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Prospecting Tungsten (Scheelite) Mineralization in the Djouzami Area (Adamawa Cameroon) Using Ultra-Violet (UV) Fluorescence and Landsat-8 OLI Images

Received: 17 May 2024     Accepted: 11 June 2024     Published: 27 June 2024
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Abstract

Remote sensing technology and X-rays fluorescence are largely used in the applied geology field. In this study, we combine field observations and petrography, remote sensing applications through the processing of the Landsat-8 OLI, and Ultra-violet fluorescence to map geological structures, hydrothermal alteration minerals, and characterize tungsten mineralization in the Djouzami area (Adamawa, Cameroon). Landsat-8 OLI satellite imagery, was processed to detect both hydrothermal alteration zones and regional structural lineaments associated with tungsten mineralization. Fieldworks and petrography revealed hydrothermal mineral assemblage made of muscovite, chlorite, tourmaline, hematite, calcite and sericite associated to metallic minerals including tungsten and pyrite hosted in quartz veins. This hydrothermal mineral assemblage is also identified in the gold-bearing quartz veins reported in several areas along the Lom group. Band Ratio (BR) and Principal component analysis (PCA) were implemented to extract spectral information related to alteration minerals. The Band Ratios 6/7, 4/2, and 6/5 have permits to map clay, iron oxide/hydroxides, and ferrous minerals, respectively. This study demonstrates the significant potential of fieldwork and multispectral remote sensing data processing for tungsten prospecting as a mineral exploration technique in the Djouzami region. The mapping led to the detection of 1334 lineaments which show four main directions. The ENE-WSW directions corresponds to the trending of the Sanaga shear zone; the NE-SW direction represents the trending of the Djouzami and the Bétaré-Oya shear zones or the main shear zone which underline the Lom group; the N-S and E-W directions are equivalent to the trending of the foliation in the Meiganga area. Most of the high hydrothermal zones and tungsten-bearing quartz veins are located along the NE-SW lineaments or shear zone. Gold-related NE-SW trending Djouzami shear zone is also proposed. The NE-SW structure constitute certainly pathway for mineralizing fluids and ground water circulation, and control tungsten mineralization. Results proposed in this work provide important information for research of characteristic hydrothermal minerals assemblage that accompany tungsten mineralization, and for identify structures that control this mineralization in the area.

Published in Earth Sciences (Volume 13, Issue 3)
DOI 10.11648/j.earth.20241303.12
Page(s) 97-115
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Tungsten, Scheelite, Hydrothermal Alteration, Shear Zone, Ultra-Violet (UV) Fluorescence, Landsat-8 OLIReferences

