastructure into sustainable urban planning frameworks, supporting multiple Sustainable Development Goals (SDGs), including SDG 3 (Good Health and Well-being), SDG 11 (Sustainable Cities and Communities), and SDG 13 (Climate Action).