The green energy transition is speculated to cause an increase in the demand for raw materials while recycling rates are improving; discoveries are required to maintain supply. Geological remote sensing offers a cost-effective way of exploring mineral resources. While satellite and airborne imaging are routinely used for exploration targeting, a gap remains at the outcrop scale. Hyperspectral imaging (HSI) is advantageous for large-scale regional mapping, typically performed from satellite or airborne platforms. Accurately mapping geological lithologies remains challenging in inaccessible areas, such as rough terrain or mine sites. Proximal sensing techniques can boost geological activities’ reliability, safety, and efficiency in exploration or during mining activities. It also generates objective, reproducible results and valuable raw data that can be archived, further processed, and re-interpreted. Ground-based hyperspectral imaging of outcrops has steadily increased during the last decade due to sensor development and better processing routines. There is often a big technology gap related to mineral mapping, integration of images and spectra (reduction in manual identification of minerals and types) and hyperspectral data visualisation through remote sensing. TEXMiN Foundation, in collaboration with its industry partner Dassault Systemes Foundation, carried out the project, ‘Developing Hyperspectral Image Processing and Analysis, build a rich library of Hyperspectral images of a vast range of minerals from India which will help in increasing prediction accuracy of mineral deposit for mining exploration’.