1. Introduction
Tungsten is a rare metals or strategic metals, scarce in the nature (1.25 ppm in the terrestrial crust). It is mainly present in the form of wolframite (FeMnWO4), but also as scheelite. (CaWO4). Several types of tungsten deposits are distinguished among which skarns, breccia pipes, rare-metal granites, disseminated greisen-type deposits and vein-type deposits . Tungsten mineralization can be of magmatic and/or hydrothermal origin . Hydrothermal deposits are frequently associated with primary gold mineralization and have a hydrothermal paragenesis consisting of carbonates, epidote, tourmaline and muscovite . Scheelite ore, composed of calcium and tungsten, under UV lighting (254 nanometers). When ores and crystals are exposed to different light sources (white light, infrared, ultraviolet, laser, etc.), the matter of which they are composed interacts with the light. A residual coloration, or luminescence, is then observed. These phenomena make it possible to gather information about the structure of mineral materials, their composition, and their physico-chemical properties without damaging them. Physical color phenomena result from the diffraction of light on materials, while photoluminescence phenomena result from the emission of light by these materials. Scheelite can be recognized petrographically under a short-wave UV lamp, fluorescing pale blue .
Mineral exploration includes a succession of stages that make it possible to focus on one or more mining targets, starting from one or more favorable mineral occurrences to move towards concentrations high enough and technically exploitable to allow the opening of a mine . Several methods are used for the mineral exploration including remote sensing, coupled with geology, geophysics, geochemistry and reserve estimation methods. Remote sensing has been largely used these last years for mapping lithological units and geological structures, identify hydrothermal alteration zones; and mineral exploration . The principle consists to use the spectral signatures of minerals and mineral assemblages formed by hydrothermal alteration to identify outflows of hydrothermal systems, which can support the recognition of mineralized zones . Remote sensing technique in mainly employed because it provide a cost-effective approach resulting from his ability to access difficult terrains and landforms (such as some mountains and forest terrains), and data collection can be done rapidly at frequent intervals on a large scale. Hydrothermally altered rocks are frequently indicated by iron oxide, clay, carbonate, and sulfate minerals, which produce diagnostic absorption signatures throughout the visible and near infrared (VNIR) and shortwave infrared (SWIR) regions . Therefore, image processing methods transform multispectral satellite data into images that enhance geological features in contrast to the background .
The eastern part of Cameroon in endowed with rare-metal mineralization occurrences, including tungsten but, few studies have been made for the characterization and mapping of this mineralization using remote sensing. During field works in the Djouzami area located along the Lom group, tungsten mineralization associated to quartz veins have been identified. This group is well known for its significant mining potential and in importance of gold mining exploration .
The goal of this study is to characterize tungsten mineralization and associated hydrothermal minerals assemblage, and define the structure which control this mineralization. This will be done through Ultra-violet (UV) fluorescence analysis of mineralized samples, and Landsat-8 OLI images by study multispectral imagery. The results may provide a tool for mineral exploration in Adamawa Cameroon.
2. Geological Setting and Mineralization
The Djouzami area is located along the Lom group and belongs to the Adamawa-Yadé domain of the Central African Orogenic Belt (Figure 1A) in Cameroon. The Adamawa-Yadé or Central Cameroon domain (Figure 1B) extends from the north of Bafia group, to the Tcholliré-Banyo shear zone (TBSZ) . This domain is made of (a) Archaean to Palaeoproterozoic metamorphic rocks (amphibolite, paragneiss, orthogneiss and migmatite) . Recently, U-Pb ages on detrital zircon in paragneisses point out the contribution of Archaean, Palaeoproterozoic, and Neoproterozoic sources and suggest a maximum deposition age of 725 ± 12 Ma . Metamorphic rocks of this domain were transformed under high-grade metamorphic conditions (1.3 GPa–770°C) dated between 600 and 582 Ma (U-Pb on zircon data .; (b) Neoproterozoic metavolcano-sedimentary rocks belonging to the Lom group, recrystallized under low- to medium grade metamorphic conditions during the Panafrican orogeny . In addition, some Mbé–Sassa-Berci amphibolite having preserved magmatic zircon grains yielding Neoproterozoic ages of 600 ± 4 and 599 ± 6 Ma (U/Pb on zircon; ); (c) syn- to late-orogenic weakly deformed granites emplaced between 600 and 575 Ma , showing calc-alkaline to shoshonitic affinity, and considered to be of crustal melt or having mixed origin . These granitoids displays in place enclaves or xenolith of host rocks (gneiss, migmatite, amphibolite, schists) and are crosscut by aplite, microgranite, pegmatite and quartz veins . The abundance of inherited zircon and monazite grains with Archaean to Palaeoproterozoic U-Pb ages in the metasediments and granites of the Adamawa-yadé domain suggests that it is mostly composed of rocks issued from an Archaean to Palaeoproterozoic crust reworked during the Panafrican orogeny ; According to , the Central Cameroon domain represents an Achaean/Palaeoproterozoic crust, detached from the Congo craton during the early Neoproterozoic and re-accreted with the Mayo Kebbi domain during the Panafrican orogeny. Granite-gneiss rocks of this domain are covered in place by the cretaceous sediments (e.g., the Koum and Mbéré basins) and by the Cenozoic volcanic rocks of the Cameroon hot line (Figure 1B) . The Adamawa-Yadé domain is also characterized by the development of a regional-scale mega-fractures or transcurrent shear zone among which the ENE–WSW-trending Sanaga shear zone (SSZ) and Central Cameroon shear zone (CCSZ) also called the Adamawa fault which extends toward the Gulf of Aden . The Central Cameroon shear zone is interpreted as the NW extension of the Pernambuco Fault in NE Brazil . The CCSZ marks the transition between a subdomain with an N–Strending foliation to the north and a subdomain with an E–W-trending foliation to the south . Along the CCSZ shear zone and his Sanaga shear zone relay, kinematic analysis shows an earlier D2 sinistral transpression followed by a D3 dextral transtension during the Panafrican Orogeny .
Figure 1. (A) Geology of West-central Africa and northern Brazil in a Gondwana (pre-drift) reconstruction (modified from . Thick line, boundary of the two continents: (1) Phanerozoic cover; (2) Neoproterozoic formations; (3) Regions of Brasiliano/Panafrican deformation in which Palaeoproterozoic basement is absent or only present as small isolated blocks; (4) Regions of Brasiliano/Panafrican deformation with large amounts of reworked Palaeoproterozoic basement; (5) cratons. (B) Geological map of Cameroon (after . The Lom group is represented by a yellow rectangle. KCF (Kribi-Campo fault); SSZ (Sanaga shear zone); CCSZ (Central Cameroon shear zone); TBSZ (Tcholliré-Banyo shear zone); MNSZ (Mayo Nolti shear zone) and GGSZ (Godé-Gormaya shear zone). (1) volcanic rokcs (Tertiary to recent); (2) Post-Panafrican sedimentary cover; (3) Syn- to Post-tectonic granitoids (500-600Ma); (4) Pre- to syn-tectonic orthogneisses (600-660Ma); (5) Meso- to Neoproterozoic volcano-sedimentary belt (700-1000Ma; (6) Yokadouma and Dja series (age unknown); (7) Palaeoproterozoic gneiss and orthogneiss (2100Ma) and (8) Ntem Complex (3000Ma). (C) Structural map of the Lom Group . Monocyclic units associated to grabens: (a) orthogneiss; (b) Lom volcaniclastic series; (c) polygenic conglomerates; (d) Mari quartzites. Polycyclic units: (e) staurolite micaschists; (f) Lom bridge gneisses; (g) staurolite and chloritoid ductile mylonites. Intrusions with uncertain structural position: (h) granites (G2); (i) granites and monzonites; (j) metalamprophyres (modified after ). Inset: location of the Lom Group as an extensional relay zone between two en- echelon segments of the Sanaga fault; the opening of this basin corresponds to sinistral shear movement along these major faults. The study area is indicated in Figure 1C by the red rectangle.
The Lom group (Figure 1C) consists of metatuffs, volcaniclastic and sedimentary-derived schists, staurolite–garnet micaschists, and quartzites with local conglomerate layers . This group is interpreted as a post-collisional and intra-continental basin developed on the old crust, with depositional age constrained between 613 and 600 Ma . The same works suggest that detrital sources include Archaean to Palaeoproterozoic, late Mesoproterozoic to early Neoproterozoic (1100–950 Ma), and Neoproterozoic (735, 644 and 613 Ma) zircons. The Lom group is characterized by polyphase tectonic evolution with two successive D1 and D2 deformations leading to a N50–N70 steeply dipping regional foliation that does not contain any apparent stretching lineation. Dextral or sinistral faults, locally parallel to the main foliation, characterize the later stages of the structural evolution. The associated low-pressure regional metamorphism (garnet–staurolite– andalusite–sillimanite) involved a high thermal gradient related to widespread crustal melting that produced the dominant S-type granitoids in the region . The Group is characterized by gold-bearing quartz veins underlining a NE-SW to NNE-SSW-trending shear zone developed during brittle-to-ductile deformation, associated to K‐feldspar alteration and hydrothermal wall‐rock alteration comprising silicification, sericitization, sulphidation, hematitization, and carbonatization .
3. Methodology
3.1. Ultra-Violet (UV). Fluorescence
The ultra-violet lamp is the high-power U.V lamps in the Blak-Ray B-100 Series which provide bright irradiance for optimal fluorescence. The B-100AP lamp (presented) is placed at the base of the transformer for free-handed operation. The UV method is a method that is used only in the dark environment. As part of our work, we entered the laboratory at night in order to be able to perform our tests in a dark chamber. To make the device work, you must first connect the device to a sector outlet and wait for the lamp to start. Once running, after 60 seconds, we have a purple light that is emitted from the lamp. All that remains is to place the sample to be analyzed under this emitted light and observe. Using a camera, so the flash was disabled, we filmed the samples under the effect of UV. Note that the camera emits ultraviolet radiation for about 3 minutes, then turns off before turning on after 2 minutes in order not to overheat the lamp. You should not expose yourself to this radiation for long because it has harmful effects on the skin and is even a source of cancer.
3.2. Landsat-8 OLI Image Characteristics
The Landsat-8 OLI scene LC08_L1TP_184056_20230212_20230218_02_T1 taken on February 23, 2023, was downloaded free of charge from the United States Geological Survey (USGS) image database at http://earthexplorer.usgs.gov/. The Landsat-8 OLI system, designed by Ball Aerospace Technology, operates from a conventional height of 705 km with an equatorial crossing time of 10 h00 ± 15 min. It circles the earth every 16 days (except for the highest polar latitude) and has a scene size of 170 km × 185 km. In general, this system detects geographic information in spectral wavelengths ranging from 0.483 to 2.330 µm, covering the visible to infrared regions. The Landsat-8 OLI image is divided into 11 bands, which include visible (bands 1, 2, and 3), red (band 4), near infrared (band 5), shortwave infrared (bands 6 and 7), panchromatic (band 8), circus (band 9), and thermal (bands 10 and 11). Information capture from the Landsat 8 OLI system is generally at a spatial resolution of 30 m, with the exception of the panchromatic band, which obtains information at 15 m, and the thermal bands, which operate at a spatial resolution of 100 m. Table 1 illustrates the band characteristics of the Landsat OLI system.
Table 1. Landsat-8 OLI image characteristics.

