@article{fdi:010079975,
  title = {{R}etrospective analysis and version improvement of the satellite-based drought composite index : a semi-arid {T}ensift-{M}orocco application},
  author = {{H}oumma, {I}. {H}. and {E}l {M}ansouri, {L}. and {H}adria, {R}. and {E}mran, {A}. and {C}hehbouni, {A}bdelghani},
  editor = {},
  language = {{ENG}},
  abstract = {{T}his paper aims to offer an improved version of the new composite drought monitoring index ({CDMI}) and to test its applicability in the context of {T}ensift watershed in {M}orocco. {A} synergistic approach incorporating the remote sensing techniques, hydrometeorological data, simulated data and agricultural statistics was used for this purpose. {A}fter assessing the performance of {CDMI}, estimated {S}oil {M}oisture {A}nomaly {I}ndicator ({ISMA}) was processed, validated and incorporated to the composite model. {R}andom {F}orest algorithm was used to determine the weight of composite model components. {A}part from comparative mapping, {P}earson's correlation statistical analysis, linear regression and dependency tests were used to assess the performance of the improved composite model ({CDMI}a_{RF}). {T}he result show that {CDMI}a_{RF} is better correlated with several indices such as: the {S}tandardized {P}recipitation {I}ndex ({SPI}), ({R}-2=0.74); {H}ydrological {D}rought {I}ndex ({R}-2=0.70); grain productivity ({R}-2=0.70), {CDMI} ({R}-2=0.95), {V}egetation {H}ealth {I}ndex ({VHI}), ({R}-2=0.87), and {N}ormalized {V}egetation {S}upply {W}ater {I}ndex ({NVSWI}), ({R}-2= 0.85).},
  keywords = {drought index ; {R}andom {F}orest ; {CDMI}a_{RF} ; {ISMA} ; {CDMI} ; {SPI}-{VHI} ; {S}emi-arid ; {MAROC} ; {ZONE} {SEMIARIDE} ; {TENSIFT} {BASSIN}},
  booktitle = {},
  journal = {{G}eocarto {I}nternational},
  volume = {37},
  numero = {11},
  pages = {3069--3090},
  ISSN = {1010-6049},
  year = {2022},
  DOI = {10.1080/10106049.2020.1844314},
  URL = {https://www.documentation.ird.fr/hor/fdi:010079975},
}