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Controlling patterns of geospatial phenomena / Tomasz F. Stepinski in Geoinformatica, vol 15 n° 3 (July 2011)  

Public [article]  inGeoinformatica > vol 15 n° 3 (July 2011) . - pp 399 - 416 Titre : Controlling patterns of geospatial phenomena Type de document : Article/Communication Auteurs : Tomasz F. Stepinski, Auteur ; W. Ding, Auteur ; C. Eick, Auteur Année de publication : 2011 Article en page(s) : pp 399 - 416 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse spatiale [Termes IGN] exploration de données géographiques [Termes IGN] phénomène géographique [Termes IGN] relation topologique Résumé : (Auteur) Modeling spatially distributed phenomena in terms of its controlling factors is a recurring problem in geoscience. Most efforts concentrate on predicting the value of response variable in terms of controlling variables either through a physical model or a regression model. However, many geospatial systems comprises complex, nonlinear, and spatially non-uniform relationships, making it difficult to even formulate a viable model. This paper focuses on spatial partitioning of controlling variables that are attributed to a particular range of a response variable. Thus, the presented method surveys spatially distributed relationships between predictors and response. The method is based on association analysis technique of identifying emerging patterns, which are extended in order to be applied more effectively to geospatial data sets. The outcome of the method is a list of spatial footprints, each characterized by a unique “controlling pattern”—a list of specific values of predictors that locally correlate with a specified value of response variable. Mapping the controlling footprints reveals geographic regionalization of relationship between predictors and response. The data mining underpinnings of the method are given and its application to a real world problem is demonstrated using an expository example focusing on determining variety of environmental associations of high vegetation density across the continental United States. Numéro de notice : A2011-206 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-010-0107-2 Date de publication en ligne : 29/01/2010 En ligne : https://doi.org/10.1007/s10707-010-0107-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30984 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
057-2011031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

A framework for regional association rule mining and scoping in spatial datasets / W. Ding in Geoinformatica, vol 15 n° 1 (January 2011)  

Public [article]  inGeoinformatica > vol 15 n° 1 (January 2011) . - pp 1 - 28 Titre : A framework for regional association rule mining and scoping in spatial datasets Type de document : Article/Communication Auteurs : W. Ding, Auteur ; C. Eick, Auteur ; X. Yuan, Auteur ; Jing Wang, Auteur ; J.P. Nicot, Auteur Année de publication : 2011 Article en page(s) : pp 1 - 28 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse de groupement [Termes IGN] découverte de connaissances [Termes IGN] exploration de données géographiques [Termes IGN] règle d'association Résumé : (Auteur) The motivation for regional association rule mining and scoping is driven by the facts that global statistics seldom provide useful insight and that most relationships in spatial datasets are geographically regional, rather than global. Furthermore, when using traditional association rule mining, regional patterns frequently fail to be discovered due to insufficient global confidence and/or support. In this paper, we systematically study this problem and address the unique challenges of regional association mining and scoping: (1) region discovery: how to identify interesting regions from which novel and useful regional association rules can be extracted; (2) regional association rule scoping: how to determine the scope of regional association rules. We investigate the duality between regional association rules and regions where the associations are valid: interesting regions are identified to seek novel regional patterns, and a regional pattern has a scope of a set of regions in which the pattern is valid. In particular, we present a reward-based region discovery framework that employs a divisive grid-based supervised clustering for region discovery. We evaluate our approach in a real-world case study to identify spatial risk patterns from arsenic in the Texas water supply. Our experimental results confirm and validate research results in the study of arsenic contamination, and our work leads to the discovery of novel findings to be further explored by domain scientists. Numéro de notice : A2011-026 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-010-0111-6 Date de publication en ligne : 18/06/2010 En ligne : https://doi.org/10.1007/s10707-010-0111-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30807 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
057-2011011	RAB	Revue	Centre de documentation	En réserve L003	Disponible