Web of Science: 105 cites, Scopus: 114 cites, Google Scholar: cites
Near real-time vegetation monitoring at global scale
Verger, Aleixandre (Centre de Recerca Ecològica i d'Aplicacions Forestals)
Baret, Frédéric (Institut National de la Recherche Agronomique (França))
Weiss, Marie (Institut National de la Recherche Agronomique (França))

Data: 2014
Resum: The NRT algorithm for near-real time estimation of global LAI, FAPAR, and FCOVER variables from SPOT/VEGETATION (VGT) satellite data is described here. It consists of three steps: 1) neural networks (NNT) (one for each variable) to provide instantaneous estimates from daily VGT-P reflectances; 2) a multistep filtering approach to eliminate data mainly affected by atmospheric effects and snow cover; and 3) Savitzky-Golay and climatology temporal smoothing and gap filling techniques to ensure consistency and continuity as well as short-term projection of the product dynamics. Performances of NRT estimates were evaluated by comparing with other products over the 2005-2008 period: 1) the offline estimates from the application of the algorithm over historical time series (HIST); 2) the geoland2 version 1 products also issued from VGT (GEOV1/VGT); and 3) ground data. NRT rapidly converges closely to the HIST processing after six dekads (10-day period) with major improvement after two dekads. Successive reprocessing will, therefore, correct for some instabilities observed in the presence of noisy and missing data. The root-mean-square error (RMSE) between NRT and HIST LAI is lower than 0. 4 in all cases. It shows a rapid exponential decay with the number of observations in the composition window with convergence when 30 observations are available. NRT products are in good agreement with ground data (RMSE of 0. 69 for LAI, 0. 09 for FAPAR, and 0. 14 for FCOVER) and consistent with GEOV1/VGT products with a significant improvement in terms of continuity (only 1% of missing data) and smoothness, especially at high latitudes, and Equatorial areas.
Drets: Tots els drets reservats.
Llengua: Anglès
Document: Article ; recerca ; Versió acceptada per publicar
Matèria: Biophysical variables ; Consistency ; Continuity ; Global scale ; Near real-time (NRT) ; SPOT/VEGETATION (VGT)
Publicat a: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 7, no. 8 (August 2014) , p. 3473-3481, ISSN 2151-1535

DOI: 10.1109/JSTARS.2014.2328632


Postprint
22 p, 863.2 KB

El registre apareix a les col·leccions:
Documents de recerca > Documents dels grups de recerca de la UAB > Centres i grups de recerca (producció científica) > Ciències > CREAF (Centre de Recerca Ecològica i d'Aplicacions Forestals)
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 Registre creat el 2024-03-07, darrera modificació el 2024-05-04



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