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.

Smartphones can help researchers track how people use green spaces and understand how design features impact their behaviors. However, when using this data to evaluate green space designs, researchers should be aware of human perceptions of the features within these environments. We contribute a mixed method approach that allows for comparison between how people report using green space features intended to support wellbeing, with how often they are used in common daily routines. As an illustration of this approach, we present the results of a case study conducted on a university campus that compares how outdoor design features are used by students with how these features are reported as being used. Specifically, we compare perceptions of 362 students about which campus design features create a sense of wellbeing, and which are near locations they report using, with the use of these features recorded by the smartphones of a separate group of 62 students. We found that there were large differences between locations students reported using, and locations tracked students used regularly. Features that were used more often during daily routines (low walls, food retail outlets), did not match features reported as helping create a sense of wellbeing in the questionnaire (benches, trees, and sunshine). Of all the design features we modeled, only water features were positively associated with use in the tracking data and supportive of wellbeing in the questionnaire data. Our findings point to the importance of using tracking data together with response data from questionnaires in mixed-method studies if designers want to locate features that the public consider as supportive to their wellbeing, in locations that will be regularly used.

With the near-ubiquitous presence of smartphones among urban dwellers in many parts of the world, we are living in an age where the public can act as continuous sensors of urban spaces. As such, data collected from GPS sensors in phones are particularly suited to support understanding human spatial behaviors in cities, and their potential for societal monitoring has been much anticipated. Yet, the field is still emerging and practical steps for utilizing smartphone-GPS in human behavior research remain unclear. Over a decade after the introduction of smartphones, we review the use of GPS data collected by these devices (smartphone-GPS data) as a tool for researching human behavior in cities. Using methods and findings from 96 papers that investigate human behaviors using smartphone-GPS data, we present seven application themes that describe domains where these data have been used thus far: sports and physical activity, environmental conditions, health and wellbeing, places and movement, neighborhoods and society, tourism, and single amenity use. We also describe the methodological factors, including parameters and variables, that have shaped how researchers have used smartphone-GPS data to understand relationships between pedestrian-scale human behaviors and urban environments. Based on these findings, we make recommendations for future researchers using smartphone-GPS data to understand relationships between humans and urban environments, at the pedestrian scale.

We present the SmartCampus visualization tool, representing spatiotemporal data of over 200 student pathways and restpoints on a university campus. Based on our experiences with SmartCampus, we also propose a task-based framework that describes how practicing urban designers (specifically, architects) can use human movement data visualizations in their work. Although extensive amounts of location data are produced daily by smartphones, existing geospatial tools are not customized to specifically support high-level urban design tasks. To help identify opportunities in urban design for visualizing human movement data from devices such as smartphones, we used our SmartCampus prototype to facilitate a series of 3 participatory design sessions (3 participants), a targeted online survey (14 participants), and semi-structured interviews (6 participants) with architectural experts. Our findings showcase the need for location analysis tools tailored to concrete urban design practices, and also highlight opportunities for Smart City researchers interested in developing domain specific, visualization tools.

For many university students, commuting to and from campus constitutes a large proportion of their daily movement, and therefore it may influence their ability and willingness to spend time on campus or to participate in campus activities. To assess student engagement on campus, we collected smartphone GPS location histories from volunteers (n = 280) attending university in a major Canadian city. We investigated how campus visit length and frequency were related to characteristics of the commute using Bayesian regression models. Slower commutes and commutes over longer distances were associated with more time spent but less frequent visits to campus. Our results demonstrate that exposure to campus life, and therefore the potential for student engagement, may relate not just to whether a student lives on or near campus, but also to urban environmental factors that interact to influence the commuting experience.

Selecting a location for a new amenity can be a ‘wicked problem’ in planning engagement processes, involving multiple contradicting criteria. Recently available data sources generated by personal devices such as smartphones may be able to help. Planners are often required to incorporate public engagement methods when making urban planning decisions. Ideally, such decisions will be informed by evidence of how relevant public spaces are used. Researchers have speculated that smartphone location data, which can be mapped to show the use of space, might be useful for such purposes, however, it is not obvious whether non-experts will trust location data enough to use it. Our objective is to investigate whether non-experts use these data in an urban planning scenario by empirically measuring the influence of personal smartphone location histories on a location selection. Using an experimental simulation of an engagement scenario with 48 participants, and two manipulated factors (data presentation format and group size) we ask: do students use smartphone location data when locating a new campus amenity and how were the data used? We utilized regression analysis to assess changes in location selection after viewing data and compared these results to a qualitative post-study interview. Our data demonstrated a plausible change in location selection after viewing maps of smartphone location data. In addition, groups using a digital interactive surface discussed the data while those using paper did not. We also found that, when asked to make a final location selection, participants combined the data with previously held values (such as centrality). We conclude that those researching and leading planning decisions, such as locating a new amenity, should invest in incorporating smartphone data where it can provide empirical support for public engagement decisions.

Outdoor learning spaces can be used to support child development where children engage with natural elements as an integral part of their school experience. This naturally facilitates cognitive play: a grouping of behaviors that facilitate cognitive development. The problem is that outdoor learning is particularly challenging in winter due to cold weather. This compromises opportunities for children to benefit from outdoor learning for a large part of the school year in cold climates. Previous studies, using behavioral mapping, have pointed to the role that design elements play in child development; although these studies were conducted in warm weather. Our solution is to map child behaviors in schools where outdoor play is encouraged during winter, to illustrate the role that design elements play in winter outdoor learning, and to enable us to highlight challenges of winter outdoor learning that may be addressed through design interventions. We observed three schools which are dedicated to outdoor learning, during winter in a cold climate, using behavioral mapping, focused observations and photo documentation. Our analysis confirms that outdoor winter environments support cognitive play, and we discuss design interventions that can mitigate challenges faced by schools dedicated to outdoor learning in winter.