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

IF 2.6 3区 经济学 Q2 ENVIRONMENTAL STUDIES Environment and Planning B: Urban Analytics and City Science Pub Date : 2024-08-21 DOI:10.1177/23998083241276021
Hui Jeong Ha, Youngbin Lee, Kyusik Kim, Sohyun Park, Jinhyung Lee
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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.
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Spnaf:用于分析和绘制流量数据集热点的 R 软件包
本文介绍了{spnaf}(流动的空间网络自相关性),这是一个基于 Berglund 和 Karlström 的 G 指数设计的 R 软件包,用于对流动(如人类流动、交通和动物移动)数据集进行热点分析。我们通过两个数据形式的分析示例展示了 {spnaf} 软件包的实用性:1)美国俄亥俄州哥伦布市的共享单车出行模式(使用多边形数据);2)美国机场的旅客出行模式(使用点数据)。{spnaf}可从 R 综合存档网络(CRAN)下载,其中包含可立即使用的小节和样本数据/代码。该软件包解决了现有空间分析软件包的局限性,并强调其在检测流量热点方面的效率。它非常适用于各种城市和地理数据科学应用。{spnaf}目前仍处于早期阶段,我们希望感兴趣的读者能为软件包的开发和改进献计献策。
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CiteScore
6.10
自引率
11.40%
发文量
159
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