Biases in estimated vegetation indices from observations under cloudy conditions

Wolf, Kevin; Jäkel, Evelyn; Ehrlich, André; Schäfer, Michael; Feilhauer, Hannes; Huth, Andreas; Wendisch, Manfred

doi:10.5194/bg-22-7797-2025

Articles | Volume 22, issue 23

https://doi.org/10.5194/bg-22-7797-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/bg-22-7797-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 22, issue 23

Research article

|

08 Dec 2025

Research article |

| 08 Dec 2025

Biases in estimated vegetation indices from observations under cloudy conditions

Kevin Wolf, Evelyn Jäkel, André Ehrlich, Michael Schäfer, Hannes Feilhauer, Andreas Huth, and Manfred Wendisch

Data sets

Simulated spectral irradiances, radiances, and vegetation albedo obtained from coupling libRadtran and SCOPE2.0 Kevin Wolf et al. https://doi.org/10.5281/zenodo.15275610

Short summary

This paper presents combined atmosphere-vegetation radiative transfer simulations to systematically investigate cloud-induced biases in remotely sensed vegetation indices (VIs) derived from below-cloud measurements. The biases in VIs have been investigated for the general case of two-band VIs, and for the special cases of the normalized difference vegetation index (NDVI), the normalized difference water index (NDWI), and the enhanced vegetation index (EVI).