LAUSR

Greenspace exposure (GSE) may have a positive impact on mental health. However, existing research lacks a classification analysis of the influence pathways of different GSE on mental health. Meanwhile, the research method is limited to the measurement of the green space ratio (GSR) based on remote sensing data, which ignores people’s real perception of greenspace. This paper aims to further expand the measurement method of GSE, taking Hangzhou, China as an example, and to reveal the influence mechanism of different GSE modes on mental health. We obtained the personal information, mental health, physical activity, and other data of the interviewees through a questionnaire (n = 461). Combined with a remote sensing satellite and the Baidu Street view database, the method of image interpretation and deep learning was used to obtain the GSR, green visual ratio (GVR), and green visual exposure (GVE). The structural equation model is used to analyze the relationship between different variables. The results showed that: (1) GSE has a certain positive effect on mental health; (2) there are differences in the influence mechanism of multiple measures of GSE on mental health—the GVR and GVE measures based on the interaction perspective between human and greenspace make the influence mechanism more complicated, and produce direct and indirect influence paths; and (3) greenspace perception, sense of community, and physical activity can act as mediators, and have indirect effects. Finally, we call for expanding the measurement index and methods of GSE and integrating them into the management and control practices of urban planning to promote the healthy development of communities and even cities.