“…Spatiotemporal clustering, one of the most significant branches of spatiotemporal data mining, aims to group a set of spatiotemporal objects into clusters so that objects within a cluster have high similarity with one another but are dissimilar to objects in other clusters (Bai, Cheng, Liang, Shen, & Guo, 2017;Khairullah, Gawad, Roose, & Van Bael, 2016;Shekhar, Zhang, & Huang, 2005). Spatiotemporal clustering analysis is a major tool in many engineering and scientific applications, including pattern recognition, data segmentation, outlier detection, discretization of continuous attributes, data reduction, image processing and noise filtering (Birant & Kut, 2007;Hagenauer & Helbich, 2013;He, Ling, Zhang, & Gong, 2018;Hu, Mao, & McKenzie, 2019;Li, Liu, Tang, & Deng, 2018;Shi et al, 2019;Song, Song, & Kuang, 2019).…”