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

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  • Hui Jeong Ha
  • Youngbin Lee
  • Kyusik Kim
  • Sohyun Park
  • Jinhyung Lee

Abstract

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.

Suggested Citation

  • Hui Jeong Ha & Youngbin Lee & Kyusik Kim & Sohyun Park & Jinhyung Lee, 2025. "Spnaf: An R package for analyzing and mapping the hotspots of flow datasets," Environment and Planning B, , vol. 52(2), pages 509-517, February.
    • Handle: RePEc:sae:envirb:v:52:y:2025:i:2:p:509-517
    DOI: 10.1177/23998083241276021
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    References listed on IDEAS

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    1. Yongwan Chun, 2008. "Modeling network autocorrelation within migration flows by eigenvector spatial filtering," Journal of Geographical Systems, Springer, vol. 10(4), pages 317-344, December.
    2. Svante Berglund & Anders Karlström, 1999. "Identifying local spatial association in flow data," Journal of Geographical Systems, Springer, vol. 1(3), pages 219-236, October.
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