Spatial entropy for biodiversity and environmental data: The R-package SpatEntropy

Entropy measures are standard tools in environmental and ecological sciences to describe the heterogeneity of data. This paper reviews a selection of spatial entropy indices, some of which are very recent, suitable to deal with spatial data on variables presenting a finite number of categories. A special focus is given on biodiversity data, but methods can be applied to any other environmental phenomena. The new R package SpatEntropy is here introduced to compute spatial entropy measures in practice. The extension from traditional entropy measures to their spatial version is a unique feature of the package, which is able to work with both areal and point data. A practical part is also presented, where two types of environmental data are considered, regarding trees biodiversity and urban expansion, respectively. The package SpatEntropy is run over these dataset and shown to represent a user-friendly and helpful tool for new package users.

Automated summary

This paper reviews the application of entropy measures as standard tools in environmental and ecological sciences to describe data heterogeneity, with a focus on spatial entropy indices and related processing tools. Special attention is given to biodiversity data, and the practical application of these methods to other environmental phenomena is demonstrated. The introduction of the new R package SpatEntropy shows readers how to compute spatial entropy measures in practice, highlighting its unique feature of extending traditional entropy measures to their spatial version.