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.

熵度量是环境和生态科学中描述数据异质性的标准工具。本文回顾了一系列空间熵指数，其中一些是最近的，适用于处理呈现有限数量类别的变量的空间数据。特别关注生物多样性数据，但方法可以应用于任何其他环境现象。这里引入了新的 R 包 SpatEntropy 来计算实践中的空间熵度量。从传统的熵度量扩展到它们的空间版本是该包的一个独特功能，它能够处理面数据和点数据。还介绍了一个实际部分，其中考虑了两种类型的环境数据，分别涉及树木生物多样性和城市扩张。