Autor/a

Verger, Aleixandre

Filella, Iolanda

Baret, Frédéric

Peñuelas, Josep

Fecha de publicación

2016

Resumen

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.

Tipo de documento

Article

Lengua

Inglés

Materias y palabras clave

Climatology of land surface phenology; Mean annual seasonal cycle; Leaf area index; SPOT-VEGETATION; MODIS; Ground observations; Climatic drivers

Publicado por

 

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Remote sensing of environment ; Vol. 178, (June 2016), p. 1-14

Derechos

open access

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