Determination of Snow Pollution from EnMAP and in Situ Data

Abstract

Observing snow pollution is crucial for understanding environmental changes and assessing ecosystem health. Snow is a vital indicator of atmospheric pollutants, and its spectral properties can reveal concentrations of substances like black carbon and dust, which affect climate and water quality. Spaceborne hyperspectral instruments offer the required spectral resolution to characterize optical active pollutants based on their spectral shape. A simple method to derive snow properties using hyperspectral data from four specific wavelengths is used, enabling accurate identification of snow contamination levels. We applied this method to in situ spectra and En-MAP scenes from three locations, demonstrating its effectiveness in varying conditions. The findings enhance our ability to monitor and manage snow pollution, offering insights into its implications for climate feedback mechanisms and water resource management. In addition, this method allows the determination of radiative forcing based on the detected contamination.