@article{fdi:010064730,
  title = {{E}valuating the sensitivity of clay content prediction to atmospheric effects and degradation of image spatial resolution using {H}yperspectral {VNIR}/{SWIR} imagery},
  author = {{G}omez, {C}{\'e}cile and {O}ltra-{C}arrio, {R}. and {B}acha, {S}. and {L}agacherie, {P}. and {B}riottet, {X}.},
  editor = {},
  language = {{ENG}},
  abstract = {{V}isible, near-infrared and short wave infrared ({VNIR}/{SWIR}, 0.4-2.5 mu m) hyperspectral satellite imaging is one of the most promising tools for topsoil property mapping for the following reasons: i) it is derived from a laboratory technique that has been demonstrated to be a good alternative to costly physical and chemical laboratory soil analysis for estimating a large range of soil properties; ii) it can benefit from the increasing number of methodologies developed for {VNIR}/{SWIR} hyperspectral airborne imaging; and iii) it provides a synoptic view of the study area. {D}espite the significant potential of {VNIR}/{SWIR} hyperspectral airborne data for topsoil property mapping, the transposition to satellite data must be evaluated. {T}he objective of this study was to test the sensitivity of clay content prediction to atmospheric effects and to degradation of spatial resolution. {T}his study may offer an initial analysis of the potential of future hyperspectral satellite sensors, such as the {HYP}erspectral {X} {I}magery ({HYPXIM}), the {S}paceborne {H}yperspectral {A}pplicative {L}and and {O}cean {M}ission ({SHALOM}), the {PR}ecursore {I}per{S}pettrale della {M}issione {A}pplicativa ({PRISMA}), the {E}nvironmental {M}apping and {A}nalysis {P}rogram ({E}n{MAP}) and the {H}yperspectral {I}nfrared {I}mager ({H}ysp{IRI}), for soil applications. {T}his study employed {VNIR}/ {SWIR} {AISA}-{DUAL} airborne data acquired in a {M}editerranean region over a large area (300 km(2)) with an initial spatial resolution of 5 m. {T}hese hyperspectral airborne data were simulated at the top of the atmosphere and aggregated at six spatial resolutions (10, 15, 20, 30, 60 and 90 m) to correlate with the future hyperspectral satellite sensors. {T}he predicted clay content maps were obtained using the partial least squares regression ({PLSR}) method. {T}he large area of the studied region allows analysis of different pedological patterns of soil composition and spatial structures. {O}ur results showed the following: (i) when a correct compensation of atmosphere effects was performed, only slight differences were detected between clay maps retrieved from the airborne imagery and those from spaceborne imagery (both at 5 m of spatial resolution); (ii) the {PLSR} models, built from data with 5 to 30 m spatial resolutions, performed well, and allowed clay mapping, although variations in clay content related to short scale succession of parent material was imperfectly captured beyond 15 m of spatial resolution; (iii) the {PLSR} models built from data with 60 and 90 m spatial resolutions were inaccurate, and did not enable clay mapping; and (iv) the two latter results could be explained by the combination of a small short-scale clay content variability and small field sizes observed in the study area. {T}herefore, in the {M}editerranean and under the spectral specifications of the {AISA}-{DUAL} airborne sensor, most of the future hyperspectral satellite sensors (four of the five sensors examined in this study) will be potentially useful for clay content mapping.},
  keywords = {{VNIR}/{SWIR} spectroscopy ; {H}yperspectral satellite ; {A}irborne remote sensing ; {S}patial resolution ; {C}lay content mapping ; {PLSR} ; {M}editerranean context ; {TUNISIE}},
  booktitle = {},
  journal = {{R}emote {S}ensing of {E}nvironment},
  volume = {164},
  numero = {},
  pages = {1--15},
  ISSN = {0034-4257},
  year = {2015},
  DOI = {10.1016/j.rse.2015.02.019},
  URL = {https://www.documentation.ird.fr/hor/fdi:010064730},
}