Information and complexity analysis of spatial data
Metadatos
Afficher la notice complèteAuteur
Angulo Ibáñez, José Miguel; Esquivel Sánchez, Francisco Javier; Madrid García, Ana Esther; Alonso Morales, Francisco JavierEditorial
Elsevier
Materia
Entropy Divergence Multifractality Product complexity Structural properties
Date
2021-04Referencia bibliográfica
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
Patrocinador
MCIU/AEI/ERDF, EU, Spain PGC2018-098860-B-I00; ERDF Operational Programme 2014–2020 A-FQM-345-UGR18; Regional Government of Andalusia, SpainRésumé
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.