Spatio-temporal analysis of foot traffic dynamics in Charleston County, South Carolina: before, during, and after COVID-19ston County, South Carolina: Before, During, and After COVID-19.
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引用次数: 0
Abstract
While the COVID-19 pandemic significantly disrupted urban mobility in general, its effects on spatio-temporal foot traffic patterns remain insufficiently explored. This study addresses this issue by analysing foot traffic dynamics across various regions of Charleston County, South Carolina, before, during and after the pandemic. We examined changes across nine distinct stages of the pandemic from 2018 to 2022 at the sub-county level, utilizing point of interest data and public health records. Various machine learning models, including Random Forest, were employed to predict foot traffic trends, achieving high predictive accuracy with an R2 value of 0.88. Our findings reveal varying foot traffic patterns across the county. Prior to the pandemic, foot traffic was generally consistent across county subdivisions, maintaining steady levels in each area. The onset of the pandemic led to significant decreases in foot traffic across most subdivisions, followed by gradual recovery, with some areas surpassing pre-pandemic levels. These results underscore the need for tailored crisis management and urban planning, particularly in midsized counties with similar structures to inform more effective resource allocation and improve risk management in public safety during public health crises.
期刊介绍:
The focus of the journal is on all aspects of the application of geographical information systems, remote sensing, global positioning systems, spatial statistics and other geospatial tools in human and veterinary health. The journal publishes two issues per year.