Over the last decade, distance-based methods have been introduced and then improved in the field of spatial economics to gauge the geographic concentration of activities. There is a growing literature on this theme including new tools, discussions on specific properties and various...

In many fields, the spatial clustering of sampled data points has significant consequences. Therefore, several indices have been proposed to assess the degree of clustering affecting datasets (e.g. the Morisita index, Ripley’s K-function and Rényi’s information). The classical Morisita...

Graph theory and entropy concepts are used to retrieve and quantify information in dD-sets of points. In this approach, each disordered set of points is assigned a graph which is considered as a probe that gives access to some information typical of the kind of graph chosen. It is shown that...