Mapping and Classification of Areas with Mineral Potential in Guinea-Bissau

Objective: The objective of this work is to use remote sensing techniques to map and classify the mineral aptitude of Guinea-Bissau, a country that is in the process of intensifying the exploration of its natural resources and has a scarcity of studies on the subject. Theoretical Framework: This work is theoretically based on remote sensing techniques and multispectral classification, using a cloud-based platform for mineral suitability mapping. The iSDAsoil database, used in Google Earth Engine for large-scale territorial analysis, stands out. Method: The method uses and processes the iSDAsoil database to estimate five levels of mineral suitability classes. Data on calcium, iron, aluminum, sand, magnesium, silt, potassium, and clay were used, with multiclass classification and thematic map generation. Results and Discussion: The results suggest low mineral prominence, with significant nutrient presence in Gabú, Cacheu, and Tombali. It is estimated that approximately 64% of the territory is classified as weak or very weak, while less than 1% is classified as strong or very strong. Research Implications: This work provides technical support for the formulation of public policies in the sustainable management of natural resources and suggests future research on mineral extraction in the region. Originality/Value: The study fills a gap in the literature by integrating iSDAsoil data under cloud analysis for mineral suitability estimation of Guinea-Bissau, providing a baseline approach for sustainable monitoring.