Abstract
Green exposure levels are closely related to human well-being. However, previous studies have rarely considered the green exposure experienced through human mobility, especially within the framework of the 15-minute city. Additionally, due to the lack of seasonal and large-scale spatial data, seasonal variations in green exposure have often been overlooked. In this study, we propose an assessment framework for seasonal green space exposure inequality within the context of the 15-minute city. By integrating the Green View Index, spatial statistical methods, deep learning, and publicly available urban housing price big data, we analyzed green exposure inequality in Xi'an, China. The results indicate that: (1) There is a seasonal inequality in the exposure to greenery within the 15-minute residential areas of Xi'an. At short distances (5-10 min), green exposure in summer is higher than that in winter, whereas at longer distances (15-30 min), green exposure in winter exceeds that in summer. (2) There is an inequitable relationship between urban housing prices and seasonal green exposure. In short-distance living circles, housing prices are negatively correlated with seasonal differences in green exposure, meaning that areas with less seasonal variation tend to have higher housing prices. In long-distance living circles, the correlation is positive, with areas exhibiting greater seasonal variation tending to have higher housing prices. (3) Spatial autocorrelation between housing prices and seasonal green exposure varies across different living circles, showing an unequal distribution. High-value clusters extend from the southern part of Weiyang District along a northwest-southeast axis, forming a stable pattern in the west, a dynamic pattern in the east, and a heterogeneous pattern in the central region. This study not only fills a research gap regarding seasonal green exposure at the community level but also provides new perspectives for urban planning and environmental design, offering scientific evidence to mitigate urban environmental inequalities.