@incollection{fdi:010081919,
  title = {{PLSR} method for contaminating mineral content prediction from field hyperspectral reflectance : a case study of {H}ammam {Z}riba mining area},
  author = {{D}khala, {B} and {M}ezned, {N}. and {G}omez, {C}{\'e}cile and {A}bdeljaouad, {S}.},
  editor = {},
  language = {{ENG}},
  abstract = {{M}ine tailings, left after the mine activities without any control, are charged of heavy metals and contaminating minerals, qualified as risks minerals. {I}n this study, we explore the potential of hyperspectral field spectroscopy in predicting the abundance of risk minerals in agricultural soils around the {H}ammam {Z}riba mine site in {N}orthern {T}unisia. {S}ixty-nine samples were gathered from the top surface of soils and dikes (tailing deposits) and measured using the {ASD} {F}ield {S}pec {H}i{R}es operated in {VNIR}/{SWIR} regions (350-2500 nm). {A}ll samples were analyzed by {X}-ray diffraction method {XRD} for the estimation of both several minerals, including {B}arite and {F}luorite contents. {T}he partial least squares regression ({PLSR}) was used to relate the measured {VNIR}/{SWIR} spectra to {XRD} analysis results for the prediction of risk mineral contents. {T}he prediction performances of {F}luorite and {B}arite contents were evaluated using particularly, the coefficient of determination {R}2 and the ratio of performance to deviation {RPD}. {R}esults have shown an accurate prediction of both risk minerals using {VNIR}/{SWIR} hyperspectral field spectroscopy.},
  keywords = {{TUNISIE}},
  booktitle = {2020 {IEEE} international geoscience and remote sensing symposium : proceedings},
  numero = {},
  pages = {1861--1864},
  address = {{N}ew {Y}ork},
  publisher = {{IEEE}},
  series = {},
  year = {2020},
  DOI = {10.1109/{IGARSS}39084.2020.9323983},
  ISBN = {978-1-7281-6374-1},
  URL = {https://www.documentation.ird.fr/hor/fdi:010081919},
}