Processing of drone-borne hyperspectral data for geological applications

Abstract

Unmanned Aerial Systems (UAS) are used increasingly to close the gap between space-or airborne and field spectral data. They are able to provide high-resolution hyperspectral images within a short time. However, complex geometric and radiometric corrections are required. These correction steps are crucial, especially when the data should be used in geological applications such as detection of raw materials. Thus, in the following paper we present a new toolbox for processing drone-borne hyperspectral data. Processing steps comprise automatic co-registration, mosaicking and georeferencing as well as topographic and illumination correction. For the first time we show the applicability of drone-borne hyperspectral data for geological surveys.