DRONE DATA ATMOSPHERIC CORRECTION CONCEPT FOR MULTI- AND HYPERSPECTRAL IMAGERY – THE DROACOR MODEL

Abstract

Remote sensing with unmanned aerial vehicles (UAVs) is a fast and cost-efficient tool for mapping and environmental monitoring. The sensors are operated at low flight altitudes, usually below 500 m above ground, leading to spatial resolutions up to the centimeter range. This type of data causes new challenges in atmospheric compensation and surface reflectance retrieval. Based on these specific boundary conditions, a new drone based atmospheric correction concept (DROACOR) is proposed, which is designed for currently available UAV based sensors. It is suited for multispectral visible/near infrared sensors as well as hyperspectral instruments covering the 400–1000 nm spectral region or the 400–2500 nm spectrum. The goal of the development is a fully automatic processor which dynamically adjusts to the given instrument and the atmospheric conditions. Optionally, irradiance measurements from simultaneously measured cosine receptors or from in-field reference panels can be taken into account to improve the processing quality by adjusting the irradiance parameter or by performing an in-flight vicarious calibration. Examples of DROACOR processing results are presented for a multispectral image data set and a hyperspectral data set, both acquired at variable flight altitudes. The resulting spectra show the applicability of the methods for both sensor types and an accuracy level below 2.5% reflectance units.