Activity graphs: Spatial graphs as a framework for quantifying individual mobility

Long, Jed A.; Lee, Jinhyung; Reuschke, Darja

doi:10.1007/s10109-023-00405-0

Cited by 4 publications

(1 citation statement)

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“…How mobility is measured can lead to different interpretations and associations with socioeconomic factors. Previous work has identified at least six independent dimensions of human mobility (Fillekes et al, 2019) and there may in fact be more unmeasured or difficult to measure dimensions of human mobility patterns (Long et al, 2023). While we capture two of the most often reported dimensions—range of movement (i.e., radius of gyration) and time/duration of movement (i.e., movement time)—changes in mobility patterns during the COVID‐19 pandemic may differentially impact other movement dimensions as well.…”

Section: Discussionmentioning

confidence: 99%

Associations between socio‐demographic factors and change in mobility due to COVID‐19 restrictions in Ontario, Canada using geographically weighted regression

Klar,

Gilliland,

Long

2023

Canadian Geographies / Géographies canadiennes

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Transportation research has shown that socio‐demographic factors impact people's mobility patterns. During the COVID‐19 pandemic, some of these effects have changed in accordance with changing mobility needs adapting to the pandemic, including restrictions on in‐person gatherings, closure of in‐person businesses, and working from home. We investigate two gaps in current knowledge in this area of transportation research: to what extent the associations between socio‐demographic factors and mobility metrics have changed, and how these associations vary across geographic space. We used aggregate deidentified cell tower location data to measure two mobility metrics—movement time and radius of gyration—and socio‐demographic data from the 2016 Canadian Census to model these associations across Ontario, Canada in 2020 using a linear model and a geographically weighted regression model. We find that certain associations between socio‐demographics and mobility have changed from what we previously observed before the pandemic, and we can see the variation of these associations across space. These findings will improve our understanding of how socio‐demographic factors affect mobility patterns in different communities and demonstrate the importance of measuring these associations at a more fine‐grained level using models that consider spatial variation to best reflect the nature of these associations.

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Section: Discussionmentioning

confidence: 99%