Efficient Computation of Spatial Entropy Measures.

ABSTRACT: Entropy indices are commonly used to evaluate the heterogeneity of spatially arranged data by exploiting various approaches capable of including spatial information. Unfortunately, in practical studies, difficulties can arise regarding both the availability of computational tools for fast and easy implementation of these indices and guidelines supporting the correct interpretation of the results. The present work addresses such issues for the most known spatial entropy measures: the approach based on area partitions, the one based on distances between observations, and the decomposable spatial entropy. The newly released version of the R package SpatEntropy is introduced here and we show how it properly supports researchers in real case studies. This work also answers practical questions a

SUBMITTER: Altieri L 

PROVIDER: S-EPMC10742711 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature