Space-time Network Analysis of Public Bicycle Use and its Visualization Using Spatial Network Autocorrelation

This paper introduces {spnaf} (spatial network autocorrelation for flows), an R package designed for the hotspot analysis of flow (e.g., human mobility, transportation, and animal movement) datasets based on Berglund and Karlström’s G index. We demonstrate the utility of the {spnaf} package through two example analyses by data forms: 1) bike-sharing trip patterns in Columbus, Ohio, USA, using polygon data, and 2) U.S. airports’ passenger travel patterns, using point data. The {spnaf} is available for download from the Comprehensive R Archive Network (CRAN), which contains a vignette and sample data/code for immediate use. This package addresses limitations in existing spatial analysis packages and emphasizes its efficiency in detecting flow hotspots. It is highly applicable in various urban and geographic data science applications. {spnaf} is still in its early stages and we hope that interested readers can contribute to the development and enhancement of the package.

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Space-time Network Analysis of Public Bicycle Use and its Visualization Using Spatial Network Autocorrelation

Cited by 5 publications

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Spnaf: An R package for analyzing and mapping the hotspots of flow datasets

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