Event pattern analysis: Spatial clustering of sequential events and temporal change of events over time

Abstract

AbstractThis article develops a method for analyzing spatial and temporal event patterns. Events in this article refer to zero‐dimensional objects in the spatiotemporal dimension, which represent the occurrence of crimes, traffic accidents, earthquakes, and so forth. The spatial clustering of sequential events and the increase and decrease in events over time are discussed. These patterns are often observed and analyzed in various academic fields, such as criminology, epidemiology, and geography. However, analytical methods for these patterns have not yet been fully developed. To fill the research gap, this article proposes a new method for analyzing these event patterns. Two statistical measures are utilized, one represents the degree of the spatial clustering of sequential events, and the other evaluates the increase and decrease of events over time. The method is applied to the analysis of the spatial and temporal patterns of the openings of new shops and restaurants in Shibuya‐ku, Tokyo. The results gave us interesting empirical findings and indicated the soundness of the method.