Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1085890
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dc.contributor.authorMACIEL, R. J. S.
dc.contributor.authorSILVA, M. A. S. da
dc.contributor.authorMATOS, L. N.
dc.contributor.authorDOMPIERI, M. H. G.
dc.date.accessioned2018-01-19T19:10:00Z-
dc.date.available2018-01-19T19:10:00Z-
dc.date.created2018-01-19
dc.date.issued2017
dc.identifier.citationA neural qualitative approach for automatic territorial zoning. In: INTERNATIONAL CONFERENCE ON GEOCOMPUTATION, 21., 2017, Leeds. Celebrating 21 years of GeoComputation: extended abstracts. Leeds: University of Leeds, 2017.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1085890-
dc.descriptionThis article presents the application of the Self-Organizing Maps (SOM) as an exploratory tool for automatic territorial zoning by combining the handle of categorical data and the other for automatic clustering. The SOM online learning algorithm had been chosen to treat categorical data by using the dot product method and the Sorense-Dice binary similarity coefficient. To automatically perform a spatial clustering, an adaptation of the automatic clustering Costa-Netto algorithm had been also proposed. The correspondence analysis had been used to examine the profiles of each homogeneous zones. To explore the approach it has been performed the territorial zoning of the Alto Taquari River Basin, Brazil, using as input data a set of thematic maps. The results indicate the applicability of the approach to perform the exploratory territorial zoning.
dc.language.isoengeng
dc.rightsopenAccesseng
dc.subjectBacia do Alto Taquari
dc.subjectZoneamento
dc.subjectAnálise espacial
dc.subjectSelf-organizing maps
dc.subjectExploratory spatial analysis
dc.subjectSimilarity coefficients
dc.subjectAlto Taquari River Basin
dc.titleA neural qualitative approach for automatic territorial zoning.
dc.typeArtigo em anais e proceedings
dc.date.updated2020-01-21T11:11:11Zpt_BR
dc.subject.nalthesaurusCorrespondence analysis
dc.subject.nalthesaurusZoning
dc.subject.nalthesaurusThematic maps
dc.description.notesGeoComputation 2017.
dc.format.extent2p. 1-7.
riaa.ainfo.id1085890
riaa.ainfo.lastupdate2020-01-21 -02:00:00
dc.contributor.institutionRENATO JOSE SANTOS MACIEL, CNPTIA; MARCOS AURELIO SANTOS DA SILVA, CPATC; UFS; MARCIA HELENA GALINA DOMPIERI, CPATC.
Appears in Collections:Artigo em anais de congresso (CNPTIA)

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