%0 Book Section
%@holdercode {isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}
%4 sid.inpe.br/mtc-m21b/2017/08.17.18.33
%A Santos, Lorena Alves dos,
%A Simões, Rolf Ezequiel de Oliveira,
%A Ferreira, Karine Reis,
%A Queiroz, Gilberto Ribeiro,
%A Camara, Gilberto,
%A Santos, Rafael Duarte Coelho dos,
%@secondarytype PRE LI
%B Computational Science and Its Applications – ICCSA 2017
%D 2017
%E Gervasi, Osvaldo,
%E Murgante, Beniamino,
%E Misra, Sanjay,
%E Borruso, Giuseppe,
%E Torre, Carmelo M.,
%E Rocha, Ana Maria A. C.,
%E Taniar, David,
%E Apduhan, Bernady O.,
%E Stankova, Elena,
%E Cuzzocrea, Alfredo,
%@secondarykey INPE--/
%I Springer
%K Time series clustering, MODIS vegetation indexes, Land cover change classification, Self-Organizing Map (SOM).
%P 662-673
%S Lecture Notes in Computer Science , 10409
%T Clustering methods to asses land cover samples of modis vegetation indexes time series
%X MODIS vegetation indexes time series have been widely used to build land cover change maps on large scales. In this scope, to obtain good quality maps using supervised classification methods, it is crucial to select representative training samples of land cover change classes. In this paper, we evaluate two clustering methods, Hierarchical and Self-Organizing Map (SOM), to assess land cover samples of MODIS vegetation indexes time series. As we show, these techniques are suitable tools for assisting users to select representative land cover change samples from MODIS vegetation indexes time series. We present the accuracy of both methods for a case study in Ipiranga do Norte municipality in Mato Grosso state, Brazil.
%@area COMP
%@electronicmailaddress lorena.santos@inpe.br
%@electronicmailaddress rolf.simoes@inpe.br
%@electronicmailaddress karine.ferreira@inpe.br
%@electronicmailaddress gilberto.queiroz@inpe.br
%@electronicmailaddress gilberto.camara@inpe.br
%@electronicmailaddress rafael.santos@inpe.br
%@documentstage not transferred
%@group CAP-COMP-SESPG-INPE-MCTIC-GOV-BR
%@group CAP-COMP-SESPG-INPE-MCTIC-GOV-BR
%@group DIDPI-CGOBT-INPE-MCTIC-GOV-BR
%@group DIDPI-CGOBT-INPE-MCTIC-GOV-BR
%@group DIDPI-CGOBT-INPE-MCTIC-GOV-BR
%@group LABAC-COCTE-INPE-MCTIC-GOV-BR
%@dissemination BNDEPOSITOLEGAL
%@isbn 978-331962406-8
%@usergroup simone
%@resumeid
%@resumeid
%@resumeid 8JMKD3MGP5W/3C9JHKN
%@resumeid
%@resumeid 8JMKD3MGP5W/3C9JHB8
%@resumeid 8JMKD3MGP5W/3C9JJ4N
%@nexthigherunit 8JMKD3MGPCW/3EQCCU5 8JMKD3MGPCW/3ESGTTP 8JMKD3MGPCW/3F2PHGS
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@versiontype publisher
%2 sid.inpe.br/mtc-m21b/2017/08.17.18.33.40