Table of Contents
Remote Sens., Volume 9, Issue 1 (January 2017) – 98 articles
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Cover Story (view full-size image) Unmanned Aerial Systems (UAS) or drones feature increasing popularity due to their ability to [...] Read more. Unmanned Aerial Systems (UAS) or drones feature increasing popularity due to their ability to acquire high quality imagery of hardly accessible areas precisely, fast, and at any time. Equipped with a hyperspectral sensor, UAS are able to deliver characteristic spectral information for each recorded pixel, which may provide indications about type and composition of outcropping material. However, unpredictable movements of the drone as well as complex viewing geometry and illumination of the Earth’s surface require careful geometric and radiometric corrections of the acquired data. These corrections are crucial, especially in geological applications. MEPHySTo is a new dedicated Python-based open-source toolbox for the processing of drone-borne hyperspectral data. The created accurately corrected datasets are specifically designed for the challenges of geological surveys such as mineral exploration and lithological mapping. View the paper.