A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Impact of urban structure on mobility during COVID-19: A polycentricity perspective
The COVID-19 pandemic has caused immense disruptions, particularly affecting urban mobility as a crucial aspect of infection containment efforts. While numerous studies have investigated various factors driving mobility changes, a substantial gap exists in understanding the influence of spatial structure in this context. This study addresses this gap by investigating the connection between spatial structure, particularly polycentricity, and mobility patterns during the pandemic. The polycentric structure of 384 U.S. Metropolitan Statistical Areas (MSAs) is assessed by employing a novel application of whole graph embedding on dynamic human mobility flow data. Utilizing dimensionality reduction and clustering techniques, the MSAs are categorized into monocentric, intermediate, and polycentric groups. The findings reveal a larger reduction within areas characterized by a higher degree of polycentricity. Despite these significant results, the applied regression model highlights the dominance of factors such as education, employment density, and public transportation. The results emphasize the complex nature of mobility and its drivers. When considering the broader concept of spatial structure, the applied model demonstrates a notable 12 to 25 % enhancement in R2 performance, underscoring the importance of spatial structure on mobility reduction. This study not only offers valuable insights into how spatial structure, especially polycentricity, affected mobility during the pandemic, but also demonstrates the effectiveness of whole graph embedding in modeling the complexity of urban dynamics. The findings have the potential to shape spatial planning strategies, public health policies, and economic activities of urban space.
Impact of urban structure on mobility during COVID-19: A polycentricity perspective
The COVID-19 pandemic has caused immense disruptions, particularly affecting urban mobility as a crucial aspect of infection containment efforts. While numerous studies have investigated various factors driving mobility changes, a substantial gap exists in understanding the influence of spatial structure in this context. This study addresses this gap by investigating the connection between spatial structure, particularly polycentricity, and mobility patterns during the pandemic. The polycentric structure of 384 U.S. Metropolitan Statistical Areas (MSAs) is assessed by employing a novel application of whole graph embedding on dynamic human mobility flow data. Utilizing dimensionality reduction and clustering techniques, the MSAs are categorized into monocentric, intermediate, and polycentric groups. The findings reveal a larger reduction within areas characterized by a higher degree of polycentricity. Despite these significant results, the applied regression model highlights the dominance of factors such as education, employment density, and public transportation. The results emphasize the complex nature of mobility and its drivers. When considering the broader concept of spatial structure, the applied model demonstrates a notable 12 to 25 % enhancement in R2 performance, underscoring the importance of spatial structure on mobility reduction. This study not only offers valuable insights into how spatial structure, especially polycentricity, affected mobility during the pandemic, but also demonstrates the effectiveness of whole graph embedding in modeling the complexity of urban dynamics. The findings have the potential to shape spatial planning strategies, public health policies, and economic activities of urban space.
Impact of urban structure on mobility during COVID-19: A polycentricity perspective
Grossenbacher, Adrian Nicolas (author)
2023-08-25
doi:10.5167/uzh-252251
Grossenbacher, Adrian Nicolas. Impact of urban structure on mobility during COVID-19: A polycentricity perspective. 2023, University of Zurich, Faculty of Science.
Theses
Electronic Resource
English
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