%0 Conference Proceedings
%4 sid.inpe.br/marte2/2017/10.27.14.03.13
%2 sid.inpe.br/marte2/2017/10.27.14.03.14
%@isbn 978-85-17-00088-1
%F 59433
%T Análise espaço‐temporal para redução de ruídos em séries temporais de NDVI
%D 2017
%A Servián, Fernanda Carneiro Rola,
%A Oliveira, Julio Cesar de,
%@electronicmailaddress fernanda.servian@ufv.br
%E Gherardi, Douglas Francisco Marcolino,
%E Aragão, Luiz Eduardo Oliveira e Cruz de,
%B Simpósio Brasileiro de Sensoriamento Remoto, 18 (SBSR)
%C Santos
%8 28-31 maio 2017
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 5119-5123
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%X MODerate resolution Imaging Spectroradiometer (MODIS) data are largely used in multitemporal analysis of various Earth-related phenomena, such as mapping patterns of vegetation phenology and detecting land use/land cover change. NDVI time series are composite mosaics of the best quality pixels over a period of sixteen days. However, it is common to find low quality pixels in the composition that affect the time series analysis due to errors in the atmosphere conditions and in data acquisition. We present a filtering methodology that considers the pixel position (location in space) and time (position in the temporal data series) to define a new value for the low quality pixel. This methodology estimates the value of the point of interest, based first on a linear regression excluding pixels with low coefficient of determination R2 and second on excluding outliers according to a boxplot analysis. Thus, from the remaining group of pixels, a Smooth Spline is generated in order to reconstruct the time series.
%9 Análise de séries temporais de imagens de satélite
%@language pt
%3 59433.pdf