Satellite-based silica mapping as an essential mineral for clean energy transition: Remote sensing mineral exploration as a climate change adaptation approach

Elsevier, Journal of African Earth Sciences, Volume 196, December 2022
Ali H.F., Ghoneim S.M.

One of the most important challenges in facing climate changes is transition to clean energy to reduce the warm gases emissions. The technologies of clean energy transition require more mineral resources than the traditional fossil fuel methods. The present study sheds the light on the role of mineral exploration using remote sensing techniques to fulfill the requirements of the clean energy technologies from mineral resources. In this study, the capabilities of ASTER data in mapping silica (an essential mineral for solar energy technologies) were demonstrated. Two case study areas with different geological environments of silica-rich rock units were studied. The Faiyum area contains sedimentary silica-rich rock units; mainly white sand, sandstone, and sand dunes. While the Higlig-Suwayqat area contains basement silica-rich rock units; mainly quartz plugs and veins included in the granitic rocks. Two remote sensing techniques; Band ratio (BR), and Constrained Energy Minimization (CEM) supervised classification techniques were applied to the ASTER surface reflectance. Several ASTER band ratios were tested; the ratio of b14/b12 was found the most effective band ratio for delineating the silica-rich areas. On the other hand, the CEM technique was applied using the USGS spectral signature of quartz mineral. CEM technique enabled mapping the pixels that have similar signatures to the input quartz signature as silica-rich areas. A field study was conducted in both the studied case areas to validate the remote sensing results; several silica-rich units were observed including; white sand, sandstone, sand dunes, quartz plugs/veins, and sand-rich wadi deposits. Based on the distribution of the silica-rich units mapped by both the adopted techniques as compared to the field observations, it is found that the accuracy of both the techniques is very high with an advantage of the CEM technique over the BR technique.