Mineralogical mapping using Landsat-8 OLI, Terra ASTER and Sentinel-2A multispectral data in Sidi Flah-Bouskour inlier, Moroccan Anti-Atlas

Adiri, Zakaria; Harti, Abderrazak El; Jellouli, Amine; Maacha, Lhou; Azmi, Mohamed; Zouhair, Mohamed; Bachaoui, El Mostafa

doi:10.1080/14498596.2018.1490213

Cited by 19 publications

(7 citation statements)

References 46 publications

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“…Sericite alteration generates phyllosilicate minerals, particularly muscovite and illite, which define the phyllic alteration area [ 46 ], and are characterized by an absorption of Al–OH at 2.20 μm. The muscovite, illite, and Kaolinite also define the argillitic alteration [ 33 ], where the Kaolinite showed a high absorption at 0.9 μm. The propylitic alteration zone is primarily composed of chlorite and carbonates (particularly calcite, dolomite, and epidote).…”

Section: Methodology and Materialsmentioning

confidence: 99%

“…Adiri (2020) evaluated the capability of Landsat-8 OLI, Sentinel-2A and ASTER data in mineralogical mapping in Sidi Flah-Bouskour inlier, Moroccan Anti-Atlas. The BR, ICA, and mixture tuned matched filtering (MTMF) techniques were used in this study, as well as field investigation for validation of the results [ 33 ]. Ouhoussa (2022) utilized Landsat-8 OLI to examine the spectral characteristics of the lithological units in the Oumjrane-Boukerzia Mining District, eastern Anti-Atlas, then identify the alteration areas that might hold significant base metal deposits.…”

Section: Introductionmentioning

confidence: 99%

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Lithological discrimination and mineralogical mapping using Landsat-8 OLI and ASTER remote sensing data: Igoudrane region, jbel saghro, Anti Atlas, Morocco

Baid,

Tabit,

Algouti

et al. 2023

Heliyon

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Section: Methodology and Materialsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Lithological discrimination and mineralogical mapping using Landsat-8 OLI and ASTER remote sensing data: Igoudrane region, jbel saghro, Anti Atlas, Morocco

Baid,

Tabit,

Algouti

et al. 2023

Heliyon

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“…Some types of alteration can be better distinguished by remote sensing than in the field, as most minerals have absorption characteristics at wavelengths outside the spectrum visible to the human eye. For this reason, we have opted to calculate band ratios (Kalinowski and Oliver, 2004;Gozzard, 2006;Van der Meer et al, 2014) on Aster, Landsat OLI, and Sentinel 2 bands (Tables 7 and 8), which is a very useful technique to detect areas with spectral anomalies of minerals or mineral groups associated with the presence of hydrothermal or supergene alteration in the study area (Van der Werff & Van der Meer, 2016;El Atillah et al, 2018;Adiri et al, 2020).…”

Section: Mineralogical Mappingmentioning

confidence: 99%

Cartografía estructural y mineral mediante imagen multiespectral en el Alto Atlas Central de Marruecos

