An Assessment of the Capabilities of GNSS Reflectometry for Dynamic
Monitoring of Wetlands and Inundations
Abstract
The dynamic distribution and change of terrestrial water, manifested in
wetlands that support a wide range of vegetation types and ecosystems,
and also in floodplains that are prone to inundations, are very
important to the understanding of our changing climate and our ability
to mitigate risk. At present all of the existing measurement techniques
have serious limitations in the ability to observe terrestrial water
bodies globally and at the spatial and temporal scales required to fully
capture their dynamics. In the last few years a number of studies in the
community of Global Navigation Satellite Systems (GNSS) Reflectometry
have been focusing on reflections over wetlands and inundated areas
[Zuffada et al, 2016; Nghiem et al, 2017; Chew et al., 2018; Morris et
al., 2019], particularly since data analysis of the CYclone GNSS
(CYGNSS) mission began showing the ability to resolve small-scale land
features such as rivers and bodies of water even partially obstructed by
vegetation. CYGNSS is a constellation of 8 microsatellites, that
provides significantly increased temporal sampling and revisit rate in
the tropical latitudinal band as compared to traditional monolithic
instruments, thus enabling a new observing strategy for capturing
dynamic water events. In [Zuffada et al., 2017; Nghiem et al.,
2017], based on reflected signal characteristics such as peaked
(limited spread in delay and doppler) and symmetric shape, and very high
reflected peak power, it was hypothesized that over wetlands there are
strong coherent specular reflections in the collection area of the
signal, originating from (even small) areas of standing water, resulting
in the measurements’ magnified sensitivity to water because of its high
electric permittivity compared to dry land and/or vegetation. Plots of
peak power, corresponding to CYGNSS measurements’ specular points,
aggregated over a period of time, and displayed over large regions with
complex hydrology such as the Amazon basin clearly showed the potential
of CYGNSS to map surface hydrology of intricate scenes at the
continental level. At the regional scale, availability of in-situ and
other correlative data have led to introduce thresholds in peak power
values that differentiate between two binary states, i.e. dry and wet
associated with inundations [Chew et al., 2018; Morris et al.,
2019]. The limitations of the assumptions used to map wetlands have
been analyzed in [Loria et al., 2019 (in preparation)] and shown to
be traceable to the complex nature of the scattering from inhomogeneous
scenes where the local water topology, surface topography and local
meteorology can affect the mix of coherent and incoherent scattering,
thus producing highly variable peak power that confounds the
measurements. This communication summarizes our best understanding of
the retrieval accuracy of GNSS reflectometry for dynamic monitoring of
wetlands and inundations. It is based on analysis of actual CYGNSS
constellation data acquired over terrestrial water bodiesand discusses
the limitations in estimating surface water globally when
inhomogeneities at the small scales are at play. Comparisons and
cross-validations have been performed with measurements from ALOS-2 and
Sentinel-1 data. References Chew, C., Reager, J.T. and Small, E., 2018.
CYGNSS data map flood inundation during the 2017 Atlantic hurricane
season. Scientific Reports (Nature Publisher Group), 8, pp.1-8. Loria,
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