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Assimilation of SPOT-Vegetation NDVI data into a Sahelian vegetation dynamics model / Lionel Jarlan in Remote sensing of environment, vol 112 n° 4 (15/04/2008)  

Public [article]  inRemote sensing of environment > vol 112 n° 4 (15/04/2008) . - pp 1381 - 1394 Titre : Assimilation of SPOT-Vegetation NDVI data into a Sahelian vegetation dynamics model Type de document : Article/Communication Auteurs : Lionel Jarlan, Auteur ; S. Mangiarotti, Auteur ; et al., Auteur Année de publication : 2008 Article en page(s) : pp 1381 - 1394 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] flore locale [Termes IGN] image SPOT-Végétation [Termes IGN] intégration de données [Termes IGN] modèle dynamique [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] Sahel Résumé : (Auteur) This paper presents a method to monitor the dynamics of herbaceous vegetation in the Sahel. The approach is based on the assimilation of Normalized Difference Vegetation Index (NDVI) data acquired by the VEGETATION instrument on board SPOT 4/5 into a simple sahelian vegetation dynamics model. The study region is located in the Gourma region of Mali. The vegetation dynamics model is coupled with a radiative transfer model (the SAIL model). First, it is checked that the coupled models allow for a realistic simulation of the seasonal and interannual variability of NDVI over three sampling sites from 1999 to 2004. The data assimilation scheme relies on a parameter identification technique based on an Evolution Strategies algorithm. The simulated above-ground herbage mass resulting from NDVI assimilation is then compared to ground measurements performed over 13 study sites during the period 1999–2004. The assimilation scheme performs well with 404 kg DM/ha of average error (n = 126 points) and a correlation coefficient of r = 0.80 (to be compared to the 463 kg DM/ha and r = 0.60 of the model performance without data assimilation). Finally, the sensitivity of the herbage mass model estimates to the quality of the meteorological forcing (rainfall and net radiation) is analyzed thanks to a stochastic approach. Copyright Elsevier Numéro de notice : A2008-093 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2007.02.041 En ligne : https://doi.org/10.1016/j.rse.2007.02.041 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29088 [article]