Spatial Statistics along Networks

AbstractSpatial statistics along networks is a branch of spatial statistics. Traditional spatial statistics deals with events occurring on a plane, referred to asplanar spatial statistics. By contrast, spatial statistics along networks, referred to in parallel asnetwork spatial statistics, deals with events occurring along networks. The events occurring “along” a network are of two types: those directly occurring on a network, for example, traffic accidents, and those occurring alongside a network, for example, stores facing a street. Networks may potentially include corridors, roads, railways, gas and oil pipelines, sewer systems, rivers, canals, electric wires, neurons, the Internet, social networks (e.g., SNS), and so on. Network spatial statistics is applied to various studies, for instance, pedestrian, car, and bicycle accidents, roadkill, street crimes, contamination of rivers, floods, facility locations, tree falls on a railway, etc. This article first describes the most basic hypothesis used in network spatial statistics, called thecompletely spatial randomness(CSR) hypothesis. Next, the article introduces nine methods used for network spatial statistics, that is, Voronoi diagrams, nearest‐neighbor distance method,Kfunction method, spatial autocorrelation, point cluster analysis, kernel density estimation, spatial interpolation, and software for network spatial statistics.