Hyperspectral field spectroscopy and SENTINEL-2 Multispectral data for minerals with high pollution potential content estimation and mapping

Dkhala, B and Mezned, N and Gomez, C and Abdeljaouad, S (2020) Hyperspectral field spectroscopy and SENTINEL-2 Multispectral data for minerals with high pollution potential content estimation and mapping. In: Science of the Total Environment, 740 .

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Abstract

Mining in Tunisia generates a large amount of tailings charged with toxic minerals. As these tailings have a wide spread distribution, it is important to characterize and estimate their impact on soil contamination. This study examines the potential of field hyperspectral spectroscopy and SENTINEL-2 Multispectral data in estimating and mapping seven minerals content, including three toxic minerals (fluorite, barite and sphalerite), within soils around Hammam Zriba mine in Northen Tunisia. 69 soil and dike surface samples were collected, field Visible, Near InfraRed (VNIR) and Short-Wave InfraRed (SWIR) reflectance spectra were measured on these surfaces. The X-ray diffraction (XRD) method was used to identify the types of mineral and their associated contents on each collected soil samples. The mineral contents were predicted using the partial least squares regression (PLSR) method using i) field VNIR-SWIR spectra at raw spectral resolution, ii) field VNIR-SWIR spectra aggregated to the SENTINEL-2 spectral resolution and then iii) SENTINEL-2 spectra. This study shows 1) an accurate prediction of four of the seven minerals using field VNIR-SWIR spectroscopy, 2) a slight decrease of performances due to spectral resolution degradation (SENTINEL-2 simulated spectra) and 3) a significant decrease of performances due to spatial resolution degradation, except for fluorite. This work paves the way for large-scale mapping of minerals with high pollution potential using SENTINEL-2 data. In addition, the high frequency of SENTINEL-2 data may be used to monitor the spatial distribution of some minerals with high pollution potential in soils. © 2020 Elsevier B.V.

Item Type:	Journal Article
Publication:	Science of the Total Environment
Publisher:	Elsevier B.V.
Additional Information:	Copy right for this article belongs to Elsevier B.V.
Keywords:	Fluorspar; Hydraulic structures; Infrared devices; Infrared radiation; Least squares approximations; Mapping; Minerals; Photodegradation; Soil pollution; Soils; Spectral resolution; Zinc sulfide, Accurate prediction; Multi-spectral data; Partial least squares regressions (PLSR); Reflectance spectrum; Short wave infrared; Soil contamination; Spatial resolution; Spectral resolution degradation, Soil surveys, barium sulfate; fluorite; mineral; unclassified drug; zinc sulfide, data set; estimation method; mapping method; mineral deposit; Sentinel; soil pollution; spectral analysis; tailings, Article; biodegradation; concentration (parameter); hyperspectral imaging; laboratory test; measurement accuracy; mine tailings; mineralogy; multispectral imaging; near infrared reflectance spectroscopy; prediction; priority journal; soil analysis; soil pollution; soil property; Tunisia; X ray diffraction, Tunisia
Department/Centre:	Division of Interdisciplinary Sciences > Interdisciplinary Centre for Water Research
Date Deposited:	13 Mar 2021 05:33
Last Modified:	13 Mar 2021 05:33
URI:	http://eprints.iisc.ac.in/id/eprint/65913

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