%0 Journal Article
%9 ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES
%A Dkhala, B
%A Mezned, N.
%A Gomez, Cécile
%A Abdeljaouad, S.
%T PLSR method for contaminating mineral content prediction from field hyperspectral reflectance : a case study of Hammam Zriba mining area
%B 2020 IEEE international geoscience and remote sensing symposium : proceedings
%C New York
%D 2020
%L fdi:010081919
%G ENG
%I IEEE
%@ 978-1-7281-6374-1
%K TUNISIE
%M ISI:000664335301233
%P 1861-1864
%R 10.1109/IGARSS39084.2020.9323983
%U https://www.documentation.ird.fr/hor/fdi:010081919
%> https://www.documentation.ird.fr/intranet/publi/2022-02/010081919.pdf
%W Horizon (IRD)
%X Mine tailings, left after the mine activities without any control, are charged of heavy metals and contaminating minerals, qualified as risks minerals. In this study, we explore the potential of hyperspectral field spectroscopy in predicting the abundance of risk minerals in agricultural soils around the Hammam Zriba mine site in Northern Tunisia. Sixty-nine samples were gathered from the top surface of soils and dikes (tailing deposits) and measured using the ASD Field Spec HiRes operated in VNIR/SWIR regions (350-2500 nm). All samples were analyzed by X-ray diffraction method XRD for the estimation of both several minerals, including Barite and Fluorite contents. The 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. The prediction performances of Fluorite and Barite contents were evaluated using particularly, the coefficient of determination R2 and the ratio of performance to deviation RPD. Results have shown an accurate prediction of both risk minerals using VNIR/SWIR hyperspectral field spectroscopy.
%B IEEE International Geoscience and Remote Sensing Symposium
%8 2020/09/26-10/02
%$ 068