Hyperspectral remote-sensing in the reflected infrared and thermal infrared regions offers a unique and efficient alternative for mineral mapping, as most minerals exhibit spectral features in these regions, mainly in the shortwave and longwave infrared. Airborne hyperspectral data in both spectral regions, acquired with the AisaFENIX and AisaOWL (Specim) sensors over Makhtesh Ramon in Israel, were analyzed. Calculating the reflectance and emissivity spectra of each pixel in the shortwave infrared and longwave infrared region images, respectively, and determining mineral indices enabled identifying the dominant minerals in this area-kaolinite, calcite, dolomite, quartz, feldspars and gypsum-and mapping their spatial distribution in the surface. The benefit of using hyperspectral data from both reflected infrared and thermal infrared regions to improve mineral identification was demonstrated.
- Hyperspectral remote sensing
- Makhtesh Ramon
- Mineral mappi
- Reflected infrared region
- Thermal infrared region
All Science Journal Classification (ASJC) codes
- Earth and Planetary Sciences(all)