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%0 Conference Proceedings
%4 sid.inpe.br/mtc-m16d/2019/11.27.19.30
%2 sid.inpe.br/mtc-m16d/2019/11.27.19.30.18
%@issn 2179-4847
%A Matosak, Bruno Menini,
%A Rodrigues, Marcos Antônio de Almeida,
%A Uehara, Tatiana Dias Tardelli,
%A Körting, Thales Sehn,
%A Fonseca, Leila Maria Garcia,
%@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 bruno.matosak@inpe.br
%@electronicmailaddress marcos.almeida@inpe.br
%@electronicmailaddress tatiana.uehara@inpe.br
%@electronicmailaddress thales.korting@inpe.br
%@electronicmailaddress leila.fonseca@inpe.br
%T Filtering Algorithm for MODIS Time Series Data
%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 This paper describes an easy to use and friendly Graphical User Interface (GUI) of a smoothing tool for remote sensing time series, focused in MODIS data. This tool is developed in Python environment and thus uses packages, libraries, modules and functions to retrieve and filter time series data, and display temporal information based on user defined parameters. The GUI allows users to choose MODIS products, different noise-removal filters, parameters for outlier removal, and also creating animations based on the time series, of predefined areas. Time series processed by our system can be downloaded in the well known CSV format, to be used in other applications.
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%@language pt
%3 304-306.pdf


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