Spectral indicants to determine the most abundant mineral(s) in soil samples,using LWIR hyper- and multi- spectral configurations.

Ground-based hyperspectral longwave infrared (LWIR) images of 90 soil samples from the legacy soil spectral library of Israel were acquired with the Telops Hyper-Cam sensor. Mineral-related emissivity features were identified and used to create indicants and indices to determine the appearance and content of quartz, clay minerals, and carbonates in the soil in a semi-quantitative manner—from more to less abundant minerals. The resultant most abundant mineral(s) fit the results of the XRD analysis in most (90%) of the soil samples. The full mineralogy, including the relative amounts of the less abundant minerals, of most (75%) of the soil samples fit the XRD analysis results.

These hyperspectral LWIR images were resampled to the multispectral LWIR configurations of the airborne sensor Airborne Hyperspectral Scanner (AHS) and present and future spaceborne sensors—Land Surface Temperature Monitoring (LSTM), ECOSTRESS and Thermal Infra-Red Imaging Satellite for High-resolution Natural Resource Assessment (TRISHNA). The emissivity spectrum of each soil sample was calculated and then spectral indicants were created, for each spectral configuration, to determine the content of quartz, clay minerals and carbonates in each soil. The resulted mineral classification, in all spectral configurations, of the most abundant mineral(s) fit the XRD analysis results in most (90-80%) of the soil samples. However, identifying the less abundant minerals in each soil, and determining the mineralogy, from more to less abundant, using multispectral-based created indicants, was enabled only with the AHS configuration.