Resolution of Landsat-8 OLI / TIRS

Band

Characteristics

Spatial resolution

Spectral resolution (μm)

Band 1

Aerosol

30 m × 30 m

0.433 – 0.453

Band 2

Blue

30 m × 30 m

0.45 – 0.515

Band 3

Green

30 m × 30 m

0.525 – 0.6

Band 4

Red

30 m × 30 m

0.63 – 0.68

Band 5

Near Infrared

30 m × 30 m

0.845 – 0.885

Band 6

Mid Infrared 1

30 m × 30 m

1.36 – 1.39

Band 7

Mid Infrared 2

30 m × 30 m

1.56 – 1.66

Band 8

Panchromatic

15 m × 15 m

0.50 – 0.68

Band 9

Cirrus

30 m × 30 m

2.10 – 2.30

Band 10

Thermal Infrared 1

100 m × 100 m

10.30 – 11.30

Band 11

Thermal Infrared 2

100 m × 100 m

11.50 – 12.50

3.2.1. Pre-treatment of the Landsat-8 OLI Image
Pre-processing mainly consisted of converting digital numbers to reflectance. When acquiring the Landsat 8 image, they take into account the effect of elements obscuring the image. The Landsat-8 OLI image appears with minor radiometric noise and therefore requires less processing. One of the most important processes in mineral exploration and geological discrimination using remote sensing techniques is radiometric correction .
In this study, the Haze/Rodiometric and Noise/Reduction modules of Erdas Imagine 2013 software were used to have high dynamic range and contrast. This function refines images using either a tufted cap or a point convolution approach, thus giving real reflectance images of objects on the ground. Image data is calibrated based on radiance, reflectance, or brightness temperatures using radiometric calibration, which reduces errors in the image's digital numbers. Always with the aim of improving the quality of the image, the radiometric correction operation is followed by the atmospheric correction and the geometric correction carried out on ENVIE 5.2. This section focuses on the initial adjustments we used after obtaining the images. Radiometric calibration, atmospheric correction, geometric correction, and noise elimination are the different preprocessing phases. This study uses the atmospheric correction technique to eliminate the effects of the atmosphere on the signal collected by the Landsat 8 satellite sensors. The Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) approach, which is a tool A first-principle atmospheric correction tool that corrects visible, near-infrared, and short-wave infrared wavelengths up to 3 m was employed in this study. Mineral prospecting has benefited from this technology . Preprocessing of raw Landsat 8 data, including atmospheric correction, radiometric calibration, and image normalization, was first performed on the dataset before any further processing. In the same environment, image normalization was performed on this dataset.
The main goal of image processing is to obtain a spectral signature of easily detectable hydrothermal alteration of rocks and lineaments. The processing applied in this work consisted of the extraction of the study area and the application of a mask, as well as the improvement of the quality of the images to make them more expressive, allowing better visualization of geological elements and phenomena. This processing includes: the band ratio; principal component analysis (PCA); directional filtering; and lineament extraction.
3.2.2. Treatment of Landsat-8 OLI Image
(i). Bands Ratio
Band ratio analysis is a technique that relies primarily on selected band operations. It is widely used and applied to mineral exploration to detect hydrothermal alterations that may be linked to mineral deposits . The band ratio consists of combining information from multiple bands into one. The band ratios that will be performed are: iron oxides, Al-OH-rich rocks, clay minerals, and hydrothermal alteration. In general, the ratio analysis bands are essential to highlight specific features that are not visible on individual bands, and the selection of the most appropriate bands for ratio analysis depends on the spectral properties of the rock or minerals and their relative abundance . The band ratio statistic can be calculated by dividing the digital number of a given band by the digital number of another band. Equation (1) illustrates the basic equation of band ratio analysis .
Br= B1i B2j (1)
Where B1 and B2 are the specific bands, and i and j represent the digital numbers in these bands. In this study, the 6/7, 6/5, and 4/2 band ratios of Landsat 8 OLI imagery were used to highlight hydrothermal alterations.
(ii). Principal Component Analysis (PCA)
Principal Component Analysis (PCA) is a mathematical transformation that consists of calculating the eigenvalues and eigenvectors of the variance-covariance matrix calculated from a series of images, then the principal components of the numerical count of the multi-spectral bands . It is a multivariate statistical analysis that aims to transform correlated variables into new free variables (principal components). PCA is very important for unraveling alteration evidence that may represent mineralization patterns . Basically, PCA transforms several correlated spectral bands into a smaller number of uncorrelated spectral bands called principal components. In exploration studies, PCA has been applied to Landsat imagery . In this study, PCA was applied to Landsat bands (2–7) to improve information relating to hydrothermal alterations, associated mineralizations, and to extract lineaments.
3.2.3. Lineaments Extraction
This treatment is applied to the ACP1 component . It involves the application of directional filters (N-S, E-W, NE-SW, and NE-SW) using the 7×7 Sobel matrix (Table 2). It makes it possible to highlight the major directions of linear structures. The filtering method is a technique aimed at eliminating noise contained in satellite data . This technique makes it possible to improve the visual quality of the image in order to facilitate its interpretation. In geology, we are interested in discontinuities in textures such as the contours of relatively homogeneous zones, which can reveal the presence of faults or fractures . Enhancement of lineaments amounts to highlighting in the image the strong reflectance transitions (tonal and/or texture contrast) in the image and the high spatial frequencies that are generally associated with them. Directional filters improve the perception of lineaments by causing an optical shadow effect to cast on the image as if it were illuminated by grazing light . In addition, this type of filter makes it possible to enhance lineaments (Table 3) that are not favored by the lighting source.
Table 2. 7×7 matrix of Sobel.

