This exploratory study explores the potential contexts and opportunities for emerging visual data in urban forest design. Forestry experts deploy drone-mounted digital sensors to capture detailed visual and spatial data urban vegetation. These sensors generate point clouds that not only inform ecological analysis but also visually construct urban environments from a pedestrian perspective. Even though many data sources and visualisation tools such as GIS are available, how visualised data should be integrated into design practice is still unclear. Using a prototype multi-sourced data visualisation, we conducted eight semi-structured interviews with urban forestry experts to elicit reflections of the analytical and cultural roles of data visualisations in the domain. Thematic analysis of the interview transcripts revealed three design-oriented themes: (1) design analysis, (2) public engagement, and (3) sustainability. By analysing expert reflections, this paper considers potential research directions for visualising social and ecological data as a design material in the built environment. We discuss the implications of such visualisations for the broader community of spatial planning research including urban designers and communication scholars, proposing future research directions that leverage visual data to better design evolving urban landscapes.

Urban planners and urban forestry researchers use various methods to evaluate how well different populations access the benefits of parks, often by assessing park distribution in relation to the social and economic conditions of surrounding neighbourhoods. However, without precise visitation data, it remains unclear whether proximity to parks translates into actual use. This study analyses the social and spatial factors influencing park visitation using real-world data across multiple urban and ecological contexts. We utilised smartphone mobility to capture visitation counts for over 14,000 parks across 10 US metropolitan areas, representing populations from more than 26,000 census block groups (CBGs). By integrating census data with spatial models, we examined the relationships between park visitation, proximity of parks to visitors' home neighbourhoods, and socio-economic variables such as race and ethnicity. Our analysis revealed that park visitation increases with proximity to visitors' home neighbourhoods. We also found positive associations between visitation rates and factors such as population density, median income, and park coverage in visitors' home neighbourhoods. Additionally, we identified significant correlations between park visitation and the racial and ethnic composition of these neighbourhoods. These findings confirm the assumption that closer proximity to parks enhances visitation rates. We recommend that park visitation data be considered alongside distributional analyses when planning for park accessibility.