Preprints
https://doi.org/10.5194/egusphere-2026-1759
https://doi.org/10.5194/egusphere-2026-1759
09 Apr 2026
 | 09 Apr 2026
Status: this preprint is open for discussion and under review for Biogeosciences (BG).

Assessment of vegetation water dynamics by comparing microwave remote sensing signals from satellites and field-based GNSS reflectometry

Andrew F. Feldman, William K. Smith, Alexandra G. Konings, Martin J. Baur, Marvin Browne, David Chaparro, Charles Devine, Jennifer L. Diehl, Arthur Endsley, Thomas Jagdhuber, Kristine M. Larson, Coral del Mar Valle-Rodriguez, Konstantin Schellenberg, Ruxandra-Maria Zotta, and Shawn P. Serbin

Abstract. Monitoring plant water stress and biomass is limited by labor intensive measurements techniques. Observing plant water conditions more broadly is now enabled by microwave remote sensing. Specifically, satellite-based vegetation optical depth (VOD) provides daily observations of vegetation water volume at tens of kilometers. While satellite VOD has been used for many applications, VOD validations have rarely been carried out. A new method has enabled direct measurements of in-situ VOD, from Global Navigation Satellite Systems (GNSS). However, GNSS measurements have yet to be applied to more globally dominant grasslands and shrublands. Here, we explore how satellite-based VOD from SMAP and AMSR-2 compares with field-based microwave observations from 272 GNSS-based interferometric reflectometry (GNSS-IR) sites across the Western U.S as a part of the Plate Boundary Observatory (PBO) H20 network. These sensors measure a proxy for VOD at a scale of tens of meters, the normalized microwave reflectance index (NMRI). We find that satellite VOD generally positively correlates with GNSS NMRI with correlations between 0.2 to 0.6 across sites. These correlations increase to 0.3 to 0.7 when evaluating sites in regions with low spatial vegetation type heterogeneity, low tree cover, and large seasonal vegetation dynamics. The correlations are higher for X-band VOD, likely related to our finding that both X-band VOD and NMRI are both more sensitive to seasonal vegetation variations than C-band and L-band VOD products. These findings suggest that satellite VOD is capturing field-based GNSS signals in dryland ecosystems, and therefore that these sensors are a critical resource for validating satellite VOD at scale.

Competing interests: Andrew F. Feldman is currently an associate editor of Biogeosciences. The other authors declare that they have no conflict of interest.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
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Andrew F. Feldman, William K. Smith, Alexandra G. Konings, Martin J. Baur, Marvin Browne, David Chaparro, Charles Devine, Jennifer L. Diehl, Arthur Endsley, Thomas Jagdhuber, Kristine M. Larson, Coral del Mar Valle-Rodriguez, Konstantin Schellenberg, Ruxandra-Maria Zotta, and Shawn P. Serbin

Status: open (until 21 May 2026)

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Andrew F. Feldman, William K. Smith, Alexandra G. Konings, Martin J. Baur, Marvin Browne, David Chaparro, Charles Devine, Jennifer L. Diehl, Arthur Endsley, Thomas Jagdhuber, Kristine M. Larson, Coral del Mar Valle-Rodriguez, Konstantin Schellenberg, Ruxandra-Maria Zotta, and Shawn P. Serbin
Andrew F. Feldman, William K. Smith, Alexandra G. Konings, Martin J. Baur, Marvin Browne, David Chaparro, Charles Devine, Jennifer L. Diehl, Arthur Endsley, Thomas Jagdhuber, Kristine M. Larson, Coral del Mar Valle-Rodriguez, Konstantin Schellenberg, Ruxandra-Maria Zotta, and Shawn P. Serbin
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Latest update: 09 Apr 2026
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Short summary
Vegetation water observations from 272 field-based GNSS sensors and satellite-based vegetation optical depth are compared across the western U.S. We find significant positive correlations across the sites and identify common conditions that increase the correlations including less forest cover, more homogeneous vegetation across landscapes, and large seasonal amplitudes. These field-based sensors are thus useful tools to evaluate grass and shrub water stress and validate satellite signals.
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