BackgroundThe built environment health promotion has attracted notable attention across a wide spectrum of health-related research over the past decade. However, the results about the contextual effects on health and PA are highly heterogeneous. The discrepancies between the results can potentially be partly explained by the diverse use of different spatial units of analysis in assessing individuals’ exposure to various environment characteristics. This study investigated whether different residential and activity space units of analysis yield distinct results regarding the association between the built environment and health. In addition, this study examines the challenges and opportunities of the different spatial units of analysis for environmental health-related research.MethodsTwo common residential units of analysis and two novel activity space models were used to examine older adults’ wellbeing in relation to the built environment features in the Helsinki Metropolitan Area, Finland. An administrative unit, 500 m residential buffer, home range model and individualized residential exposure model were used to assess the associations between the built environment and wellbeing of respondent’s (n = 844).ResultsAll four different spatial units of analysis yield distinct results regarding the associations between the built environment characteristics and wellbeing. A positive association between green space and health was found only when exposure was assessed with individualized residential exposure model. Walkability index and the length of pedestrian and bicycle roads were found to positively correlate with perceived wellbeing measures only with a home range model. Additionally, all units of analysis differed from each other in terms of size, shape, and how they capture different contextual measures.ConclusionsThe results show that different spatial units of analysis result in considerably different measurements of built environment. In turn, the differences derived from the use of different spatial units seem to considerably affect the associations between environment characteristics and wellbeing measures. Although it is not easy to argue about the correctness of these measurements, what is evident is that they can reveal different wellbeing outcomes. While some methods are especially usable to determine the availability of environmental opportunities that promote active travel and the related health outcomes, others can provide us with insight into the mechanisms how the actual exposure to green structure can enhance wellbeing.

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The COVID-19 pandemic has encouraged a deeper exploration about how people deal with crisis. This paper presents one of the first pre- and during-pandemic assessments of urban green infrastructure (UGI) use across the same individuals with the aim of better understanding how people's use of different types of urban green and blue spaces changed during the pandemic. A baseline Public Participation GIS survey (N = 1,583 respondents) conducted in August 2018 was followed up in May 2020 (N = 418 identical respondents) during the COVID-19 pandemic in Helsinki, Finland. We found that residents were more likely to visit UGI closer to their home during the pandemic compared with before the pandemic. Patterns of use of UGI were associated with the quality of residential green areas, for example, people sought out forests nearby one's domicile and tended to avoid parks and recreation areas in order to escape the pressures of lockdown, socially distance and avoid overcrowding. However, spatial cluster analyses also revealed that the places mapped by intensive users of natural recreational areas and more outdoor oriented users became more dispersed during the pandemic, suggesting their active search for new types of UGI, including use of agricultural land and residential areas with high tree density cover. Our results further highlighted that some types of UGI such as more distant natural and semi-natural areas and blue spaces serve as critical infrastructure both before and during the pandemic. Natural and semi-natural areas experienced very little change in use. The presented results have implications for how planners design and manage green spaces to enable residents to cope with crises like pandemics into the future.

Today, various methods are applied to analyze the data collected through participatory mapping, including public participation GIS (PPGIS), participatory GIS (PGIS), and collecting volunteered geographic information (VGI). However, these methods lack an organized framework to describe and guide their systematic applications. Majority of the published articles on participatory mapping apply a specific subset of analyses that fails to situate the methods within a broader, more holistic context of research and practice. Based on the expert workshops and a literature review, we synthesized the existing analysis methods applied to the data collected through participatory mapping approaches. In this article, we present a framework of methods categorized into three phases: Explore, Explain, and Predict/Model. Identified analysis methods have been highlighted with empirical examples. The article particularly focuses on the increasing applications of online PPGIS and web-based mapping surveys for data collection. We aim to guide both novice and experienced practitioners in the field of participatory mapping. In addition to providing a holistic framework for understanding data analysis possibilities, we also discuss potential directions for future developments in analysis of participatory mapping data.