The stakes are considerable. Chad is widely regarded as having substantial geological potential, yet more than 60 percent of its subsoil remains unexplored, according to the authors. The country sits within the Central African Pan-African Belt, a vast orogenic chain forged roughly 600 million years ago when the São Francisco-Congo cratons, the West African craton and the Saharan metacraton collided. In Chad this chain surfaces in several basement massifs, including Tibesti in the north, Ouaddaï in the east, Mayo Kebbi in the southwest, Guéra in the centre, and the little-studied Baïbokoum massif in the far south, which continues into Cameroon and the Central African Republic as part of the Adamawa-Yadé domain. Earlier work had dated syenites there to about 654 million years and associated granites to between 632 and 568 million years, but no systematic exploration map had ever been drawn.

The team’s raw material was a single, almost cloud-free Landsat 9 scene acquired on 18 February 2025, with cloud cover of just 0.21 percent. Landsat 9’s Operational Land Imager captures light from the visible, near-infrared and shortwave-infrared parts of the spectrum in nine bands, plus a 15-metre panchromatic band that the researchers fused with the 30-metre multispectral data to sharpen the imagery. Before any interpretation, the raw digital numbers were converted to surface reflectance and corrected for atmospheric distortion using the QUAC algorithm, which the authors note typically recovers reflectance spectra within 10 to 15 percent of ground reference values. That preprocessing matters: without it, water vapour and aerosols can masquerade as mineral signatures.

With clean data in hand, the researchers deployed a battery of image-processing techniques, each probing a different aspect of how rocks reflect light. False colour composites using bands 7, 5 and 3 gave a quick visual first pass, rendering syenites in light pink, gneisses in green and shales in white. Principal component analysis then compressed the spectral information from six bands into statistically independent components; the first three components carried 92.86, 5.94 and 0.84 percent of the total variance, and the third component isolated anomalies linked to altered and ferrous minerals. Minimum noise fraction transformation performed a similar trick while explicitly separating signal from noise, which proved especially useful for low-reflectance units such as syenites and shales.

Band ratios delivered the most direct mineralogical clues. Ratios such as 4/2 highlight iron oxides like hematite and goethite, which absorb strongly in the blue and reflect in the red; 6/7 targets the hydroxyl and carbonate absorption near 2.2 micrometres produced by clays and micas; and 6/5 picks out ferrous minerals. On these ratio images the team mapped iron-oxide zones, ferrous occurrences, clay-rich alteration and broader hydrothermal halos across the pluton. To push identification further, they ran the constrained energy minimization algorithm on bands 7, 5 and 3 against laboratory spectra from the USGS library, matching pixels to biotite, chlorite, goethite, hematite, illite, ilmenite, kaolinite, magnetite, pyrite and rutile.

The final classification step used the Spectral Angle Mapper, an algorithm that treats each pixel’s spectrum as a vector and measures its angular distance from reference spectra, making it relatively insensitive to illumination differences caused by topography. With a fixed threshold of 0.1 radians, SAM successfully separated syenite, shale and gneiss, and a confusion-matrix accuracy assessment returned an overall accuracy of 80 percent with a Kappa coefficient of 0.80. The authors report that in subsequent tests the method reached full agreement with reference data, underscoring its reliability for lithological mapping in Precambrian terrain, where subtle mineralogical contrasts and limited exposure typically defeat conventional interpretation.

Structure proved just as important as chemistry. Using the panchromatic band and the PCI Geomatica line tool, the team extracted lineaments, the linear traces of faults, fractures and shear zones that often channel mineralising fluids. Rose diagrams revealed dominant NE-SW and E-W trends, with an additional NNE-SSW set, and the iron-oxide anomalies align along the NE-SW corridor. Fieldwork grouped these structures into three deformation phases: D1 trending NW-SE, D2 from N-S to NNE-SSW, and D3 from E-W to NW-SE. Because lineaments can also reflect roads, vegetation boundaries or artefacts, the researchers validated them against geological maps and ground observations before accepting them as tectonic features.

The ground truth came from weeks of mapping and dozens of thin sections. Mount Kongaoura, a NE-SW-trending ridge south of the town, is built of fine-, medium- and coarse-grained syenites cut by pegmatite and aplite veins and studded with microsyenodiorite enclaves. Under the microscope, the coarse syenites contain 40 to 50 percent alkali feldspar with pyroxene, amphibole and biotite, while the metamorphic country rocks include hornblende-biotite gneisses with granonematoblastic textures, biotite gneisses, amphibolites dominated by 50 to 60 percent amphibole, and striking mylonites. At Mbaïssaye, a N15E shear corridor within the syenite shows potassium feldspar porphyroclasts crushed into a matrix that climbs from 30 to 60 percent of the rock, direct evidence of the ductile shearing that accompanied fluid circulation.

Stitching everything together in a GIS, the team produced a synthesis litho-mineral map that revises the region’s geology and flags its most promising ground. The syenitic units emerge as the principal hosts of iron oxides and ferrous minerals, while the gneisses carry significant hydroxyl-bearing alteration, with mineralisation styles consistent with greisen, skarn and quartz-vein systems controlled by foliations, fractures and joints. The authors are candid about the limits: the absence of geochemical data constrains interpretation, and spectral methods detect alteration, not ore grades. Their next step is automated processing of the imagery followed by whole-rock geochemistry on a much larger sample set. Even so, the message is clear and quietly transformative for a country where exploration budgets are thin: a free satellite scene, a laptop and a hammer can now do the work that once required years of costly reconnaissance, and in Baïbokoum they have just redrawn the map.

Subject of Research: Remote sensing and field-based mapping of mineralisation potential in the Baïbokoum pluton, southern Chad

Article Title: Mapping and discrimination of mineralisation potential of the Baïbokoum pluton (Southern Chad), using Landsat 9 OLI images and field observations

Article References: Gustave, B. R., Ousmanou, S., Ngarena, K. M., Jules, T. K., Souleymane, A. N., Merlin, G. D., & Maurice, K. (2026). Mapping and discrimination of mineralisation potential of the Baïbokoum pluton (Southern Chad), using Landsat 9 OLI images and field observations. Discover Geoscience, 4(1), Article 292. https://doi.org/10.1007/s44288-026-00673-5

Image Credits: AI Generated

DOI: 10.1007/s44288-026-00673-5

Keywords: Landsat 9, remote sensing, mineral exploration, Chad, Baïbokoum, syenite, iron oxides, hydrothermal alteration, Spectral Angle Mapper, principal component analysis, lineaments, Pan-African belt