N-S

NE-SW

-1.0

-1.0

-1.0

0.0

1.0

1.0

1.0

-1.0

-1.0

-1.0

-1.0

-1.0

-1.0

-1.0

-1.0

-1.0

-1.0

0.0

1.0

1.0

1.0

-1.0

-1.0

-1.0

-1.0

-1.0

-1.0

-1.0

-1.0

-1.0

-1.0

0.0

1.0

1.0

1.0

-1.0

-1.0

-1.0

-1.0

-1.0

-1.0

-1.0

-1.0

-1.0

-1.0

0.0

1.0

1.0

1.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

-1.0

-1.0

-1.0

0.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

-1.0

-1.0

-1.0

0.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

-1.0

-1.0

-1.0

0.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

E-W

NW-SE

0.0

0.0

0.0

-0.7

-1.4

-1.4

-1.4

-1.0

-1.0

-1.0

0.0

1.0

1.0

1.0

0.0

0.0

0.0

-0.7

-1.4

-1.4

-1.4

-1.0

-1.0

-1.0

0.0

1.0

1.0

1.0

0.0

0.0

0.0

-0.7

-1.4

-1.4

-1.4

-1.0

-1.0

-1.0

0.0

1.0

1.0

1.0

1.4

1.4

1.4

0.0

-0.7

-0.7

-0.7

-1.0

-1.0

-1.0

0.0

1.0

1.0

1.0

1.4

1.4

1.4

0.7

0.0

0.0

0.0

-1.0

-1.0

-1.0

0.0

1.0

1.0

1.0

1.4

1.4

1.4

0.7

0.0

0.0

0.0

-1.0

-1.0

-1.0

0.0

1.0

1.0

1.0

1.4

1.4

1.4

0.7

0.0

0.0

0.0

-1.0

-1.0

-1.0

0.0

1.0

1.0

1.0

Table 3. Software specification for lineament extraction.

Sn

Parameter Settings

Parameter Value

1

Filter Radius (Pixels)

5

2

Edge Gradient Threshold

10

3

Curved Length Threshold (Pixels)

10

4

Line fitting Error Threshold (Pixels)

3

5

Angular difference Threshold (Degrees)

30

6

Linking Distance Threshold (Pixels)

