@article{fdi:010070438,
  title = {{A} quantile mapping bias correction method based on hydroclimatic classification of the {G}uiana shield},
  author = {{R}ingard, {J}ustine and {S}eyler, {F}r{\'e}d{\'e}rique and {L}inguet, {L}.},
  editor = {},
  language = {{ENG}},
  abstract = {{S}atellite precipitation products ({SPP}s) provide alternative precipitation data for regions with sparse rain gauge measurements. {H}owever, {SPP}s are subject to different types of error that need correction. {M}ost {SPP} bias correction methods use the statistical properties of the rain gauge data to adjust the corresponding {SPP} data. {T}he statistical adjustment does not make it possible to correct the pixels of {SPP} data for which there is no rain gauge data. {T}he solution proposed in this article is to correct the daily {SPP} data for the {G}uiana {S}hield using a novel two set approach, without taking into account the daily gauge data of the pixel to be corrected, but the daily gauge data from surrounding pixels. {I}n this case, a spatial analysis must be involved. {T}he first step defines hydroclimatic areas using a spatial classification that considers precipitation data with the same temporal distributions. {T}he second step uses the {Q}uantile {M}apping bias correction method to correct the daily {SPP} data contained within each hydroclimatic area. {W}e validate the results by comparing the corrected {SPP} data and daily rain gauge measurements using relative {RMSE} and relative bias statistical errors. {T}he results show that analysis scale variation reduces r{BIAS} and r{RMSE} significantly. {T}he spatial classification avoids mixing rainfall data with different temporal characteristics in each hydroclimatic area, and the defined bias correction parameters are more realistic and appropriate. {T}his study demonstrates that hydroclimatic classification is relevant for implementing bias correction methods at the local scale.},
  keywords = {{HYDROCLIMAT} ; {PRECIPITATION} ; {ZONE} {COTIERE} ; {TELEDETECTION} {SPATIALE} ; {DONNEES} {SATELLITE} ; {DISTRIBUTION} {STATISTIQUE} ; {MODELISATION} ; {DEBIT} ; {TRAITEMENT} {D}'{IMAGE} ; {METHODOLOGIE} ; {CHANGEMENT} {CLIMATIQUE} ; {CORRECTION} {DE} {DONNEES} ; {GUYANE} {FRANCAISE} ; {AMAZONIE} ; {BRESIL} ; {COLOMBIE} ; {GUYANA} ; {SURINAME} ; {VENEZUELA}},
  booktitle = {},
  journal = {{S}ensors},
  volume = {17},
  numero = {6},
  pages = {art. no 1413 [17  en ligne]},
  ISSN = {1424-8220},
  year = {2017},
  DOI = {10.3390/s17061413},
  URL = {https://www.documentation.ird.fr/hor/fdi:010070438},
}