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Measures of individual mobility, such as activity space, have been previously used to help improve our understanding of individuals' interactions with their everyday environments. However, such methods have rarely been adopted in studying children's physical activity and active travel behavior. In this study, we use a combination of participatory mapping and accelerometer data collected from children aged 8–13 years living in Tāmaki Makaurau/Auckland, Aotearoa/New Zealand, to describe children's travel behavior and explore associations of active travel, physical activity, and socio-demographic characteristics with environmental attributes. The results from this study reveal complex associations between these different layers. Density of cycling routes was consistently associated with higher levels of physical activity captured via moderate-to-vigorous physical activity (MVPA), prevalence of active travel, and total activity space exposure. Nevertheless, population density, greenspace, and land-use mix revealed varying associations across different activity behaviors including MVPA, number of steps, and prevalence of active travel. The results from this study not only reassert the complexity of person–environment relationships, but also highlight the potential impacts of measurement and analytical methods on the study results. The novel combination of participatory mapping and accelerometer data together with activity space analysis provided new analytical insights which we discuss in this paper. This study concludes by reporting its observations and envisioning future research directions. [ABSTRACT FROM AUTHOR]

Abstract: The human perception and valuation of landscapes is a complex process but has been pragmatically advanced through public participation GIS (PPGIS). PPGIS methods have the capacity to generate spatial data to empirically examine relationships between human landscape values and physical landscape character. In 2011, PPGIS methods were used to identify a range of social landscape values for two regions in southern New Zealand, Otago and Southland. Seven of these landscape values were analysed to identify significant relationships with physical landscape character from the New Zealand Landscape Classification system. In this paper we examine methods to extrapolate landscape values from this regional data set to a national level using these landscape value and character relationships. In the absence of empirical value data at a national level, we examine two quantitative approaches for extrapolating landscape values: (1) landscape component weights based on the percentage of value counts found within landscape components, and (2) landscape component weights based on the ratio of landscape values to the landscape area. We prepare and present maps of seven landscape values for the entire country of New Zealand to demonstrate the method. We conclude that landscape value extrapolation can assist impact assessment for land use change but should be kept simple for decision support. [Copyright &y& Elsevier]