@article{fdi:010057263,
  title = {{P}redictability of vegetation cycles over the semi-arid region of {G}ourma ({M}ali) from forecasts of {AVHRR}-{NDVI} signals},
  author = {{M}angiarotti, {S}ylvain and {M}azzega, {P}. and {H}iernaux, {P}. and {M}ougin, {E}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he {NOAA}-{AVHRR} {N}ormalised {D}ifference {V}egetation {I}ndex ({NDVI}) dataset is used to investigate the predictability of the vegetation cycle in an area centred on the {G}ourma region in {S}ahelian {M}ali at scales varying from 8 km(2) to 1024 km(2) over a period spanning from 1982 to 2004. {T}he predictability of the vegetation cycle is analysed with a model based on a reconstruction approach that fully relies on the dataset. {T}wo parameters deduced from the growth of the forecast error are considered: the horizon of effective predictability, {H}-{E}, which is the horizon at which a satisfying prediction can be effectively forecasted at a given level of error, and the level of noise. {P}redictability is therefore analysed with regard to the horizon of prediction and the spatial scale; the influence of the model's dimensions is also discussed. {T}he analysis clearly indicates that the signal predictability increases, and the level of noise decreases with an expanding area. {H}owever, even though the signal is more regular, its complexity increases within the narrowing entangled trajectory, setting the level of error of any prediction at a minimum of 15%, which matches the level of noise characteristic of the {AVHRR}-{NDVI} data series. {T}he forecasting error quickly increases with the horizon of prediction, setting the optimum horizon of predictability in the range of 2 to 4 decades, with high intra-annual variability. {A}t the short horizon of 1 decade, a resolution of 16 km(2) is reasonable to achieve an accuracy of approximately 20%. {A}t the longer horizon of 3 decades, only low resolutions (256 km(2) or lower) give an accuracy equal to or better than 35%.},
  keywords = {{V}egetation cycle ; {S}emi-arid region ; {H}orizon of predictability ; {S}patial scale ; {NDVI} satellite data ; {N}onlinear prediction ; {MALI} ; {ZONE} {SEMIARIDE}},
  booktitle = {},
  journal = {{R}emote {S}ensing of {E}nvironment},
  volume = {123},
  numero = {},
  pages = {246--257},
  ISSN = {0034-4257},
  year = {2012},
  DOI = {10.1016/j.rse.2012.03.011},
  URL = {https://www.documentation.ird.fr/hor/fdi:010057263},
}