Detection of linear trends in multi-sensor time series in the presence of autocorrelated noise: Application to the chlorophyll-a SeaWiFS and MERIS datasets and extrapolation to the incoming Sentinel 3-OLCI mission

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Detection of linear trends in multi-sensor time series in the presence of autocorrelated noise: Application to the chlorophyll-a SeaWiFS and MERIS datasets and extrapolation to the incoming Sentinel 3-OLCI mission

The detection of long-term trends in geophysical time series is a key issue in climate change studies. This detection is affected by many factors: the size of the trend to be detected, the length of the available data sets, and the noise properties. Although the noise autocorrelation observed in geo...

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Bibliographic Details
Main Authors:	Saulquin, B., Fablet, R., Mangin, A., Mercier, G., Antoine, David, Fanton d'Andon, O.
Format:	Journal Article
Published:	Wiley-Blackwell Publishing Inc. 2013
Online Access:	http://hdl.handle.net/20.500.11937/7374

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