This paper proposes a spatiotemporal clustering algorithm and its implementation in the R package spotoroo. This work is motivated by the catastrophic bushfires in Australia throughout the summer of 2019-2020 and made possible by the availability of satellite hotspot data. The algorithm is inspired by two existing spatiotemporal clustering algorithms but makes enhancements to cluster points spatially in conjunction with their movement across consecutive time periods. It also allows for the adjustment of key parameters, if required, for different locations and satellite data sources. Bushfire data from Victoria, Australia, is used to illustrate the algorithm and its use within the package.

翻译：本文提出了一种时空聚类算法及其在R语言包spotoroo中的实现。该工作的研究动机源于2019-2020年夏季澳大利亚发生的灾难性森林大火，而卫星热点数据的可用性使其成为可能。该算法受两种现有时空聚类算法的启发，但在空间聚类的基础上，结合了连续时间段内点的移动特性进行了增强。此外，该算法允许根据不同的地点和卫星数据源调整关键参数（如有需要）。本文以澳大利亚维多利亚州的森林火灾数据为例，阐述了该算法及其在软件包中的应用。