TIMESAT : A Software Package for Time-Series Processing and Assessment of Vegetation Dynamics

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TIMESAT : A Software Package for Time-Series Processing and Assessment of Vegetation Dynamics

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Publication BookChapter
Title TIMESAT : A Software Package for Time-Series Processing and Assessment of Vegetation Dynamics
Author(s) Eklundh, Lars ; Jönsson, Per
Date 2015
Editor(s) Kuenzer, Claudia; Dech, Stefan; Wagner, Wolfgang
English abstract
Large volumes of data from satellite sensors with high time-resolution 6 exist today, e.g. Advanced Very High Resolution Radiometer (AVHRR) and 7 Moderate Resolution Imaging Spectroradiometer (MODIS), calling for efficient 8 data processing methods. TIMESAT is a free software package for processing 9 satellite time-series data in order to investigate problems related to global change 10 and monitoring of vegetation resources. The assumptions behind TIMESAT are 11 that the sensor data represent the seasonal vegetation signal in a meaningful way, 12 and that the underlying vegetation variation is smooth. A number of processing 13 steps are taken to transform the noisy signals into smooth seasonal curves, including 14 fitting asymmetric Gaussian or logistic functions, or smoothing the data using a 15 modified Savitzky-Golay filter. TIMESAT can adapt to the upper envelope of the 16 data, accounting for negatively biased noise, and can take missing data and quality 17 flags into account. The software enables the extraction of seasonality parameters, 18 like the beginning and end of the growing season, its length, integrated values, etc. 19 TIMESAT has been used in a large number of applied studies for phenology 20 parameter extraction, data smoothing, and general data quality improvement. To 21 enable efficient analysis of future Earth Observation data sets, developments of 22 TIMESAT are directed towards processing of high-spatial resolution data from 23 e.g. Landsat and Sentinel-2, and use of spatio-temporal data processing methods.
DOI http://dx.doi.org/10.1007/978-3-319-15967-6_7 (link to publisher's fulltext)
Publisher Springer
Host/Issue Remote Sensing Time Series
Series/Issue Remote Sensing and Digital Image Processing;22
ISSN 1567-3200
ISBN 978-3-319-15967-6
978-3-319-15966-9
Pages 141-158
Language eng (iso)
Subject(s) remote sensing
photogrammetry
environmental monitoring
environmental analysis
physical geography
Sciences
Research Subject Categories::NATURAL SCIENCES
Handle http://hdl.handle.net/2043/20074 (link to this page)

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