Assessing the cluster correspondence between paired point locations

Abstract

Some complex geographic events are associated with multiple point locations. Such events include, but are not limited to, those describing linkages between and among places. The term multi-location event is used in the paper to refer to these geographical phenomena. Through formalization of the multi-location event problem, this paper situates the analysis of multi-location events within the broad context of point pattern analysis techniques. Two alternative approaches (vector autocorrelation analysis and cluster correspondence analysis) to the spatial dependence of paired-location events (i.e., two-location events) are explored, with a discussion of their appropriateness to general multi-location event problems. The research proposes a framework of cluster correspondence analysis for the detection of local non-stationarities in the spatial process generating multi-location events. A new algorithm for local analysis of cluster correspondence is proposed. It is implemented on a large-scale dataset of vehicle theft and recovery location pairs in Buffalo, New York.