*Article* **Integration of Absorption Feature Information from Visible to Longwave Infrared Spectral Ranges for Mineral Mapping**

#### **Veronika Kopaˇcková \* and Lucie Koucká**

Remote Sensing Department, Czech Geological Survey, Prague 11821, Czech Republic; lucie.koucka@gmail.com **\*** Correspondence: veronika.kopackova@seznam.cz; Tel.: +420-257-089-481

Received: 4 September 2017; Accepted: 24 September 2017; Published: 28 September 2017

**Abstract:** Merging hyperspectral data from optical and thermal ranges allows a wider variety of minerals to be mapped and thus allows lithology to be mapped in a more complex way. In contrast, in most of the studies that have taken advantage of the data from the visible (VIS), near-infrared (NIR), shortwave infrared (SWIR) and longwave infrared (LWIR) spectral ranges, these different spectral ranges were analysed and interpreted separately. This limits the complexity of the final interpretation. In this study a presentation is made of how multiple absorption features, which are directly linked to the mineral composition and are present throughout the VIS, NIR, SWIR and LWIR ranges, can be automatically derived and, moreover, how these new datasets can be successfully used for mineral/lithology mapping. The biggest advantage of this approach is that it overcomes the issue of prior definition of endmembers, which is a requested routine employed in all widely used spectral mapping techniques. In this study, two different airborne image datasets were analysed, HyMap (VIS/NIR/SWIR image data) and Airborne Hyperspectral Scanner (AHS, LWIR image data). Both datasets were acquired over the Sokolov lignite open-cast mines in the Czech Republic. It is further demonstrated that even in this case, when the absorption feature information derived from multispectral LWIR data is integrated with the absorption feature information derived from hyperspectral VIS/NIR/SWIR data, an important improvement in terms of more complex mineral mapping is achieved.

**Keywords:** imaging spectroscopy; optical spectral region; thermal infrared spectral region; mineral mapping; data integration; HyMap; AHS; raw material; remote sensing
