@article{fdi:010081038,
  title = {{M}ean spectral reflectance from bare soil pixels along a {L}andsat-{TM} time series to increase both the prediction accuracy of soil clay content and mapping coverage},
  author = {{G}asmi, {A}. and {G}omez, {C}{\'e}cile and {L}agacherie, {P}. and {Z}ouari, {H}. and {L}aamrani, {A}. and {C}hehbouni, {A}bdelghani},
  editor = {},
  language = {{ENG}},
  abstract = {{V}isible, near-infrared and short wave infrared ({VNIR}/{SWIR}, 400-2500 nm) remote sensing imagery is a useful tool for topsoil property mapping, but limited to bare soils pixels. {W}ith the increasing amount of freely available {VNIR}/{SWIR} satellite imagery (e.g. {L}andsat {TM}, {ETM}+, {OLI} and {S}entinel-2{A}/{B}), extensive time series data can be exploited to increase the spatial coverage of bare soil derived information. {T}he objective of this study was to evaluate the benefits of using a bare soil image created from the mean spectral reflectance from bare soil pixels along a time series, compared to a single-date image. {T}he benefits were analyzed in term of (i) proportion of soil mapping and (ii) accuracy of clay content prediction. {T}he study was conducted over the {C}ap-{B}on region ({N}orthern {T}unisia) which is a pedologically contrasted and cultivated area. {T}o this end, 262 topsoil samples and three {L}andsat-{TM} images acquired during the summer season were used. {M}ultiple linear regression ({MLR}) models based on the multi-date and single-date {L}andsat-derived spectral dataset were performed to quantify clay soil content. {O}ur results have shown that (1) a bare soil image created from only mean spectral reflectance from common bare soil pixels along a time series provided the best accuracy of clay content prediction (i.e., coefficient of determination of validation ({R}-val(2)) of 0.75, a root mean square error of prediction ({RMSEP}) of 88 g/kg) with a moderate bare soil coverage (i.e., 23% of the study area); (2) a bare soil image created from a mix of mean spectral reflectance from common bare soil pixels along a time series and of spectral reflectance from bare soil pixels of single-date images provided acceptable accuracy of clay content prediction (i.e., {R}-val(2) = 0.64, {RMSEP} = 109 g/kg) with a relatively high bare soil coverage (i.e., 44% of the study area); and (3) all the bare soil images provided similar spatial structures of the clay content predictions. {W}ith the actual availability of the {VNIR}/{SWIR} satellite imagery for the entire globe, this study offer a simple and accurate method for delivering accurate soil property maps over large areas, to the geoscience community.},
  keywords = {{M}ulti-{D}ate imagery ; {L}andsat-{TM} ; {B}are soil coverage ; {S}oil day mapping ; {MLR} ; {P}rediction accuracy ; {TUNISIE} ; {CAP} {BON}},
  booktitle = {},
  journal = {{G}eoderma},
  volume = {388},
  numero = {},
  pages = {114864 [12 p.]},
  ISSN = {0016-7061},
  year = {2021},
  DOI = {10.1016/j.geoderma.2020.114864},
  URL = {https://www.documentation.ird.fr/hor/fdi:010081038},
}