This study deciphers the impacts of urban forests and green spaces (UFGSs) on housing prices through a systematic review of 180 peer-reviewed articles (440 empirical cases) to delineate how various UFGS attributes drive housing price changes, focusing on the direction, intensity, and contextual dependency of these impacts. We identified specific UFGS attributes (e.g., proximity, size, type, quality, accessibility, landscape patterns) and the methodologies assessing their price impacts, primarily hedonic pricing models. Our findings confirm a consistent, albeit highly variable, positive premium from urban forests and related green infrastructure on housing prices. Key drivers include not only proximity and size, but also crucial qualitative attributes like perceived UFGS quality (e.g., tree canopy coverage, wooded park maintenance), which often show stronger or more consistent effects than simple quantitative measures. The analysis also highlights that negative impacts can arise from poorly managed urban forests or certain disamenity-prone green typologies. Significant spatio-temporal heterogeneity is evident, with price effects varying by urban context (e.g., density, development stage) and over time. Socio-economic factors, particularly manifesting as “green gentrification”, which can exacerbate inequalities by disproportionately benefiting higher-income groups, critically moderate these relationships. Furthermore, prevalent non-linear effects (e.g., distance-decay patterns, threshold effects for UFGS size) and complex interactions between different UFGS attributes underscore the nuanced nature of the UFGS–price nexus. This review provides a structured understanding of urban forest and green space capitalization drivers, emphasizing the need for nuanced, evidence-based urban forestry planning and green space management that considers UFGS quality, diversity, and equitable distribution for sustainable urban development.
Zhou et al. (Thu,) studied this question.