The park environment is crucial for promoting physical activity (PA). While numerous studies show that park environments influence PA behavior, inconsistencies remain, likely due to varing research methods and parks types. This study employs a fixed spatial grid method to systematically sample four representative parks in Tianjin, China. High-precision orthophoto map (DOM) data from drones provided detailed environmental attributes (like tree canopy area, lawn area, and paved area) and PA characteristics (number of participants, intensity, diversity). The results show: 1) Cluster analysis grouped 1839 park grids into 12 environmental attribute integrations, each correlating with different PA characteristics. “Tree-lined jogging corridors” and “Large sports field areas” exhibit the highest PA intensity, while “Entrance plazas”, “Central plazas,” and “Open sports spaces” have the highest number of participants and PA diversity. 2) Correlation analysis shows that various environmental attributes, including Lawn Area, and Paved Area, are significantly correlated with PA characteristics. 3）Random Forest analysis indicates the key attributes are the paved area for the number of PA participants and PA diversity, and specialized sports facilities area for PA intensity. These findings support urban green space planning and highlight the importance of better park environments for public health.

Old residential communities are integral parts of urban areas, with their environmental quality affecting residents’ well-being. Spontaneous informal spaces (SIS) often emerge within these communities. These are predominantly crafted by the elderly using discarded materials and negatively impact the environmental quality of communities. Understanding SIS emergence patterns is vital for enhancing the environmental quality of old communities; however, methodologies fall short in terms of the quantification of these emergence patterns. This study introduces a groundbreaking approach, merging drone oblique photography technology with space syntax theory, to thoroughly analyze SIS types, functions, and determinants in five Tianjin communities. Utilizing drones and the Depthmap space syntax tool, we captured SIS characteristics and constructed topological models of residences and traffic patterns. We further explored the intrinsic relationships between architectural layout, road traffic, and SIS characteristics via clustering algorithms and multivariate correlation analysis. Our results reveal that architectural layout and road traffic play decisive roles in shaping SIS. Highly accessible regions predominantly feature social-type SIS, while secluded or less trafficked zones lean towards private-type SIS. Highlighting the elderly’s essential needs for greenery, interaction, and basic amenities, our findings offer valuable insights into the revitalization of outdoor spaces in aging communities, into the fostering of urban sustainability and into the nurturing of a balanced relationship between humans and their surroundings.