A0567
Title: Quantifying the unexpected: Developing statistical tests for spatial entropy in ecology and landscape analysis
Authors: Linda Altieri - University of Bologna (Italy) [presenting]
Abstract: Shannon entropy is widely used in ecology, biodiversity, and landscape studies to quantify the heterogeneity of a system. Its appeal lies in its versatility and broad applicability, including to qualitative and categorical data. However, its known limitations in capturing spatial structure have led to the development of alternative entropy-based measures tailored for spatial data, such as those proposed by Batty, Karlstrom, O'Neill, Leibovici, and Altieri, among others. While these spatial entropy measures hold great potential for describing complex spatial patterns, they ultimately reduce system complexity to a single value. As such, it remains difficult to assess whether the observed heterogeneity meaningfully deviates from an expected level, either under a null model or in comparison to other configurations. To date, statistical testing procedures for entropy values have only been developed for Shannon entropy in non-spatial settings, leaving a gap in the spatial domain. The development of formal statistical tests for spatial entropy measures is proposed. These tests aim to provide a framework for assessing the significance of observed spatial heterogeneity, supporting more rigorous interpretation and comparison across spatial systems.
