@article{fdi:010061976,
  title = {{A}ssessing the {MODIS} crop detection algorithm for soybean crop area mapping and expansion in the {M}ato {G}rosso state, {B}razil},
  author = {{G}usso, {A}. and {A}rvor, {D}amien and {D}ucati, {J}. {R}. and {V}eronez, {M}. {R}. and da {S}ilveira, {L}. {G}.},
  editor = {},
  language = {{ENG}},
  abstract = {{E}stimations of crop area were made based on the temporal profiles of the {E}nhanced {V}egetation {I}ndex ({EVI}) obtained from moderate resolution imaging spectroradiometer ({MODIS}) images. {E}valuation of the ability of the {MODIS} crop detection algorithm({MCDA}) to estimate soybean crop areas was performed for fields in the {M}ato {G}rosso state, {B}razil. {U}sing the {MCDA} approach, soybean crop area estimations can be provided for {D}ecember (first forecast) using images from the sowing period and for {F}ebruary (second forecast) using images from the sowing period and the maximum crop development period. {T}he area estimates were compared to official agricultural statistics from the {B}razilian {I}nstitute of {G}eography and {S}tatistics ({IBGE}) and from the {N}ational {C}ompany of {F}ood {S}upply ({CONAB}) at different crop levels from 2000/2001 to 2010/2011. {A}t the municipality level, the estimates were highly correlated, with {R}-2 = 0.97 and {RMSD} = 13,142 ha. {T}he {MCDA} was validated using field campaign data from the 2006/2007 crop year. {T}he overall map accuracy was 88.25%, and the {K}appa {I}ndex of {A}greement was 0.765. {B}y using pre-defined parameters, {MCDA} is able to provide the evolution of annual soybean maps, forecast of soybean cropping areas, and the crop area expansion in the {M}ato {G}rosso state.},
  keywords = {{BRESIL}},
  booktitle = {},
  journal = {{S}cientific {W}orld {J}ournal},
  numero = {},
  pages = {art. 863141},
  ISSN = {1537-744{X}},
  year = {2014},
  DOI = {10.1155/2014/863141},
  URL = {https://www.documentation.ird.fr/hor/fdi:010061976},
}