20

3.2.4. Control and Validation of Mapping Results
Satellite image processing regularly faces the problem of the reliability of the results it offers and their validation . This highlights the need to carry out control and validation of all results of the interpretation of derived images. After any satellite image processing, geologists regularly encounter the problem of the reliability of the results they propose and their validation . This supports the obligation to carry out control and validation of all results of the interpretation of processed images. This evaluation and validation phase is very essential for a mapping study of the lineaments in the base zone, given the complexity of this environment. For a substantial improvement in the results obtained as part of this study, several verification and validation missions in the field were carried out. The phase of evaluation and validation of the lineaments extracted from the digital processing of satellite images is essential to judging the relevance of the method used .
The lineaments identified from Landsat-8 OLI images were the subject of a frequency analysis to highlight the main directions. To validate these lineaments, the directions obtained are then compared to those of previous work carried out in the study area . The structural diagram obtained also complements the inventory of faults in this area. The lineaments mapped by satellite imagery and retained as part of this study will have a fracturing value and could be assimilated to fractures or tectonic discontinuities. When the anthropogenic origin of a linear structure has been proven (roads, tracks, limits of forests or cultivated areas, high voltage lines, etc.), it has been removed. Thus, those remaining must probably correspond to tectonic fracturing .
Figure 2. Photography and microphotography of the rocks from Djouzami. (a) tungsten-bearing quartz vein with NE-SW trends, cross-cutting orthogneiss; (b) Blue fluorescence of tungsten (scheelite) in the quartz vein sample; (c) Hematization of quartz vein; (d) Tungsten (scheelite)-iron oxide association in the quartz vein sample; (e) Massive sulphide-iron oxide association in the quartz vein sample; (f, g) Epidote and chlorite Hydrothermal in amphibolite; (h, i) Muscovite-epidote-calcite Hydrothermal in orthogneiss; (j) Muscovitization in mylonitic gneiss; (k) Sericitization in metagranite; (l) Muscovitization in metagranite.
4. Results
4.1. Ultra-Violet Fluorescence Data and Hydrothermal Mineral Associations
On the field, tungsten (scheelite)-bearing quartz veins cross cut amphibolites, orthogneiss, mylonitic gneisses, and metagranites (e.g., Figure 2a). Scheelite is recognized in quartz veins by its blue luminescence under ultra-violet lighting (Figure 2b).
Hydrothermal alterations related to this mineralization affect the host rock in the study area progressively, depending on their mineralogical composition and structure. The main hydrothermal alterations process recognized in the mineralized quartz veins are hematization and tourmalinization (Figure 2c). By contrast in the host rocks, hydrothermal alteration types include clay/carbonate alterations, phyllic (sericite and muscovite) alterations, prophyllic (epidote and chlorite) alterations, potassic (K-feldspar) alterations, as well as silicification and sulfidation (Figures. 2h, i, j, k, l). Phyllic, clayey/carbonate, and prophyllic alterations are predominant in the distal alteration zone. Phyllic alteration and carbonatation are closely related to tungsten mineralization, and they are abundant in the proximal alteration zones (Figures 2d, e). Prophyllic alteration are abundant in amphibolites, and it is widespread around most tungsten ore veins, extending up to several meters from the ore body with a gradually decreasing intensity of development. Pyrite; iron oxide, sericite, and apatite are common in this zone. Phyllic alteration (sericite and muscovite) is dominated in orthogneiss, mylonitic gneiss, and metagranites (Figures 2h, i, j, k, and l). Muscovite is one of the most predominant types of hydrothermal alteration mineral in orthogneiss.
4.2. Mapping of Hydrothermal Alterations
The hydrothermal alteration zones in the Djouzami area are shows on the map of Figure 3. This map display the zones of abundance of iron oxides (Figure 3a), the zones of abundance of ferrous minerals (Figure 3b), the zones of abundance of clay and carbonate minerals (Figure 3c), and the zones of hydrothermal alteration (Figure 3d).
The Landsat 8 image band ratio method was applied to create combined RBG images highlighting hydrothermally altered rocks. The ratio of band 4 and band 2 was applied to highlight areas where iron oxide/hydroxide-containing minerals are abundant (Figure 3a), as bright red-toned pixels, which are concentrated in the alteration zones associated with tungsten and gold mineralization (Figure 3a). Average concentrations are present throughout the study area, with the exception of the eastern part of our study sector. The 6/5 band ratio makes it possible to distinguish ferrous minerals in a bright tone and shows a strong reflectance, indicating the presence of ferrous minerals in the form of a red pixel in the zones mineralized in tungsten and gold (Figure 3b). The 6/7 band ratio makes it possible to distinguish altered rocks containing clay minerals Al-OH, (Fe, Mg) –OH and carbonate minerals in darker blue pixels (Figure 3c). Average concentrations are very poorly dispersed in the entire study area, while the highest concentrations are limited to a few key locations. This ratio of band 6 and band 7 was used to map areas of clay minerals, shown in blue, but it is also sensitive to moisture variations in vegetation and soils, which also highlights vegetation.
RGB composite images containing band ratios were produced. An image using the ratio of Sabin (1999) (4/2, 6/7, 6/5) was calculated for mapping the identification of hydrothermal alteration zones (Figure 3d). By superimposing that sites where at least two types of mineralization meet are likely to be subject to the flow of hydrothermal minerals, The areas in purple, red, and blue concentrated in the central, western, and south-western parts of Djouzami are identified as areas with high potential for unexploited tungsten and gold mineralization, which could be good prospects for future detailed exploration (Figure 3d). The distribution of minerals in the study area is mainly found in areas crossed by tungsten veins or near gold occurrences. The minerals concentrate most strongly in the central part of the study area and form elongated bodies along the NE-SW direction (Figure 3d). Hydrothermal alteration zones highlight relationships between them.
Figure 3. Map of the hydrothermal alteration zones from the Djouzami (extract from the Landsat 8 image). (a) Map showing areas of abundance of iron oxides; (b) Map showing areas of abundance of ferrous minerals; (c) Map showing areas of abundance of clay and carbonate minerals; (d) Map from the Sabin 1999 report showing zones of hydrothermal alteration.
4.3. Extraction and Analysis of Lineaments
Principal component analysis (PCA), image combinations and directional spatial filtering were applied for image enhancement (Figure 4).
Figure 4. Sobel directional filter map of Djouzami lineaments (extracted from Landsat 8, ACP1 image). (a) Directional Sobel filter map of N-S lineaments; (b) Directional Sobel filter map of NE-SW lineaments; (c) Directional Sobel filter map of E-W lineaments; (d) Directional Sobel filter map of NW-SE lineaments.
Lineaments represent linear geological objects or alignments of sufficiently close geological objects, topographic discontinuities, or geomorphological structures inherited from ancient topographies . On the figure 4, the lineaments are materialized by the limits formed by the dark and light areas. They can sometimes extend over several kilometers. The different results presented in figure 4 more or less clearly enhance the lineaments of the sector. The detailed map of the lineaments (Figure 4) was produced thanks to an interpretation of the images derived from the different processing techniques. This map presents a significant density of lineaments of varying sizes, ranging from a few hundred meters to several kilometers. The N-S directional filter applied to ACP1 allowed the extraction of 394 lineaments (Figure 4a). The directions of the lineaments obtained from this filter were processed into directional rosettes, in order to evaluate their distribution (Figure 5).
