TIMESAT - a program for analyzing time-series of satellite sensor data

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TIMESAT - a program for analyzing time-series of satellite sensor data

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Publication Article, peer reviewed scientific
Title TIMESAT - a program for analyzing time-series of satellite sensor data
Author Jönsson, Per ; Eklundh, Lars
Date 2004
English abstract
Three different least-squares methods for processing time-series of satellite sensor data are presented. The first method uses local polynomial functions and can be classified as an adaptive Savitzky–Golay filter. The other two methods are more clear cut least-squares methods, where data are fit to a basis of harmonic functions and asymmetric Gaussian functions, respectively. The methods incorporate qualitative information on cloud contamination from ancillary datasets. The resulting smooth curves are used for extracting seasonal parameters related to the growing seasons. The methods are implemented in a computer program, TIMESAT, and applied to NASA/NOAA Pathfinder AVHRR Land Normalized Difference Vegetation Index data over Africa, giving spatially coherent images of seasonal parameters such as beginnings and ends of growing seasons, seasonally integrated NDVI and seasonal amplitudes. Based on general principles, the TIMESAT program can be used also for other types of satellite-derived time-series data.
DOI https://doi.org/10.1016/j.cageo.2004.05.006 (link to publisher's fulltext.)
Publisher Elsevier
Host/Issue Computers & Geosciences;8
Volume 30
ISSN 0098-3004
Pages 833-845
Language eng (iso)
Subject function fitting
data smoothing
seasonality
phenology
TIMESAT
NOAA AVHRR
NDVI
CLAVR
Sciences
Research Subject Categories::NATURAL SCIENCES::Earth sciences
Research Subject Categories::TECHNOLOGY::Information technology::Computer science::Computer science
Handle http://hdl.handle.net/2043/10669 Permalink to this page
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