Land surface phenology derived from remotely sensed satellite data can substantially improve our macroecological knowledge and the representation of phenology in earth system models. We characterized the baseline phenology of the vegetation at the global scale from the GEOCLIM climatology of leaf area index (LAI) estimated from 1-km SPOT-VEGETATION time series for 1999-2010. The phenological metrics were calibrated over an ensemble of ground observations of the timing of leaf unfolding and autumnal colouring of leaves. The start and end of season were best identified using respectively 30% and 40% threshold of LAI amplitude values. The accuracy of the derived phenological metrics, evaluated using available ground observations for birch forests over Europe (and lilac shrubs over North America), improved as compared to those derived from MODIS-EVI and produced an overall root mean square error of 7 days (19 days) for the timing of the start of season, 15 for the end of season, and 16 for the length of season. The spatial patterns of the derived LAI phenology agreed well with those from MODIS-EVI and -NDVI, although the timing of the start, end, and length of season differed by about one month at the global scale, with higher uncertainties in areas of limited seasonality of the satellite signal and systematic biases due to the differences in the methodologies and datasets. The baseline LAI phenology was spatially consistent with the global distributions of climatic drivers and biome land cover.
English
Climatology of land surface phenology; Mean annual seasonal cycle; Leaf area index; SPOT-VEGETATION; MODIS; Ground observations; Climatic drivers
European Commission 218795
European Commission 32-566
European Commission 32-594
Ministerio de Economía y Competitividad CGL2013-48074-P
Agència de Gestió d'Ajuts Universitaris i de Recerca 2014/SGR-274
European Commission 610028
Remote sensing of environment ; Vol. 178, (June 2016), p. 1-14
open access
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