Figure 5. Rose direction diagram of Djouzami Sobel directional filter lineaments. (a) Rose diagram of N-S lineaments; (b) Rose lineament diagram; (c) Rose diagram of E-W lineaments; (d) Rose diagram of NW-SE lineaments.
In Figure 5, the main direction is WNW-ESE and the secondary one is ENE-WSW (Figure 5a). The lineaments by Sobel NE-SW directional filter (Figure 4b) applied ACP1; this filter allows the extraction of 294 lineaments whose major direction is NW-SE and the secondary one NNW-SSE (Figure 5b). The lineaments by the Sobel E-W directional filter, applied to ACP1, allow the extraction of 307 lineaments (Figure 4c) and make it possible to highlight the directions following N-E and NE-SW (Figure 5c). The lineaments by the Sobel NW-SE directional filter applied to ACP1 allow the extraction of 333 lineaments (Figure 4d), the major direction of which is NE-SW (Figure 5d).
4.4. Combination of Sobel Filter Lineaments
A total of 1334 lineaments were highlighted by filtering the ACP1 image on the 7×7 Sobel window, following the directions N-S, NE-SW, E-W, and NW-SE. The combination map of the lineaments highlights the sector crossed by the bed of the Lom River as being the most fractured (Figure 6).
Figure 6. Summary map of lineaments from Djouzami.
The lineaments present a more continuous cartographic layout. These lineaments are characterized by more accentuated cartographic continuity and looser spatial density and therefore represent the fracturing of the study area. In order to study the geometry of the lineament network and identify the dominant directions, a statistical analysis was carried out. The main directions of the mapped lineaments are between ENE-WSW, N-S, and NE-SW (Figure 7).
Figure 7. Rose summary diagram of the direction of Djouzami lineaments.
5. Discussion
Previous works have reported occurrences of rare metal mineralizations in several areas of Eastern and Adamawa Cameroon . Into quartz veins which cross cut metamorphic rocks (orthogneiss, amphibolite, mylonitic gneiss and metagranite) in the Djouzami area, minerals characterized by the blue luminescence on the ultra-violet fluorescence corresponds to tungsten (scheelite). Scheelite related to veins in the French Massif central and to granite intrusion of Pyrenees is characterized by this typical blue luminescence . Most mineral deposits are identify in the field by recognizing surface rocks that have undergone hydrothermal alteration . Some type of hydrothermal alterations can be better distinguished through remote sensing than in the field or through petrographic study, as most minerals have absorption characteristics at wavelengths outside the spectrum visible to the human eye . In the Djouzami area, interaction between hydrothermal fluids and silicates of the host rock induce mineralogical transformations, giving rise to neorformed minerals associated with metallic minerals, tungsten, and probably gold mineralization. The study area is characterized by the high-intensity hydrothermal alteration, which damaged many rocks. The hydrothermal minerals assemblage made of chlorite, epidote, muscovite and/or sericite, hematite, tourmaline, as well as opaque minerals are associated to tungsten in the quartz veins. This assemblage is comparable to the one accompanying scheelite-related to quartz veins reported in the French Variscan range of the Massif Central and in Portugal . Based on the reflectance spectrum of minerals, whose numerous absorption-feature wavelengths are characterized within the VNIR and SWIR ranges, a number of authors have conducted studies pertaining to the groups of alteration minerals (oxides, clays, and carbonates) in hydrothermal alteration areas . According to , these minerals can be identified by the spectrum difference between their unique absorptions in altered rocks that have undergone hydrothermal alteration. With regard to the mineralogy of the altered rocks and the spectral resolution of the OLI sensor, it is noted that rock containing clays, carbonates, and chloritic elements exhibit a greater spectral gradient in Landsat 8 bands 6 and 7 (SWIR range) (Figure 5). Due to the main absorption features in the visible to NIR spectral region, derived from ferric iron, the iron oxides and hydroxyl enrichment of the mineralized altered rocks (e. g., hematite) are derived from the supergene activity that affects other hydrothermal minerals such as pyrite. These minerals have served as spectral indicators for targeting tungsten exploration. But it should also be noted that the hydrothermal alteration process described in the Djouzami area are identical to those of the gold mineralization described in rocks of the Lom group , and they accompany tungsten (scheelite) mineralization.
Lineament analysis can provides a valuable framework to guide the early stages of tungsten exploration in the Djouzami area. On the map of figure 6, most of the lineaments have curvilinear trajectories which indicates their penetrative character and suggests that they correspond to regional foliations. These lineaments have various trending, the main directions being ENE-WSW, NE-SW, N-S and E-W (Figure 7). The lineaments trended ENE-WSW are concordant to the well-known regional geological structures in southern Cameroon namely the Sanaga shear zone . The N-S lineaments corresponds to foliation reported in granitic rocks south of Meiganga area ; the E-W trending lineaments are equivalent to the foliation in gneiss and orthogneiss from Meiganga area . The NE-SW trending lineaments are concordant to the N040E Djouzami shear zone, the NE-SW trending Meiganga shear zone and the N050 mylonitic band which underline globally the Lom group . The lineaments characterized by the NE-SW trends are concordant to the direction of the tungsten-bearing quartz veins and the regional foliation (e. g. Figure 3a, b). In addition, the map of tungsten indices reveals a clear correlation between areas with high tungsten potential and high lineament density (oriented NE-SW). This association suggest that the NE-SW trending shear zone in the study area correspond to a channel for tungsten fluid flow or that it control tungsten mineralization. The Djouzami shear zone trends NE-SW similarly to the Bétaré-Oya shear zone (Just southwest of the study area) which structurally controls gold-bearing quartz veins . It is underlined in the Djouzami area by mylonitic foliation . and on the field, this foliation is often delineated by quartz veins (Figure 3a) suggesting that is correspond to brittle-ductile shear zone. According to some researchers, brittle-ductile shear zones are the preferential setting for metals concentration such as mesothermal orogenic gold mineralization . In several metalliferous districts, they are association between tungsten and gold mineralization . As hydrothermal mineral assemblage identified in this study is similar to the one accompanying gold mineralization in the Lom group , it is no excluded that the Djouzami shear zone control both gold and tungsten. Were also able to establish a positive correlation between lineamentary geological structures and existing mineralization using Landsat 8 imagery in the tropics. The results on the lineament aspect, interconnections between lineaments, and fracturing density of the study area are consistent with the work of . The Paddington tungsten hydrothermal veins deposit in Australia and the Ajjanahalli deposit in India are also controlled by major fractures .
6. Conclusions
The Djouzami area in the Adamawa-Yadé domain is dominantly made of metamorphic rocks, cross cut in place by mineralized quartz veins. Integrated ultra-violet fluorescence and remote sensing using Landsat-8 OLI images have led to the following specific conclusions:
1. Tungsten (scheelite) mineralization is hosted in quartz veins and it is characterized by its blue luminescence under ultra-violet lighting. The hydrothermal minerals assemblage accompanying this mineralization is made of muscovite, chlorite, tourmaline, hematite, calcite and sericite, similar to the gold-bearing quartz veins reported in the Lom group. The metallic minerals include only pyrite.
2. Alteration minerals mapped by remote sensing through study band ratios 6/7, 4/2 and 6/5 are respectively clay, iron oxide/hydroxides, and ferrous minerals. Lineaments mapped corresponds to regional foliations and/or shear zones and they are trended following the ENE-WSW, NE-SW, N-S and E-W directions.
3. The high hydrothermal zones and tungsten-bearing quartz veins are located along the NE-SW shear zone. This geological structure is considered as the pathway for mineralizing fluids and ground water circulation, and control tungsten mineralization.
Abbreviations

