Hyperspectral remote sensing in lithological mapping, mineral exploration, and environmental geology: an updated review

Hyperspectral imaging has been used in a variety of geological applications since its advent in the 1970s. In the last few decades, different techniques have been developed by geologists to analyze hyperspectral data in order to quantitatively extract geological information from the high-spectral-resolution remote sensing images. We attempt to review and update various steps of the techniques used in geological information extraction, such as lithological and mineralogical mapping, ore exploration, and environmental geology. The steps include atmospheric correction, dimensionality processing, endmember extraction, and image classification. It is identified that per-pixel and subpixel image classifiers can generate accurate alteration mineral maps. Producing geological maps of different surface materials including minerals and rocks is one of the most important geological applications. The hyperspectral images classification methods demonstrate the potential for being used as a main tool in the mining industry and environmental geology. To exemplify the potential, we also include a few case studies of different geological applications. (C) 2021 Society of Photo-Optical Instrumentation Engineers (SPIE)

Automated summary

Hyperspectral imaging has been widely used in geological applications since the 1970s, and it can accurately extract geological information such as lithological and mineralogical mapping as well as ore exploration. The classification methods of hyperspectral images show potential to be a main tool in the mining industry and environmental geology.