Abstract
Experiencing nature can induce the perception of happiness because of mental stress alleviation and well-being restoration. The largeness of green space may not always mean the frequency of experiencing greenery. It is arguing about the probability of positive sentiments in response to an experience of interacting with green nature. In this study, 38 green spaces were investigated in Nanchang City, China, where the green space area was evaluated by the largeness of the landscape metrics of the Normalized Vegetation Index (NDVI), and Green View Index (GVI) data were further obtained using Open Street Maps (OSM). The semantic segmentation method was used by machine learning to analyze a total of 1549 panoramic photos taken in field surveys to assess the Panoramic Green View Index (PGVI) proportion. The photos of 2400 people’s facial expressions were obtained from social networks at their check-in visits in green spaces and rated for happy and sad scores using FireFACE software. Split-plot analysis of variance suggested that different categories of NDVI largeness had a significant positive effect on posted positive sentiments. Multivariate linear regression indicated that PGVI was estimated to have a significant contribution to facial expression. Increasing the amount of PGVI promoted happy and PRI scores, while at the same time, neutral sentiments decreased with increasing PGVI. Overall, increasing the PGVI in green spaces, especially in parks with smaller green spaces, can be effective in promoting positive emotions in the visitor experience.
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