OLI

Operational Land Imager

PCA

Principal Component Analysis

BR

Band Ratio

VNIR

Visible Infrared Imaging Radiometer Suite

SWIR

Short-Wave Infrared

FLAASH

Fast Line-of-Sight Atmospheric

USGS

United States Geological Survey

TIRS

Thermal Infrared Sensor

RBG

Red Bleu Green

NIR

Near Infrared

W

Tungsten

Author Contributions
Yingyang Wanbitching Raoul: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Writing – original draft, Writing – review & editing
Nomo Negue Emmanuel: Project administration, Resources, Supervision, Validation, Visualization
Nguihdama Dagwaï: Funding acquisition, Investigation, Project administration, Resources
Ayiwouo Ngounouno Mouhamed: Formal Analysis, Funding acquisition, Methodology, Investigation
Mbohou Mgambié Isaac Bertrand: Project administration, Supervision, Validation, Visualization
Ngounouno Ismaïla: Project administration, Supervision, Validation, Visualization
Conflicts of Interest
The authors declare no conflicts of interest.
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Cite This Article
  • APA Style

    Raoul, Y. W., Emmanuel, N. N., Dagwaï, N., Mouhamed, A. N., Bertrand, M. G. I., et al. (2024). Prospecting Tungsten (Scheelite) Mineralization in the Djouzami Area (Adamawa Cameroon) Using Ultra-Violet (UV) Fluorescence and Landsat-8 OLI Images. Earth Sciences, 13(3), 97-115. https://doi.org/10.11648/j.earth.20241303.12

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    Raoul, Y. W.; Emmanuel, N. N.; Dagwaï, N.; Mouhamed, A. N.; Bertrand, M. G. I., et al. Prospecting Tungsten (Scheelite) Mineralization in the Djouzami Area (Adamawa Cameroon) Using Ultra-Violet (UV) Fluorescence and Landsat-8 OLI Images. Earth Sci. 2024, 13(3), 97-115. doi: 10.11648/j.earth.20241303.12

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    AMA Style

    Raoul YW, Emmanuel NN, Dagwaï N, Mouhamed AN, Bertrand MGI, et al. Prospecting Tungsten (Scheelite) Mineralization in the Djouzami Area (Adamawa Cameroon) Using Ultra-Violet (UV) Fluorescence and Landsat-8 OLI Images. Earth Sci. 2024;13(3):97-115. doi: 10.11648/j.earth.20241303.12

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  • @article{10.11648/j.earth.20241303.12,
      author = {Yingyang Wanbitching Raoul and Nomo Negue Emmanuel and Nguihdama Dagwaï and Ayiwouo Ngounouno Mouhamed and Mbowou Gbambie Isaac Bertrand and Ngounouno Ismaïla},
      title = {Prospecting Tungsten (Scheelite) Mineralization in the Djouzami Area (Adamawa Cameroon) Using Ultra-Violet (UV) Fluorescence and Landsat-8 OLI Images
    },
      journal = {Earth Sciences},
      volume = {13},
      number = {3},
      pages = {97-115},
      doi = {10.11648/j.earth.20241303.12},
      url = {https://doi.org/10.11648/j.earth.20241303.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.earth.20241303.12},
      abstract = {Remote sensing technology and X-rays fluorescence are largely used in the applied geology field. In this study, we combine field observations and petrography, remote sensing applications through the processing of the Landsat-8 OLI, and Ultra-violet fluorescence to map geological structures, hydrothermal alteration minerals, and characterize tungsten mineralization in the Djouzami area (Adamawa, Cameroon). Landsat-8 OLI satellite imagery, was processed to detect both hydrothermal alteration zones and regional structural lineaments associated with tungsten mineralization. Fieldworks and petrography revealed hydrothermal mineral assemblage made of muscovite, chlorite, tourmaline, hematite, calcite and sericite associated to metallic minerals including tungsten and pyrite hosted in quartz veins. This hydrothermal mineral assemblage is also identified in the gold-bearing quartz veins reported in several areas along the Lom group. Band Ratio (BR) and Principal component analysis (PCA) were implemented to extract spectral information related to alteration minerals. The Band Ratios 6/7, 4/2, and 6/5 have permits to map clay, iron oxide/hydroxides, and ferrous minerals, respectively. This study demonstrates the significant potential of fieldwork and multispectral remote sensing data processing for tungsten prospecting as a mineral exploration technique in the Djouzami region. The mapping led to the detection of 1334 lineaments which show four main directions. The ENE-WSW directions corresponds to the trending of the Sanaga shear zone; the NE-SW direction represents the trending of the Djouzami and the Bétaré-Oya shear zones or the main shear zone which underline the Lom group; the N-S and E-W directions are equivalent to the trending of the foliation in the Meiganga area. Most of the high hydrothermal zones and tungsten-bearing quartz veins are located along the NE-SW lineaments or shear zone. Gold-related NE-SW trending Djouzami shear zone is also proposed. The NE-SW structure constitute certainly pathway for mineralizing fluids and ground water circulation, and control tungsten mineralization. Results proposed in this work provide important information for research of characteristic hydrothermal minerals assemblage that accompany tungsten mineralization, and for identify structures that control this mineralization in the area.
    },
     year = {2024}
    }
    

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  • TY  - JOUR
    T1  - Prospecting Tungsten (Scheelite) Mineralization in the Djouzami Area (Adamawa Cameroon) Using Ultra-Violet (UV) Fluorescence and Landsat-8 OLI Images
    
