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Local and global spatio-temporal entropy indices based on distance- ratios and co-occurrences distributions

hal.structure.identifierNottingham Geospatial Institute [NGI]
dc.contributor.authorLEIBOVICI, Didier G.
hal.structure.identifierInstitut de Recherche de l'Ecole Navale [IRENAV]
dc.contributor.authorCLARAMUNT, Christophe
hal.structure.identifierLittoral, Environnement, Télédétection, Géomatique [LETG - Brest]
dc.contributor.authorLE GUYADER, Damien
hal.structure.identifierInstitut de Recherche de l'Ecole Navale [IRENAV]
dc.contributor.authorBROSSET, David
dc.date.accessioned2021-05-14T09:55:14Z
dc.date.available2021-05-14T09:55:14Z
dc.date.issued2014-05
dc.identifier.issn1365-8816
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/77674
dc.description.abstractEnWhen it comes to characterize the distribution of ‘things’ observed spatially andidentified by their geometries and attributes, the Shannon entropy has been widely used in different domains such as ecology, regional sciences, epidemiology and image analysis. In particular, recent research has taken into account the spatial patterns derived from topological and metric properties in order to propose extensions to the measure of entropy. Based on two different approaches using either distance-ratios or co-occurrences of observed classes, the research developed in this paper introduces several new indices and explores their extensions to the spatio-temporal domains which are derived whilst investigating further their application as global and local indices. Using a multiplicative space-time integration approach either at a macro or micro-level, the approach leads to a series of spatio-temporal entropy indices including from combining co-occurrence and distances-ratios approaches. The framework developed is complementary to the spatio-temporal clustering problem, introducing a more spatial and spatio-temporal structuring perspective using several indices characterizing the distribution of several class instances in space and time. The whole approach is first illustrated on simulated data evolutions of three classes over seven time stamps.Preliminary results are discussed for a study of conflicting maritime activities in the Bay of Brest where the objective is to explore the spatio-temporal patterns exhibited by a categorical variable with six classes, each representing a conflict between two maritime activities.
dc.language.isoen
dc.publisherTaylor & Francis
dc.subject.eninformation theory
dc.subject.enentropy
dc.subject.enspatio-temporal entropy
dc.subject.enco-occurrence data
dc.subject.ennearest neighbor
dc.subject.enspatial structuring
dc.subject.enpoint pattern analysis
dc.title.enLocal and global spatio-temporal entropy indices based on distance- ratios and co-occurrences distributions
dc.typeArticle de revue
dc.identifier.doi10.1080/13658816.2013.871284
dc.subject.halInformatique [cs]/Théorie de l'information [cs.IT]
bordeaux.journalInternational Journal of Geographical Information Science
bordeaux.page1061-1084
bordeaux.volume28
bordeaux.hal.laboratoriesInstitut de Mécanique et d’Ingénierie de Bordeaux (I2M) - UMR 5295*
bordeaux.issue5
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.institutionINRAE
bordeaux.institutionArts et Métiers
bordeaux.peerReviewedoui
hal.identifierhal-01208089
hal.version1
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01208089v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=International%20Journal%20of%20Geographical%20Information%20Science&rft.date=2014-05&rft.volume=28&rft.issue=5&rft.spage=1061-1084&rft.epage=1061-1084&rft.eissn=1365-8816&rft.issn=1365-8816&rft.au=LEIBOVICI,%20Didier%20G.&CLARAMUNT,%20Christophe&LE%20GUYADER,%20Damien&BROSSET,%20David&rft.genre=article


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