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

被引:0
|
作者
Ha, Hui Jeong [1 ]
Lee, Youngbin [2 ]
Kim, Kyusik [3 ]
Park, Sohyun [4 ]
Lee, Jinhyung [1 ]
机构
[1] Western Univ, Dept Geog & Environm, 1151 Richmond St, London, ON N6A 3K7, Canada
[2] Seoul Natl Univ, Dept Civil & Environm Engn, Seoul, South Korea
[3] Florida State Univ, Dept Geog, Tallahassee, FL USA
[4] George Mason Univ Korea, Computat & Data Sci, Incheon, South Korea
基金
新加坡国家研究基金会;
关键词
Spatial autocorrelation; network autocorrelation; flow; hotspot; R; human mobility; NETWORK AUTOCORRELATION;
D O I
10.1177/23998083241276021
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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 Karlstr & ouml;m'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.
引用
收藏
页码:509 / 517
页数:9
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