@article{fdi:010081997,
  title = {{E}xtracting soil water holding capacity parameters of a distributed agro-hydrological model from high resolution optical satellite observations series},
  author = {{F}errant, {S}. and {B}ustillo, {V}. and {B}urel, {E}. and {S}almon-{M}onviola, {J}. and {C}laverie, {M}. and {J}arosz, {N}. and {Y}in, {T}. and {R}ivalland, {V}. and {D}edieu, {G}. and {D}emarez, {V}. and {C}eschia, {E}. and {P}robst, {A}. and {A}l-{B}itar, {A}. and {K}err, {Y}ann and {P}robst, {J}.{L}. and {D}urand, {P}. and {G}ascoin, {S}.},
  editor = {},
  language = {{ENG}},
  abstract = {{S}entinel-2 ({S}2) earth observation satellite mission, launched in 2015, is foreseen to promote within-field decisions in {P}recision {A}griculture ({PA}) for both: (1) optimizing crop production; and (2) regulating environmental impacts. {I}n this second scope, a set of {L}eaf {A}rea {I}ndex ({LAI}) derived from {S}2 type time-series (2006-2010, using {F}ormosat-2 satellite) is used to spatially constrain the within-field crop growth and the related nitrogen contamination of surface water simulated at a small experimental catchment scale with the distributed agro-hydrological model {T}opography {N}itrogen {T}ransfer and {T}ransformation ({TNT}2). {T}he {S}oil {W}ater {H}olding {C}apacity ({SWHC}), represented by two parameters, soil depth and retention porosity, is used to fit the yearly maximum of {LAI} ({LAX}) at each pixel of the satellite image. {P}ossible combinations of soil parameters, defining 154 realistic {SWHC} found on the study site are used to force spatially homogeneous {SWHC}. {LAX} simulated at the pixel level for the 154 {SWHC}, for each of the five years of the study period, are recorded and hereafter referred to as synthetic {LAX}. {O}ptimal {SWHC}year_{I},pixel_j, corresponding to minimal difference between observed and synthetic {LAX}(year_{I},pixel_j), is selected for each pixel, independent of the value at neighboring pixels. {E}ach re-estimated soil maps are used to re-simulate {LAX}(year_{I}). {R}esults show that simulated and synthetic {LAX}(year_{I},allpixels) obtained from {SWHC}year_{I},allpixels are close and accurately fit the observed {LAX}(year_{I},allpixels) ({RMSE} = 0.05 m(2)/m(2) to 0.2 and {R}-2 = 0.99 to 0.94), except for the year 2008 ({RMSE} = 0.8 m(2)/m(2) and {R}-2 = 0.8). {T}hese results show that optimal {SWHC} can be derived from remote sensing series for one year. {U}nique {SWHC} solutions for each pixel that limit the {LAX} error for the five years to less than 0.2 m(2)/m(2) are found for only 10% of the pixels. {S}election of unique soil parameters using multi-year {LAX} and neighborhood solution is expected to deliver more robust soil parameters solutions and need to be assessed further. {T}he use of optical remote sensing series is then a promising calibration step to represent crop growth within crop field at catchment level. {N}evertheless, this study discusses the model and data improvements that are needed to get realistic spatial representation of agro-hydrological processes simulated within catchments.},
  keywords = {{FRANCE}},
  booktitle = {{R}emote sensing in precision agriculture},
  journal = {{R}emote {S}ensing},
  volume = {154},
  numero = {{N}o special},
  pages = {154 [22 ]},
  ISSN = {2072-4292},
  year = {2016},
  DOI = {10.3390/rs8020154},
  URL = {https://www.documentation.ird.fr/hor/fdi:010081997},
}