GeoSpectra delivers advanced spectral analysis of medium to high-resolution multispectral imagery (e.g., Aster  and Worlview-3) to map structures and key alteration minerals of the area’s mineral systems, including favorable clays, sulphates, carbonates, iron oxides, and silica, for regional and camp-scale on-ground exploration.

GeoSpectra delivers advanced spectral analysis of hyperspectral satellite imagery (EnMAp and PRISMA) to  map structures and key alteration minerals of the area’s mineral systems, including favorable clays, sulphates, carbonates and iron oxides for on-ground regional-district scale exploration.

GeoSpectra process high-resolution satellite imagery to delineate structures and lithological boundaries at regional to prospect scales. By integrating structural/lithological interpretation with other exploration data, we identify key geological controls on mineralisation.

GeoSpectra applies conventional and AI-based exploration data integration to identify and prioritise mineral targets across regional to prospect scales for on-ground exploration. This approach improves targeting accuracy, reduces exploration risk, and supports efficient, data-driven decision-making.

GeoSpectra uses machine learning-based semi-supervised classification and block modelling,  within mineral systems frameworks, to optimize drilling targets, model deposits, and estimate reserves across the exploration lifecycle.

Some satellite imagery require geometric (orthorectification), radiometric  and atmospheric corrections before spectral analyses. GeoSpectra has developed inhouse workflows to correct and apply 2D and 3D enhancement of the multi- and hyperspectral satellite imagery (videos and images) for advanced interpretation.

GeoSpectra processes and interprets multi-source geochemical and geophysical datasets, integrating them with remote sensing and geological information to support mineral potential mapping from regional to deposit scale.

GeoSpectra applies advanced spectral remote sensing to map key alteration minerals—such as certain muscovite, chlorite, clays and iron oxides porphyry Cu-Au systems—and delineate favourable structural controls. These insights are integrated with other geospatial data  to define high-priority targets for regional to prospect-scale field exploration.

GeoSpectra applies advanced spectral remote sensing to identify indicator minerals in critical mineral systems, including lithium-bearing minerals (e.g., lepidolite, spodumene) and iron oxides in pegmatites, calcite–silica–iron oxide signatures in REE-bearing carbonatites, and dolomite–clay–silica signatures in Ga–Ge-bearing MVT systems.