Discrepancies between perceived accessibility and spatial accessibility modelling: A case study of urban parks in Guangzhou, China

•Over 70% of accessibility differ between spatial modelling and public perception.•It examines the stability of accessibility modelling approaches.•Population preference weights in models avoid over-generalisation.•Spatial modelling accessibility methods best reflecting perception are identified. In line with the United Nation’s Sustainable Development Goals initiatives across the globe aim to improve access to urban parks. It remains, however, a challenge to accurately measure the spatial accessibility of urban parks. Traditional measurements often fail to match residents’ perceptions of accessibility, highlighting a gap between objective measurements and subjective experiences. This study explored the Spatial Modelling Accessibility (SMA) results of parks derived from various approaches, while also examining the differences with Population Perceived Accessibility (PPA). Our results reveal significant inconsistencies, with over 70 % of accessibility measurements differing between spatial analyses and residents’ perceptions. Exploring spatial distribution features under different SMA approaches for parks confirms the regional differences within the accessibility modelling process. By assessing a diverse array of SMA approaches, this study identifies methods that best reflect PPA. SMA approaches incorporating population preferences and socio-demographic factors offer a more refined understanding, aligning more closely with PPA. Particularly, models adjusted for age related differences in travel time preference better capture residents’ perceptions of accessibility. Integration of population preferences addresses the challenge of defining service radii, a known limitation of traditional models. The study highlights the important choice of the SMA approach and the need to integrate age related travel time preferences to refine the assessment of urban parks accessibility. It contributes to more accurate and inclusive urban planning strategies.