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Abstract
The aerial hyperspectral imagery has a large information content and contains data not
just only in the visible light spectra but in the near-infrared and the short-wave infrared
spectra as well. Due to this, the technology is applicable to examine and detect
preferences and conditions that visible identification is not possible or limited. During
the last decade, hyperspectral imagery was successfully used for the analysis of
vegetation, soil or minerals. During our research the AISA Fenix1K hyperspectral
sensor of the Research Institute was used for data collection with the collaboration of
experts from the Finnish sensor producer company near to Siófok. The collected aerial
hyperspectral data and the ground spectral data as reference were compared and a
spectral library of the examined materials was developed for future classifications. The
ability to separate various materials was examined with statistical analyses with which
we can determine the spectral separability of target objects. The analysis was fulfilled on
the original and on transformed channels as well. According to the results we can
conclude that the transformed channels are more applicable to separate these materials
which was demonstrated on scatter plots too.