The article reviews, under a unified framework, the main approaches to spatial entropy measures. It also illustrates the recent proposal of a set of entropy measures for spatial data, which allows to split the data heterogeneity, usually assessed via Shannon's entropy, into two components: spatial mutual information, identifying the role of space, and spatial residual entropy, measuring heterogeneity due to other sources. Some practical aspects are also covered by presenting the available software for the computation of the considered measures.
Cocchi Daniela, Altieri Linda (2022). Spatial Entropy Measures. New York : John Wiley & Sons, Ltd [10.1002/9781118445112.stat08401].
Spatial Entropy Measures
Cocchi Daniela
;Altieri Linda
2022
Abstract
The article reviews, under a unified framework, the main approaches to spatial entropy measures. It also illustrates the recent proposal of a set of entropy measures for spatial data, which allows to split the data heterogeneity, usually assessed via Shannon's entropy, into two components: spatial mutual information, identifying the role of space, and spatial residual entropy, measuring heterogeneity due to other sources. Some practical aspects are also covered by presenting the available software for the computation of the considered measures.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
