Fast and Easy Integration and Classification of Hyperspectral Optical and Thermal Data: A Mineral Mapping Case Study

Abstract

Independent spectral analysis is usually employed to analyse hyperspectral optical (visible: VIS, near infrared: NIR, shortwave infrared: SWIR) and thermal (longwave infrared: LWIR) data. The integration of the spectral information provided by different wavelength ranges and the subsequent complex classification still remains challenging. In this paper we will demonstrate the benefits of mineral classification employed to optical and thermal hyperspectral data (CASI and SASI: $0.4-2.5 \mathrm{m}$ ; TASI: $8.6-11.5 \mu \mathrm{m}$ ) when using new tools (QUANTools) developed at the Czech Geological Survey (CGS). In this case study, the same approach was employed as published by Kopackova and Koucka (2017) [1], however, previously hyperspectral optical data were used together with multispectral long-wave infrared (LWIR) data. In this paper we demonstrate that the new concept, which was recently introduced, can be directly employed to CASI/SASI/TASI hyperspectral datasets and provide results in terms of mineral classification in a quick and easy way.