Riding through the pandemic: Using Strava data to monitor the impacts of COVID-19 on spatial patterns of bicycling
COVID-19 prompted a bike boom and cities around the world responded to increased demand for space to ride with street reallocations. Evaluating these interventions has been limited by a lack of spatially-temporally continuous ridership data. Our paper aims to address this gap using crowdsourced data...
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Format: | Article |
Language: | English |
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Elsevier
2022-09-01
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Series: | Transportation Research Interdisciplinary Perspectives |
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Online Access: | http://www.sciencedirect.com/science/article/pii/S2590198222001270 |
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author | Jaimy Fischer Trisalyn Nelson Meghan Winters |
author_facet | Jaimy Fischer Trisalyn Nelson Meghan Winters |
author_sort | Jaimy Fischer |
collection | DOAJ |
description | COVID-19 prompted a bike boom and cities around the world responded to increased demand for space to ride with street reallocations. Evaluating these interventions has been limited by a lack of spatially-temporally continuous ridership data. Our paper aims to address this gap using crowdsourced data on bicycle ridership. We evaluate changes in spatial patterns of bicycling during the first wave of the COVID-19 pandemic (Apr – Oct 2020) in Vancouver, Canada using Strava data and a local indicator of spatial autocorrelation. We map statistically significant change in ridership and reference clusters of change to a high-resolution base map. Amongst streets where bicycling increased, we measured the proportion of increase occurring on pre-existing bicycle facilities or street reallocations compared to streets without. In all our analyses, we evaluate patterns across subsets of Strava data representing recreation, commuting, and ridership generated by women and older adults (55 + ). We found consistent and unique patterns by trip purpose and demographics: samples generated by women and older adults showed increases near green and blue spaces and on street reallocations that increased access to parks, and these patterns were also mirrored in the recreation sample. Commute ridership highlighted distinct patterns of increase around the hospital district. Across all subsets most increases occurred on bicycle facilities (pre-existing or provisional), with a strong preference for high-comfort facilities. We demonstrate that changes in spatial patterns of bicycle ridership can be monitored using Strava data, and that nuanced patterns can be identified using trip and demographic labels in the data. |
first_indexed | 2024-04-12T19:05:27Z |
format | Article |
id | doaj.art-abe870163cba442dacc9253371247229 |
institution | Directory Open Access Journal |
issn | 2590-1982 |
language | English |
last_indexed | 2024-04-12T19:05:27Z |
publishDate | 2022-09-01 |
publisher | Elsevier |
record_format | Article |
series | Transportation Research Interdisciplinary Perspectives |
spelling | doaj.art-abe870163cba442dacc92533712472292022-12-22T03:20:02ZengElsevierTransportation Research Interdisciplinary Perspectives2590-19822022-09-0115100667Riding through the pandemic: Using Strava data to monitor the impacts of COVID-19 on spatial patterns of bicyclingJaimy Fischer0Trisalyn Nelson1Meghan Winters2Faculty of Health Sciences, Simon Fraser University, Burnaby V5A 1S6, Canada; Corresponding author.Department of Geography, University of California Santa Barbara, Santa Barbara, Ellison Hall, Isla Vista, CA 93117, USAFaculty of Health Sciences, Simon Fraser University, Burnaby V5A 1S6, CanadaCOVID-19 prompted a bike boom and cities around the world responded to increased demand for space to ride with street reallocations. Evaluating these interventions has been limited by a lack of spatially-temporally continuous ridership data. Our paper aims to address this gap using crowdsourced data on bicycle ridership. We evaluate changes in spatial patterns of bicycling during the first wave of the COVID-19 pandemic (Apr – Oct 2020) in Vancouver, Canada using Strava data and a local indicator of spatial autocorrelation. We map statistically significant change in ridership and reference clusters of change to a high-resolution base map. Amongst streets where bicycling increased, we measured the proportion of increase occurring on pre-existing bicycle facilities or street reallocations compared to streets without. In all our analyses, we evaluate patterns across subsets of Strava data representing recreation, commuting, and ridership generated by women and older adults (55 + ). We found consistent and unique patterns by trip purpose and demographics: samples generated by women and older adults showed increases near green and blue spaces and on street reallocations that increased access to parks, and these patterns were also mirrored in the recreation sample. Commute ridership highlighted distinct patterns of increase around the hospital district. Across all subsets most increases occurred on bicycle facilities (pre-existing or provisional), with a strong preference for high-comfort facilities. We demonstrate that changes in spatial patterns of bicycle ridership can be monitored using Strava data, and that nuanced patterns can be identified using trip and demographic labels in the data.http://www.sciencedirect.com/science/article/pii/S2590198222001270Bicycle infrastructureBicycling ridershipCOVID-19CrowdsourcedSpatial statisticsStrava |
spellingShingle | Jaimy Fischer Trisalyn Nelson Meghan Winters Riding through the pandemic: Using Strava data to monitor the impacts of COVID-19 on spatial patterns of bicycling Transportation Research Interdisciplinary Perspectives Bicycle infrastructure Bicycling ridership COVID-19 Crowdsourced Spatial statistics Strava |
title | Riding through the pandemic: Using Strava data to monitor the impacts of COVID-19 on spatial patterns of bicycling |
title_full | Riding through the pandemic: Using Strava data to monitor the impacts of COVID-19 on spatial patterns of bicycling |
title_fullStr | Riding through the pandemic: Using Strava data to monitor the impacts of COVID-19 on spatial patterns of bicycling |
title_full_unstemmed | Riding through the pandemic: Using Strava data to monitor the impacts of COVID-19 on spatial patterns of bicycling |
title_short | Riding through the pandemic: Using Strava data to monitor the impacts of COVID-19 on spatial patterns of bicycling |
title_sort | riding through the pandemic using strava data to monitor the impacts of covid 19 on spatial patterns of bicycling |
topic | Bicycle infrastructure Bicycling ridership COVID-19 Crowdsourced Spatial statistics Strava |
url | http://www.sciencedirect.com/science/article/pii/S2590198222001270 |
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