@article{fdi:010042570,
  title = {{A}ssimilation of {SPOT}/{VEGETATION} {NDVI} data into a sahelian vegetation dynamics model},
  author = {{J}arlan, {L}. and {M}angiarotti, {S}. and {M}ougin, {E}ric and {M}azzega, {P}. and {H}iernaux, {P}. and {L}e {D}antec, {V}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}his paper presents a method to monitor the dynamics of herbaceous vegetation in the {S}ahel. {T}he approach is based on the assimilation of {N}ormalized {D}ifference {V}egetation {I}ndex ({NDVI}) data acquired by the {VEGETATION} instrument on board {SPOT} 4/5 into a simple sahelian vegetation dynamics model. {T}he study region is located in the {G}ourma region of {M}ali. {T}he vegetation dynamics model is coupled with a radiative transfer model (the {SAIL} model). {F}irst, 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. {T}he data assimilation scheme relies on a parameter identification technique based on an {E}volution {S}trategies algorithm. {T}he 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. {T}he 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). {F}inally, 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.},
  keywords = {{NDVI} ; vegetation ; {S}ahel ; data assimilation ; evolution strategies},
  booktitle = {},
  journal = {{R}emote {S}ensing of {E}nvironment},
  volume = {112},
  numero = {4},
  pages = {1381--1394},
  ISSN = {0034-4257},
  year = {2008},
  DOI = {10.1016/j.rse.2007.02.041},
  URL = {https://www.documentation.ird.fr/hor/fdi:010042570},
}