More than Bike Lanes—A Multifactorial Index of Urban Bikeability

The present study aims to deduce bikeability based on a collective understanding and provides a methodology to operationalize its calculation based on open data. The approach contains four steps building on each other and combines qualitative and quantitative methods. The first three steps include t...

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Autores principales:	Michael Hardinghaus, Simon Nieland, Marius Lehne, Jan Weschke
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	bikeability cycling active transport built environment infrastructure Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/ea37da07feba4b33995dd117a3b0fb6c
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id	oai:doaj.org-article:ea37da07feba4b33995dd117a3b0fb6c
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spelling	oai:doaj.org-article:ea37da07feba4b33995dd117a3b0fb6c2021-11-11T19:21:17ZMore than Bike Lanes—A Multifactorial Index of Urban Bikeability10.3390/su1321115842071-1050https://doaj.org/article/ea37da07feba4b33995dd117a3b0fb6c2021-10-01T00:00:00Zhttps://www.mdpi.com/2071-1050/13/21/11584https://doaj.org/toc/2071-1050The present study aims to deduce bikeability based on a collective understanding and provides a methodology to operationalize its calculation based on open data. The approach contains four steps building on each other and combines qualitative and quantitative methods. The first three steps include the definition and operationalization of the index. First, findings from the literature are condensed to determine relevant categories influencing bikeability. Second, an expert survey is conducted to estimate the importance of these categories to gain a common understanding of bikeability and merge the impacting factors. Third, the defined categories are calculated based on OpenStreetMap data and combined to a comprehensive spatial bikeability index in an automated workflow. The fourth step evaluates the proposed index using a multinomial logit mode choice model to derive the effects of bikeability on travel behavior. The expert process shows a stable interaction between the components defining bikeability, linking specific spatial characteristics of bikeability and associated components. Applied components are, in order of importance, biking facilities along main streets, street connectivity, the prevalence of neighborhood streets, green pathways and other cycle facilities, such as rental and repair facilities. The mode choice model shows a strong positive effect of a high bikeability along the route on choosing the bike as the preferred mode. This confirms that the bike friendliness on a route surrounding has a significant impact on the mode choice. Using universal open data and applying stable weighting in an automated workflow renders the approach of assessing urban bike-friendliness fully transferable and the results comparable. It, therefore, lays the foundation for various large-scale cross-sectional analyses.Michael HardinghausSimon NielandMarius LehneJan WeschkeMDPI AGarticlebikeabilitycyclingactive transportbuilt environmentinfrastructureEnvironmental effects of industries and plantsTD194-195Renewable energy sourcesTJ807-830Environmental sciencesGE1-350ENSustainability, Vol 13, Iss 11584, p 11584 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	bikeability cycling active transport built environment infrastructure Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
spellingShingle	bikeability cycling active transport built environment infrastructure Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 Michael Hardinghaus Simon Nieland Marius Lehne Jan Weschke More than Bike Lanes—A Multifactorial Index of Urban Bikeability
description	The present study aims to deduce bikeability based on a collective understanding and provides a methodology to operationalize its calculation based on open data. The approach contains four steps building on each other and combines qualitative and quantitative methods. The first three steps include the definition and operationalization of the index. First, findings from the literature are condensed to determine relevant categories influencing bikeability. Second, an expert survey is conducted to estimate the importance of these categories to gain a common understanding of bikeability and merge the impacting factors. Third, the defined categories are calculated based on OpenStreetMap data and combined to a comprehensive spatial bikeability index in an automated workflow. The fourth step evaluates the proposed index using a multinomial logit mode choice model to derive the effects of bikeability on travel behavior. The expert process shows a stable interaction between the components defining bikeability, linking specific spatial characteristics of bikeability and associated components. Applied components are, in order of importance, biking facilities along main streets, street connectivity, the prevalence of neighborhood streets, green pathways and other cycle facilities, such as rental and repair facilities. The mode choice model shows a strong positive effect of a high bikeability along the route on choosing the bike as the preferred mode. This confirms that the bike friendliness on a route surrounding has a significant impact on the mode choice. Using universal open data and applying stable weighting in an automated workflow renders the approach of assessing urban bike-friendliness fully transferable and the results comparable. It, therefore, lays the foundation for various large-scale cross-sectional analyses.
format	article
author	Michael Hardinghaus Simon Nieland Marius Lehne Jan Weschke
author_facet	Michael Hardinghaus Simon Nieland Marius Lehne Jan Weschke
author_sort	Michael Hardinghaus
title	More than Bike Lanes—A Multifactorial Index of Urban Bikeability
title_short	More than Bike Lanes—A Multifactorial Index of Urban Bikeability
title_full	More than Bike Lanes—A Multifactorial Index of Urban Bikeability
title_fullStr	More than Bike Lanes—A Multifactorial Index of Urban Bikeability
title_full_unstemmed	More than Bike Lanes—A Multifactorial Index of Urban Bikeability
title_sort	more than bike lanes—a multifactorial index of urban bikeability
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/ea37da07feba4b33995dd117a3b0fb6c
work_keys_str_mv	AT michaelhardinghaus morethanbikelanesamultifactorialindexofurbanbikeability AT simonnieland morethanbikelanesamultifactorialindexofurbanbikeability AT mariuslehne morethanbikelanesamultifactorialindexofurbanbikeability AT janweschke morethanbikelanesamultifactorialindexofurbanbikeability
_version_	1718431561441869824

More than Bike Lanes—A Multifactorial Index of Urban Bikeability

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