2023

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El Alto Atlas Central es una de las estructuras geológicas que pertenecen al Macizo del Atlas marroquí. Presenta una gran diversidad geológica y muchas características estructurales y de facies. Está controlada por fallas principales de dirección N70 a E-O, visibles a diferentes escalas y ricas en numerosas vetas mineralizadas. Esta zona ha sido objeto del presente trabajo, en el que hemos simulado las imágenes de los sensores Landsat 8 OLI, Sentinel 2 y Aster para cartografiar los minerales de alteración hidrotermal asociados a una cartografía litoestructural que puede aportar más información sobre la mineralización de esta zona de estudio. En este punto destacamos los diferentes enfoques de teledetección adoptados, citando en primer lugar los métodos de extracción de lineamientos a partir de la banda infrarroja de la imagen Landsat 8 OLI y del GDEM ASTER para destacar la fracción geológica del área de estudio. Para obtener una buena discriminación de las unidades litológicas se realizó un Análisis de Componentes Principales y se aplicó el Factor de Índice Óptimo para crear composiciones de color con mejor interpretación visual para tener una buena cartografía litológica, y finalmente, se proponen muchas relaciones de bandas para ASTER, Landsat 8 OLI y Sentinel 2 para derivar varios mapas correspondientes a las zonas de alteración hidrotermal que se comparan con el mapa geológico del lugar estudiado, que presenta una correlación favorable entre ellos. El análisis de los resultados de los mapas obtenidos permitió identificar las grandes direcciones estructurales materializadas por las familias NE-SW a E-W, NNE-SWSW y ENE-WSW y también permitió destacar dos zonas potenciales de mineralización: una situada al sur de Demnate en el extremo occidental del Alto Atlas Central y la otra en la parte central del Alto Atlas Central. La superposición de los mapas de alteración y del mapa de fracturación muestra que las zonas que pueden ser favorables para los depósitos de mineralización están afectadas por fallas en dirección generalmente NE-SW.

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“…ICA in its wording is close to PCA, but unlike it, it is aimed at finding a set of independent rather than orthogonal components. It also uses higher-order statistics and can distinguish objects of interest even if they occupy only a small part of the image pixels [57,58].…”

Section: Minimum Noise Fractionmentioning

confidence: 99%

Geological and Mineralogical Mapping Based on Statistical Methods of Remote Sensing Data Processing of Landsat-8: A Case Study in the Southeastern Transbaikalia, Russia

et al. 2022

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The work considers the suitability of using multispectral satellite remote sensing data Landsat-8 for conducting regional geological and mineralogical mapping of the territory of south-eastern Transbaikalia (Russia) based on statistical methods for processing remote sensing data in conditions of medium–low-mountain relief and continental climate. The territory was chosen as the object of study due to its diverse metallogenic specialization (Au, U, Mo, Pb-Zn, Sn, W, Ta, Nb, Li, fluorite). Diversity in composition and age of ore-bearing massifs of intrusive, volcanogenic, and sedimentary rocks are also of interest. The work describes the initial data and considers the procedure for their pre-processing, including radiometric and atmospheric correction. Statistical processing algorithms to increase spectral information content of satellite data Landsat-8 were used. They include: principal component analysis, minimum noise fraction, and independent component analysis. Eigenvector matrices analyzed on the basis of statistical processing results and two-dimensional correlation graphs were built to compare thematic layers with geological material classes: oxide/hydroxide group minerals containing transition iron ions (Fe3+ and Fe3+/Fe2+); a group of clay minerals containing A1-OH and Fe, Mg-OH; and minerals containing Fe2+ and vegetation cover. Pseudo-colored RGB composites representing the distribution and multiplication of geological material classes are generated and interpreted according to the results of statistical methods. Integration of informative thematic layers using a fuzzy logic model was carried out to construct a prediction scheme for detecting hydrothermal mineralization. The received schema was compared with geological information, and positive conclusions about territory suitability for further remote mapping research of hydrothermally altered zones and hypergenesis products in order to localize areas promising for identifying hydrothermal metasomatic mineralization were made.

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Mineralogical mapping using Landsat-8 OLI, Terra ASTER and Sentinel-2A multispectral data in Sidi Flah-Bouskour inlier, Moroccan Anti-Atlas

Cited by 19 publications

References 46 publications

Lithological discrimination and mineralogical mapping using Landsat-8 OLI and ASTER remote sensing data: Igoudrane region, jbel saghro, Anti Atlas, Morocco

Lithological discrimination and mineralogical mapping using Landsat-8 OLI and ASTER remote sensing data: Igoudrane region, jbel saghro, Anti Atlas, Morocco

Cartografía estructural y mineral mediante imagen multiespectral en el Alto Atlas Central de Marruecos

Geological and Mineralogical Mapping Based on Statistical Methods of Remote Sensing Data Processing of Landsat-8: A Case Study in the Southeastern Transbaikalia, Russia

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