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Open AccessArticle

Global Gap-Free MERIS LAI Time Series (2002–2012)

German Aerospace Center (DLR), German Remote Sensing Data Center (DFD), Münchner Strasse 20, Wessling D-82234, Germany
Brockmann Consult GmbH, Max-Planck-Strasse 2, Geesthacht D-21502, Germany
Institut National de la Recherche Agronomique (INRA), Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH UMR) 1114, Agroparc, Avignon F-84914, France
Author to whom correspondence should be addressed.
Academic Editors: Eileen H. Helmer, Clement Atzberger and Prasad S. Thenkabail
Remote Sens. 2016, 8(1), 69;
Received: 12 November 2015 / Revised: 14 December 2015 / Accepted: 21 December 2015 / Published: 15 January 2016
This article describes the principles used to generate global gap-free Leaf Area Index (LAI) time series from 2002–2012, based on MERIS (MEdium Resolution Imaging Spectrometer) full-resolution Level1B data. It is produced as a series of 10-day composites in geographic projection at 300-m spatial resolution. The processing chain comprises geometric correction, radiometric correction, pixel identification, LAI calculation with the BEAM (Basic ERS & Envisat (A)ATSR and MERIS Toolbox) MERIS vegetation processor, re-projection to a global grid and temporal aggregation selecting the measurement closest to the mean value. After the LAI pre-processing, we applied time series analysis to fill data gaps and to filter outliers using the technique of harmonic analysis (HA) in combination with mean annual and multiannual phenological data. Data gaps are caused by clouds, sensor limitations due to the solar zenith angle (<10°), topography and intermittent data reception. We applied our technique for the whole period of observation (July 2002–March 2012). Validation, carried out with VALERI (Validation of Land European Remote Sensing Instruments) and BigFoot data, revealed a high degree (R2 : 0.88) of agreement on a global scale. View Full-Text
Keywords: Leaf Area Index; MERIS; time series analysis Leaf Area Index; MERIS; time series analysis
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MDPI and ACS Style

Tum, M.; Günther, K.P.; Böttcher, M.; Baret, F.; Bittner, M.; Brockmann, C.; Weiss, M. Global Gap-Free MERIS LAI Time Series (2002–2012). Remote Sens. 2016, 8, 69.

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