A study of the walkability of a Swiss town required finding suitable representations of multivariate geographical da-ta. The goal was to represent multiple indices of walkability concurrently and visualizing the data along the street network it relates to. Different indices of pedestrian friendliness were assessed for short street sections and then mapped to an overlaid grid. Basic and composite glyphs were designed using square-or triangle-areas to display one to four index values concurrently within the grid structure. Color was used to indicate different indices. Implement-ing visualizations for different combinations of index sets, we find that single values can be emphasized or de-emphasized by selecting the color scheme accordingly and that different color selections either allow perceiving single values or overall trends over the evaluated area. Values for up to four indices can be displayed in combination within the resulting geovisualizations and the underlying gridded road network references the data to its real world locations.
ABSTRACT:The positive effects of low-intensity physical activity are widely acknowledged and in this context walking is often promoted as an active form of transport. Under the concept of walkability the role of the built environment in encouraging walking is investigated. For that purpose, walkability is quantified area-wise by measuring a varying set of built environment attributes. In purely GIS-based approaches to studying walkability, indices are generally built using existing and easily accessible data. These include street network design, population density, land use mix, and access to destinations. Access to destinations is usually estimated using either a fixed radius, or distances in the street network. In this paper, two approaches to approximate a footpath network are presented. The two footpath networks were built making different assumptions regarding the walkability of different street types with respect to more or less restrictive safety preferences. Information on sidewalk presence, pedestrian crossings, and traffic restrictions were used to build both networks. The first network comprises car traffic free areas only. The second network includes streets with low speed limits that have no sidewalks. Both networks are compared to the more commonly used street network in an access-to-distance analysis. The results suggest that for the generally highly walkable study area, access to destination mostly depends on destination density within the defined walkable distance. However, on single street segments access to destinations is diminished when only car traffic free spaces are assumed to be walkable.
Locations become places through personal significance and experience. While place data are not emotion data, per se, personal significance and experience are often emotional. In this paper, we explore the potential of using visual data exploration to support the qualitative analysis of place-related emotion data. To do so, we draw upon Creswell’s (2009) definition of place to define a generic data model that contains emotion data for a given location and its locale. For each data dimension in our model, we present symbolization options that can be combined to create a range of interactive visualizations, specifically supporting re-expression. We discuss the usefulness of example visualizations, created based on a data set from a pilot study on how elderly women experience their neighborhood. We find that the visualizations support four broad qualitative data analysis tasks: revising categorizations, making connections and relationships, aggregating for synthesis, and corroborating evidence by combining sense of place with locale information to support a holistic interpretation of place data. In conclusion, the paper contributes to the literature in three ways. It provides a generic data model and associated symbolization options, and uses examples to show how place-related emotion data can be visualized. Further, the example visualizations make explicit how re-expression, the combination of emotion data with locale information, and visualization of vagueness and linked data support the analysis of emotion data. Finally, we advocate for visualization-supported qualitative data analysis in interdisciplinary teams so that more suitable maps are used and so that cartographers can better understand and support qualitative data analysis.
The positive effects of active mobility on mental and physical health as well as on air quality are widely acknowledged. Increasing the share of active travel is therefore an aim in many countries. Providing bicycle-safe infrastructure is one way to promote cycling. Roundabouts are a common traffic infrastructure and are supposed to facilitate safe and smooth traffic flow. However, data on road traffic accidents indicate an over-proportional involvement of cyclists in accidents at roundabouts. In the present study, the influence of roundabout geometry and traffic flow on bicycle accident occurrence was investigated using a logistic regression approach on twelve parameters of N = 294 mostly small- and mini-sized single-lane roundabouts in the Canton of Berne, Switzerland. Average weekday motorized traffic was identified as a major factor in explaining bicycle accident occurrence at roundabouts. Further, the radius of the central island, the location of the roundabout (in town vs. out of town) and the number of legs were significantly related to bicycle accident occurrence. While these results are in general agreement with findings from similar studies, the findings regarding the central island’s radius and the number of legs underpin the need for roundabout type-specific studies: Some parameters may not prove relevant in intermediate- to large-sized roundabouts, but become critical in small or mini roundabouts, which are common in Switzerland and numerous in the present sample.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.