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%0 Conference Proceedings
%4 sid.inpe.br/mtc-m16d/2019/11.27.18.35
%2 sid.inpe.br/mtc-m16d/2019/11.27.18.35.10
%@issn 2179-4847
%A Moreira, Noeli Aline Particcelli,
%A Körting, Thales Sehn,
%A Dutra, Luciano Vieira,
%A Castejon, Emiliano Ferreira,
%A Arai, Egidio,
%@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)
%@electronicmailaddress noeli.aline@inpe.br
%@electronicmailaddress thales.korting@inpe.br
%@electronicmailaddress luciano.dutra@inpe.br
%@electronicmailaddress emiliano.castejon@inpe.br
%@electronicmailaddress egidio.arai@inpe.br
%T Calibração relativa para extensão de assinaturas em série de imagens MODIS
%B Simpósio Brasileiro de Geoinformática (GEOINFO)
%D 2019
%E Lisboa Filho, Jugurta,
%E Monteiro, Antonio Miguel Vieira,
%S Anais do 20º Simpósio Brasileiro de Geoinformática
%8 11 -13 nov. 2019
%J São José dos Campos
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%C São José dos Campos
%K geoinformatica.
%X Time series data analysis must consider variations due to atmospheric effects, lighting and sensor parameters. Relative calibration allows to harmonize images of a series using its statistical parameters as a reference, thus allowing comparative analysis based on a reference date. This paper emphasizes a relative calibration process performed on MODIS multitemporal images as part of a process in a subpixel mapping methodology. This process allowed to calculate a linear regression model year by year in order to calibrate images from 2013 to 2017, based on the year 2012, and thus contributing to coverage classes detection closer to reality which were not previously identified.
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%@language pt
%3 230-236.pdf


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