    AU  - Yingyang Wanbitching Raoul
    AU  - Nomo Negue Emmanuel
    AU  - Nguihdama Dagwaï
    AU  - Ayiwouo Ngounouno Mouhamed
    AU  - Mbowou Gbambie Isaac Bertrand
    AU  - Ngounouno Ismaïla
    Y1  - 2024/06/27
    PY  - 2024
    N1  - https://doi.org/10.11648/j.earth.20241303.12
    DO  - 10.11648/j.earth.20241303.12
    T2  - Earth Sciences
    JF  - Earth Sciences
    JO  - Earth Sciences
    SP  - 97
    EP  - 115
    PB  - Science Publishing Group
    SN  - 2328-5982
    UR  - https://doi.org/10.11648/j.earth.20241303.12
    AB  - Remote sensing technology and X-rays fluorescence are largely used in the applied geology field. In this study, we combine field observations and petrography, remote sensing applications through the processing of the Landsat-8 OLI, and Ultra-violet fluorescence to map geological structures, hydrothermal alteration minerals, and characterize tungsten mineralization in the Djouzami area (Adamawa, Cameroon). Landsat-8 OLI satellite imagery, was processed to detect both hydrothermal alteration zones and regional structural lineaments associated with tungsten mineralization. Fieldworks and petrography revealed hydrothermal mineral assemblage made of muscovite, chlorite, tourmaline, hematite, calcite and sericite associated to metallic minerals including tungsten and pyrite hosted in quartz veins. This hydrothermal mineral assemblage is also identified in the gold-bearing quartz veins reported in several areas along the Lom group. Band Ratio (BR) and Principal component analysis (PCA) were implemented to extract spectral information related to alteration minerals. The Band Ratios 6/7, 4/2, and 6/5 have permits to map clay, iron oxide/hydroxides, and ferrous minerals, respectively. This study demonstrates the significant potential of fieldwork and multispectral remote sensing data processing for tungsten prospecting as a mineral exploration technique in the Djouzami region. The mapping led to the detection of 1334 lineaments which show four main directions. The ENE-WSW directions corresponds to the trending of the Sanaga shear zone; the NE-SW direction represents the trending of the Djouzami and the Bétaré-Oya shear zones or the main shear zone which underline the Lom group; the N-S and E-W directions are equivalent to the trending of the foliation in the Meiganga area. Most of the high hydrothermal zones and tungsten-bearing quartz veins are located along the NE-SW lineaments or shear zone. Gold-related NE-SW trending Djouzami shear zone is also proposed. The NE-SW structure constitute certainly pathway for mineralizing fluids and ground water circulation, and control tungsten mineralization. Results proposed in this work provide important information for research of characteristic hydrothermal minerals assemblage that accompany tungsten mineralization, and for identify structures that control this mineralization in the area.
    
    VL  - 13
    IS  - 3
    ER  - 

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Author Information
  • Figure 1

    Figure 1. (A) Geology of West-central Africa and northern Brazil in a Gondwana (pre-drift) reconstruction (modified from [68, 71]. Thick line, boundary of the two continents: (1) Phanerozoic cover; (2) Neoproterozoic formations; (3) Regions of Brasiliano/Panafrican deformation in which Palaeoproterozoic basement is absent or only present as small isolated blocks; (4) Regions of Brasiliano/Panafrican deformation with large amounts of reworked Palaeoproterozoic basement; (5) cratons. (B) Geological map of Cameroon (after [68]. The Lom group is represented by a yellow rectangle. KCF (Kribi-Campo fault); SSZ (Sanaga shear zone); CCSZ (Central Cameroon shear zone); TBSZ (Tcholliré-Banyo shear zone); MNSZ (Mayo Nolti shear zone) and GGSZ (Godé-Gormaya shear zone). (1) volcanic rokcs (Tertiary to recent); (2) Post-Panafrican sedimentary cover; (3) Syn- to Post-tectonic granitoids (500-600Ma); (4) Pre- to syn-tectonic orthogneisses (600-660Ma); (5) Meso- to Neoproterozoic volcano-sedimentary belt (700-1000Ma; (6) Yokadouma and Dja series (age unknown); (7) Palaeoproterozoic gneiss and orthogneiss (2100Ma) and (8) Ntem Complex (3000Ma). (C) Structural map of the Lom Group [72]. Monocyclic units associated to grabens: (a) orthogneiss; (b) Lom volcaniclastic series; (c) polygenic conglomerates; (d) Mari quartzites. Polycyclic units: (e) staurolite micaschists; (f) Lom bridge gneisses; (g) staurolite and chloritoid ductile mylonites. Intrusions with uncertain structural position: (h) granites (G2); (i) granites and monzonites; (j) metalamprophyres (modified after [47]). Inset: location of the Lom Group as an extensional relay zone between two en- echelon segments of the Sanaga fault; the opening of this basin corresponds to sinistral shear movement along these major faults. The study area is indicated in Figure 1C by the red rectangle.

  • Figure 2

    Figure 2. Photography and microphotography of the rocks from Djouzami. (a) tungsten-bearing quartz vein with NE-SW trends, cross-cutting orthogneiss; (b) Blue fluorescence of tungsten (scheelite) in the quartz vein sample; (c) Hematization of quartz vein; (d) Tungsten (scheelite)-iron oxide association in the quartz vein sample; (e) Massive sulphide-iron oxide association in the quartz vein sample; (f, g) Epidote and chlorite Hydrothermal in amphibolite; (h, i) Muscovite-epidote-calcite Hydrothermal in orthogneiss; (j) Muscovitization in mylonitic gneiss; (k) Sericitization in metagranite; (l) Muscovitization in metagranite.

  • Figure 3

    Figure 3. Map of the hydrothermal alteration zones from the Djouzami (extract from the Landsat 8 image). (a) Map showing areas of abundance of iron oxides; (b) Map showing areas of abundance of ferrous minerals; (c) Map showing areas of abundance of clay and carbonate minerals; (d) Map from the Sabin 1999 report showing zones of hydrothermal alteration.

  • Figure 4

    Figure 4. Sobel directional filter map of Djouzami lineaments (extracted from Landsat 8, ACP1 image). (a) Directional Sobel filter map of N-S lineaments; (b) Directional Sobel filter map of NE-SW lineaments; (c) Directional Sobel filter map of E-W lineaments; (d) Directional Sobel filter map of NW-SE lineaments.

  • Figure 5

    Figure 5. Rose direction diagram of Djouzami Sobel directional filter lineaments. (a) Rose diagram of N-S lineaments; (b) Rose lineament diagram; (c) Rose diagram of E-W lineaments; (d) Rose diagram of NW-SE lineaments.

  • Figure 6

    Figure 6. Summary map of lineaments from Djouzami.

  • Figure 7

    Figure 7. Rose summary diagram of the direction of Djouzami lineaments.