Mapping the Mind in Motion: A Multi-Method GIS–SEM–NCA Model of Green Exposure and Psychological Restoration in Urban Jogging Environments

Abstract As urban mental health challenges grow, understanding how green spaces promote psychological restoration during exercise is crucial for sustainable urban development. While vegetation volume is a known factor, the psychological mechanisms through which objective green exposure translates into restorative outcomes, especially in dynamic exercise contexts remain insufficiently explored. This study investigates the Xuanwu Lake jogging circuit in Nanjing, China, a representative urban green space. We integrated GIS-based Normalized Difference Vegetation Index (NDVI) remote sensing data with subjective psychometric scales to assess green exposure. A multi-layered analytical framework was employed, combining Partial Least Squares Structural Equation Modeling (PLS-SEM) to test predictive relationships and Necessary Condition Analysis (NCA) to identify the minimum thresholds (bottlenecks) required for restoration. The findings reveal that subjective green exposure (Perceived Vegetation Density and Perceived Green Enclosure) significantly enhances psychological restoration by mediating dimensions of "Being Away" and "Fascination." Notably, Environmental Compatibility emerged as the strongest predictor, indicating that the alignment between the environment and the exerciser's needs is the primary driver of restoration. Furthermore, Nature Connectedness (NC) significantly moderates the relationship between green exposure and perceived restorativeness; individuals with higher NC are more sensitive to vegetation density. NCA results confirm that specific restorative dimensions function as "necessary but not sufficient" conditions, with compatibility and fascination acting as critical bottlenecks for high-level restoration.