the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Assessment of vegetation water dynamics by comparing microwave remote sensing signals from satellites and field-based GNSS reflectometry
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.- Preprint
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- RC1: 'Comment on egusphere-2026-1759', Anonymous Referee #1, 11 May 2026 reply
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- 1
Title: Assessment of vegetation water dynamics by comparing microwave
remote sensing signals from satellites and field-based GNSS
reflectometry
Authors: Feldman, A. F., et al.
Summary:
This study compares satellite-based vegetation optical depth (VOD)
with field-based measurements of VOD using GNSS-IR techniques. Â There
is a lot of information within this paper; different wavelengths and
algorithms are used to calculate VOD. Â Overall, I think the manuscript
is well-written, the presentation is clear, and the figures
appropriate. Â This manuscript seems appropriate for Biogeosciences.
This seems like a study where a lot of data are collected and analyzed
and then one sees what comes out of it (this is not necessarily a bad
starting point, and it is done well, but correlations of 0.2 or 0.3
are not great and some deeper understanding of why those particular
sites have such low/poor correlations is needed). Â Not being an expert
in satellite measurements, there are a lot of acronyms and terms which
I was not readily familiar with. Â With that said, my comments (listed
below) should probably be considered as comments from a "non-expert"
so please take them (or leave them) as you like.
Â
Major Comments/Questions:
1. Â There is a lot of emphasis on correlations. Â As a non-expert, I do
not have a good feel for what these correlations actually look like
(ie, I assume one can generate a x-y scatter plot between two
different measurements). Â Using Fig. 1 as a specific example, it seems
surprising how some sites have relationships with a strongly positive
correlation and others have a negative one (ie, Fig. 1E). Â What does a
scatter plot from strongly positive and negative correlations actually
look like? Â Maybe I missed it, but is there something distinctive that
leads to the negative correlations?
2. There is a lot of pre-processing that is described, but not shown.
One that seems like it would be useful for the reader to see is the
different seasonal time series for NMRI and VOD. Â As described in
Sect. 2.3, this analysis is looking at differences from the seasonal
cycle...this is fine, but it would be great to also see the actual
seasonal cycle so one can see things like: how large the peak is
relative to the rest of the year, how the timing change year-to-year,
etc.
3. Is the linear fit in Figs. 3B and C really significant? Â It seems
like there is a LOT of scatter in these plots.
4. For capturing the wetting and drying associated with individual
rainfall events---if the objective is to capture anything like
"interception on the leaf surfaces", the a 1-day temporal resolution
is going to be an issue. Â Precipitation intercepted by the vegetation
will be evaporated within a day. Â So, it seems like the daily
resolution of this analysis will miss any shorter-term (ie, hourly
scale) precipitation/evaporation effects. Â I realize this is likely
known by the authors and part of the discussion in Sect. 3.5.2 about
the lack of a clear "pulse" signal in Fig. 7.
Minor Comments:
* l.50, provide the specific name of the indices being referred to?
* l.96, remove "Nevertheless"
* l.167, Eq.1 does the "max" refer to a max over a certain time
 period?  Or, something else?
* l.204-205, how are "short statured" and "dense short statured"
 vegetation distinguished from each other?  What is the height
 cut-off to make the vegetation "short"?  Is a grassland considered a
 "cropland"?  More clear definitions would be helpful.
* l.253, why are you referring back to Section 2.2?
* l.255, is a 16-day value useful?
* l.371, can examples of the situation where the GNSS site is in a
 non-forested area, but the satellite pixel has a forest be
 explicitly explored/shown?
* l.523, is the peak in soil moisture expected to be before the peak
 of VOD?
* l.531, what do you mean by "physical representation differences"?
* how dramatic are the seasonal peaks? Â Example time series that show
 the actual annual cycle?
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