@article{fdi:010080582,
  title = {{L}inkages between rainfed cereal production and agricultural drought through remote sensing indices and a land data assimilation system : a case study in {M}orocco},
  author = {{B}ouras, {E}. and {J}arlan, {L}ionel and {E}r-{R}aki, {S}. and {A}lbergel, {C}. and {R}ichard, {B}. and {B}alaghi, {R}. and {K}habba, {S}.},
  editor = {},
  language = {{ENG}},
  abstract = {{I}n {M}orocco, cereal production shows high interannual variability due to uncertain rainfall and recurrent drought periods. {C}onsidering the socioeconomic importance of cereal for the country, there is a serious need to characterize the impact of drought on cereal yields. {I}n this study, drought is assessed through (1) indices derived from remote sensing data (the vegetation condition index ({VCI}), temperature condition index ({TCI}), vegetation health ind ex ({VHI}), soil moisture condition index ({SMCI}) and soil water index for different soil layers ({SWI})) and (2) key land surface variables ({L}and {A}rea {I}ndex ({LAI}), soil moisture ({SM}) at different depths, soil evaporation and plant transpiration) from a {L}and {D}ata {A}ssimilation {S}ystem ({LDAS}) over 2000-2017. {A} lagged correlation analysis was conducted to assess the relationships between the drought indices and cereal yield at monthly time scales. {T}he {VCI} and {LAI} around the heading stage ({M}arch-{A}pril) are highly linked to yield for all provinces ({R} = 0.94 for the {K}hemisset province), while a high link for {TCI} occurs during the development stage in {J}anuary-{F}ebruary ({R} = 0.83 for the {B}eni {M}ellal province). {I}nterestingly, indices related to soil moisture in the superficial soil layer are correlated with yield earlier in the season around the emergence stage ({D}ecember). {T}he results demonstrate the clear added value of using an {LDAS} compared with using a remote sensing product alone, particularly concerning the soil moisture in the root-zone, considered a key variable for yield production, that is not directly observable from space. {T}he time scale of integration is also discussed. {B}y integrating the indices on the main phenological stages of wheat using a dynamic threshold approach instead of the monthly time scale, the correlation between indices and yield increased by up to 14%. {I}n addition, the contributions of {VCI} and {TCI} to {VHI} were optimized by using yield anomalies as proxies for drought. {T}his study opens perspectives for the development of drought early warning systems in {M}orocco and over {N}orth {A}frica, as well as for seasonal crop yield forecasting.},
  keywords = {agricultural drought ; cereal yield ; remote sensing ; land data ; assimilation systems ; semiarid region ; {MAROC} ; {ZONE} {SEMIARIDE} ; {ZONE} {MEDITERRANEENNE}},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {12},
  numero = {24},
  pages = {4018 [35 ]},
  year = {2020},
  DOI = {10.3390/rs12244018},
  URL = {https://www.documentation.ird.fr/hor/fdi:010080582},
}