Information and complexity analysis of spatial data Angulo Ibáñez, José Miguel Esquivel Sánchez, Francisco Javier Madrid García, Ana Esther Alonso Morales, Francisco Javier Entropy Divergence Multifractality Product complexity Structural properties This work was supported by MCIU/AEI/ERDF, EU, Spain grant PGC2018-098860-B-I00, and by grant A-FQM-345-UGR18 cofinanced by the ERDF Operational Programme 2014–2020 and the Economy and Knowledge Council of the Regional Government of Andalusia, Spain . Information Theory provides a fundamental basis for analysis, and for a variety of subsequent methodological approaches, in relation to uncertainty quantification. The transversal character of concepts and derived results justifies its omnipresence in scientific research, in almost every area of knowledge, particularly in Physics, Communications, Geosciences, Life Sciences, etc. Information-theoretic aspects underlie modern developments on complexity and risk. A proper use and exploitation of structural characteristics inherent to spatial data motivates, according to the purpose, special considerations in this context. In this paper, some relevant approaches introduced regarding the informational analysis of spatial data, related aspects concerning complexity analysis, and, in particular, implications in relation to the structural assessment of multifractal point patterns, are reviewed under a conceptually connective evolutionary perspective. 2024-09-18T08:31:01Z 2024-09-18T08:31:01Z 2021-04 journal article José M. Angulo, Francisco J. Esquivel, Ana E. Madrid, Francisco J. Alonso, Information and complexity analysis of spatial data, Spatial Statistics, Volume 42, 2021, https://doi.org/10.1016/j.spasta.2020.100462, ISSN 2211-6753 https://hdl.handle.net/10481/94629 10.1016/J.SPASTA.2020.100462 eng open access Elsevier