Application of remote sensing techniques in lithological and mineral exploration: discrimination of granitoids bearing iron and corundum deposits in southeastern Banyo, Adamawa region-Cameroon

• Published in: Earth science informatics 2023-03, Vol.16 (1), p.259-285
• Main Authors: Ousmanou, Safianou, Fozing, Eric Martial, Kwékam, Maurice, Fodoue, Yaya, Jeatsa, Leprince Dubois Alokeng
• Format: Article
• Language: English
• Subjects: Earth and Environmental Science; Earth Sciences; Earth System Sciences; Information Systems Applications (incl.Internet); Ontology; Simulation and Modeling; Space Exploration and Astronautics; Space Sciences (including Extraterrestrial Physics
• ISSN: 1865-0473; 1865-0481
• DOI: 10.1007/s12145-023-00937-5

Discrimination of granitoids bearing iron and corundum mineral deposits in the southeastern part of Banyo (Adamawa region of Cameroon) using Landsat 8 OLI data and provides essential information’s for exploration. Field data and remote sensing traditional mapping techniques including false color composites (FCCs), principal component analysis (PCA), Crosta-PCA, band ratios (BR), constrained energy minimization (CEM), classification algorithm as maximum likelihood, and spectral angle mapper (SAM) were applied to the visible, near-infrared, and shortwave infrared bands of Landsat 8 OLI data. The results of this research demonstrated to be most effective to highlight potential locations of granitoids bearing iron and corundum deposits. In addition, iron deposit was mapped using band ratio 4/2 due to high reflectivity in the visible red region while corundum deposits are detected by applying the constrained energy minimization method to Landsat-8 OLI band ratio 6/7 highlighting bright tones. The results of remote sensing data were validated through fieldwork and laboratory analysis (thin section analysis). Furthermore, lineaments analysis revealed the prevalence of three major structural trends affecting the southeastern part of Banyo ( N-S, E-W, and NE-SW to ENE-WSW) paired with mapped lithologies allows the potential emplacement of mineral deposits. The novelty of the present study relies in the integration of Landsat 8 OLI and field data enabling the identification of highly prospective lithological units, mineral deposits, defining exploration targets, and the minimisation of time consuming field reconnaissance in the study area.