An Interdisciplinary Mixed-Methods Approach to Analyzing Urban Spaces: The Case of Urban Walkability and Bikeability.

geospatial analysis mixed-method approaches qualitative questionnaires real-time perceptions urban spaces wearable physiological sensors

Journal

International journal of environmental research and public health
ISSN: 1660-4601
Titre abrégé: Int J Environ Res Public Health
Pays: Switzerland
ID NLM: 101238455

Informations de publication

Date de publication:
24 09 2020
Historique:
received: 25 07 2020
revised: 17 09 2020
accepted: 21 09 2020
entrez: 29 9 2020
pubmed: 30 9 2020
medline: 12 1 2021
Statut: epublish

Résumé

Human-centered approaches are of particular importance when analyzing urban spaces in technology-driven fields, because understanding how people perceive and react to their environments depends on several dynamic and static factors, such as traffic volume, noise, safety, urban configuration, and greenness. Analyzing and interpreting emotions against the background of environmental information can provide insights into the spatial and temporal properties of urban spaces and their influence on citizens, such as urban walkability and bikeability. In this study, we present a comprehensive mixed-methods approach to geospatial analysis that utilizes wearable sensor technology for emotion detection and combines information from sources that correct or complement each other. This includes objective data from wearable physiological sensors combined with an eDiary app, first-person perspective videos from a chest-mounted camera, and georeferenced interviews, and post-hoc surveys. Across two studies, we identified and geolocated pedestrians' and cyclists' moments of stress and relaxation in the city centers of Salzburg and Cologne. Despite open methodological questions, we conclude that mapping wearable sensor data, complemented with other sources of information-all of which are indispensable for evidence-based urban planning-offering tremendous potential for gaining useful insights into urban spaces and their impact on citizens.

Identifiants

pubmed: 32987877
pii: ijerph17196994
doi: 10.3390/ijerph17196994
pmc: PMC7579167
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

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Auteurs

Bernd Resch (B)

Department of Geoinformatics-Z_GIS, University of Salzburg, 5020 Salzburg, Austria.
Institute for Quantitative Social Science, Harvard University, Cambridge, MA 02138, USA.

Inga Puetz (I)

Department of Geoinformatics-Z_GIS, University of Salzburg, 5020 Salzburg, Austria.

Matthias Bluemke (M)

GESIS-Leibniz Institute for the Social Sciences, 68159 Mannheim, Germany.

Kalliopi Kyriakou (K)

Department of Geoinformatics-Z_GIS, University of Salzburg, 5020 Salzburg, Austria.

Jakob Miksch (J)

Department of Geoinformatics-Z_GIS, University of Salzburg, 5020 Salzburg, Austria.

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Classifications MeSH