EGU26-14360, updated on 14 Mar 2026
https://doi.org/10.5194/egusphere-egu26-14360
EGU General Assembly 2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Tuesday, 05 May, 17:40–17:50 (CEST)
 
Room 2.95
Assessing dual-channel multi-year active microwave-based vegetation optical depth in temperate forest ecosystems
Florian M. Hellwig1,2, Anke Fluhrer2, Konstantin Schellenberg3,4,2, Paul Vermunt5, Benjamin Lecart6, François Jonard6, Markus Zehner3, Thomas Weiß7, David Chaparro8, Clémence Dubois9, Moritz Link10, Jan Bliefernicht1, Harald Kunstmann1,11, and Thomas Jagdhuber2,1
Florian M. Hellwig et al.
  • 1University of Augsburg, Institute of Geography, Department of Regional Climate and Hydrology, Augsburg, Germany (florian.hellwig@uni-a.de)
  • 2German Aerospace Center (DLR), Microwaves and Radar Institute, Wessling, Germany
  • 3Max-Planck Institute for Biogeochemistry, Department of Biogeochemical Processes, Jena, Germany
  • 4Friedrich Schiller University Jena, Department for Earth Observation, Jena, Germany
  • 5University of Twente, Enschede, Netherlands
  • 6University of Liège, Department of Geography, Liège, Belgium
  • 7University of Rostock, Geodesy and Geoinformatics, Rostock, Germany
  • 8Centre for Ecological Research and Forestry Applications (CREAF), Cerdanyola del Vallès, Spain
  • 9German Aerospace Center (DLR), Institute of Data Science, Jena, Germany
  • 10University of Valencia, Image Processing Laboratory (IPL), Valencia, Spain
  • 11Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany

Forest water dynamics can be assessed on large spatio-temporal scales using satellite-based remote sensing. Vegetation optical depth (VOD), which indicates the vegetation's attenuation of microwaves, contains mainly information on the dry biomass, structure, and water content of the vegetation. Water dynamics can be reflected in short-term variations in VOD. Currently, VOD is operationally retrieved using passive microwave sensors, such as AMSR-2, SMAP, and SMOS, or radar-based sensors, such as ASCAT, with a coarse spatial resolution (tens of kilometers), which hinders the understanding of complex landscapes and is a major obstacle for VOD validation using ground sensors. To overcome this shortcoming of spatial resolution, we utilize synthetic aperture radar (SAR) sensors, such as Copernicus Sentinel-1 (S1) C-band (5.504 GHz), which enables a much higher spatial resolution (tens of meters).

This study aims to estimate spatially high-resolution SAR-based VOD across different forest ecosystems, using both VH and VV polarizations, and ultimately assess forest water dynamics. We employ soil and vegetation physical scattering models (De Roo et al., 2001; Ulaby & Long, 2014) and constrain the effective scattering albedo (ω), which indicates the ratio of scattering to absorption of vegetation. In our dual-channel approach, we utilize in situ soil moisture from forest ecological observatories and co-polarized S1 backscatter as direct model inputs, and characterize the vegetation structure (ω) using cross-polarized S1 backscatter to estimate SAR-based VOD. We test our approach across two deciduous broadleaf and three evergreen needleleaf forest ecosystems in Central Europe for up to three years (2023-2025). In addition, we compare our SAR-based VOD with VOD estimates from Global Navigation Satellite System-Transmissometry (GNSS-T), derived from a pair of in situ receivers: one located at the top of the canopy and one on the ground for each test site (Brede et al., 2025). We validate our approach using in situ plant gravimetric moisture content (mg; [kgwater/kgwet biomass]) measurements of the tree canopy and remote sensing-based leaf area index. We will also transfer our dual-channel approach to the agricultural site of the Land-Atmosphere Feedback Initiative (LAFI) and other ecosystems in a later step. In the end, spatially high-resolution satellite-based SAR-based VOD enables not only analyses of forest water dynamics but also small-scale up to stand-based assessments of plant hydraulics.

 

References

Brede, B., Schellenberg, K., Camps, A., Chaparro, D., Damm, A., Forkel, M., Frankenberg, C., Ghosh, A., Hartmann, H., Herold, M., Humphrey, V., Jagdhuber, T., Konings, A., Kurum, M., Niederberger, M., Schmullius, C., Stassin, T., Steele-Dunne, S., Borght, N., …, Jonard, F. (2025). VODnet: a virtual GNSS-T VOD network for monitoring of forest water budget and structure. https://doi.org/10.13140/RG.2.2.17146.35522.

De Roo, R. D., Du, Y., Ulaby, F. T., Dobson, M. C. (2001). A semi-empirical backscattering model at L-band and C-band for a soybean canopy with soil moisture inversion. IEEE Transactions on Geoscience and Remote Sensing, 39(4), 864–872. https://doi.org/10.1109/36.917912.

Ulaby, F. T., Long, D. G. (2014). Microwave radar and radiometric remote sensing. University of Michigan Press.

How to cite: Hellwig, F. M., Fluhrer, A., Schellenberg, K., Vermunt, P., Lecart, B., Jonard, F., Zehner, M., Weiß, T., Chaparro, D., Dubois, C., Link, M., Bliefernicht, J., Kunstmann, H., and Jagdhuber, T.: Assessing dual-channel multi-year active microwave-based vegetation optical depth in temperate forest ecosystems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14360, https://doi.org/10.5194/egusphere-egu26-14360, 2026.