Geographic heterogeneity in cycling under various weather conditions: Evidence from Greater Rotterdam
Autor: | Helbich, M., Böcker, L., Dijst, M.J., SGPL Stadsgeografie, Social Urban Transitions |
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Přispěvatelé: | SGPL Stadsgeografie, Social Urban Transitions |
Jazyk: | angličtina |
Rok vydání: | 2014 |
Předmět: |
Bicycle commuting
Geography Planning and Development Logit Spatial analysis Transportation Context (language use) Cycling The Netherlands Wind speed Transport engineering Geography Spatial ecology TRIPS architecture population characteristics Active transportation Economic geography Mode choice Weather General Environmental Science |
Zdroj: | Journal of Transport Geography, 38, 38. Elsevier BV |
ISSN: | 0966-6923 |
Popis: | With its sustainability, health and accessibility benefits, cycling has nowadays been established on research and policy agendas. Notwithstanding the decision to cycle is closely related to local weather conditions and interwoven with the geographical context, research dealing with both aspects is scarce. On the basis of travel diary data, we assess the association of three weather conditions, namely air temperature, wind speed, and precipitation, on cycling trips for leisure and commute purposes for the Greater Rotterdam area, the Netherlands. Besides region-wide logit models and autologistic regressions, place-specific associations of weather conditions are explored through geographically weighted logit models. Considering the entire Rotterdam area, results confirm significant weather effects on cycling while highlighting the necessity to model the residents’ locational component. When the confounding effects of individual and household characteristics are controlled, a key finding is that weather effects appear to vary across space, specifically between the more densely settled central environments and the surrounding lower-density areas. Additionally, the results show differences between leisure and commute trips, in which leisure trips appear to be more weather sensitive and show more pronounced spatial patterns. |
Databáze: | OpenAIRE |
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