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

Hui Jeong Ha, Youngbin Lee, Kyusik Kim, Sohyun Park and Jinhyung Lee

Environment and Planning B, 2025, vol. 52, issue 2, 509-517

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.

Keywords: Spatial autocorrelation; network autocorrelation; flow; hotspot; R; human mobility (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:sae:envirb:v:52:y:2025:i:2:p:509-517

DOI: 10.1177/23998083241276021

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