Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1085890
Research center of Embrapa/Collection: Embrapa Informática Agropecuária - Artigo em anais de congresso (ALICE)
Issue Date: 2017
Type of Material: Artigo em anais de congresso (ALICE)
Authors: MACIEL, R. J. S.
SILVA, M. A. S. da
MATOS, L. N.
DOMPIERI, M. H. G.
Additional Information: RENATO JOSE SANTOS MACIEL, CNPTIA; MARCOS AURELIO SANTOS DA SILVA, CPATC; UFS; MARCIA HELENA GALINA DOMPIERI, CPATC.
Title: A neural qualitative approach for automatic territorial zoning.
Publisher: A 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.
Pages: p. 1-7.
Language: en
Notes: GeoComputation 2017.
Keywords: Bacia do Alto Taquari
Zoneamento
Análise espacial
Self-organizing maps
Exploratory spatial analysis
Similarity coefficients
Alto Taquari River Basin
Description: This 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.
NAL Thesaurus: Correspondence analysis
Zoning
Thematic maps
Year: 2018-01-19
Appears in Collections:Artigo em anais de congresso (CNPTIA)

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