Slide 1

Production, visualization and analysis of large volumes of remote sensing images modeled as multidimensional data cubes for the entire Brazilian territory.

GGSOM: Ferramenta de visualização baseada em mapas auto-organizaveis

by Felipe Carvalho de Souza¹, Rafael Duarte Coelho dos Santos¹, Karine Reis Ferreira¹

1 – Instituto Nacional de Pesquisas Espaciais (INPE) Sao José dos Campos – SP – Brazil

ISSN: 2179-4847

Publisher: XX GEOINFO | Published: 13 November 2019.


Analysis of multidimensional and time series data is useful and pertinent to several different applications, being a challenge due to the volume and complexity of the data. A possible approach for analysis of this kind of data is to use clustering algorithms to reduce the dimensionality of the data. This paper presents a tool for clustering and visualization of data, called ggsom, which uses a technique for data dimensionality reduction through projection of the data in a smaller number of dimensions by the Kohonen’s Self-Organizing Map. The tool is evaluated with data from time series of vegetation coverage from Bahia

Keywords: geoinformatica, time series

© This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

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SOUZA, F. C.; SANTOS, R. D. C.; FERREIRA, K. R. GGSOM: ferramenta de visualização baseada em mapas auto-organizáveis. In: SIMPÓSIO BRASILEIRO DE GEOINFORMÁTICA, 20. (GEOINFO), 2019, São José dos Campos. Anais do 20º Simpósio Brasileiro de Geoinformática… São José dos Campos: INPE, 2019. On-line. ISSN 2179-4847. IBI: <8JMKD3MGPDW34R/3UFHMQ8>. Disponível em: <>.

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