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An Assessment of the Capabilities of GNSS Reflectometry for Dynamic Monitoring of Wetlands and Inundations
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  • Cinzia Zuffada,
  • Brandi Downs,
  • Marco Lavalle,
  • Eric Loria,
  • Mary Morris,
  • Andrew O'Brien,
  • Ilaria Russo,
  • Valery Zavorotny
Cinzia Zuffada
Jet Propulsion Laboratory

Corresponding Author:cinzia.zuffada@jpl.nasa.gov

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Brandi Downs
Ohio State University Main Campus
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Marco Lavalle
Jet Propulsion Laboratory
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Eric Loria
Ohio State University Main Campus
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Mary Morris
Jet Propulsion Laboratory
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Andrew O'Brien
Ohio State University Main Campus
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Ilaria Russo
University' del Sannio
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Valery Zavorotny
NOAA/OAR/ESRL (retired)
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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, E. et al. Analysis of Wetland Extent Retrieval Accuracy Using CYGNSS Data. In preparation, 2019. Morris, M., C. Chew, J.T. Reager, R. Shah, C. Zuffada. A Novel Approach to Monitoring Wetland Dynamics using CYGNSS: Everglades Case Study. Remote Sensing of Environment, in press. 2019. Nghiem SV, Zuffada C, Shah R, Chew C, Lowe ST, Mannucci AJ, Cardellach E, Brakenridge GR, Geller G, Rosenqvist A. Wetland monitoring with Global Navigation Satellite System reflectometry. Earth and Space Science. 2017 Jan 1;4(1):16-39. Zuffada, C., Chew, C., Nghiem, S.V., Shah, R., Podest, E., Bloom, A.A., Koning, A., Small, E., Schimel, D., Reager, J.T. and Mannucci, A., 2016, August. Advancing Wetlands Mapping and Monitoring with GNSS Reflectometry. In Living Planet Symposium (Vol. 740, p. 83). Zuffada, C., Chew, C. and Nghiem, S.V., 2017. GNSS-R algorithms for wetlands observations. In IGARSS 2017-2017 IEEE International Geoscience and Remote Sensing Symposium (pp. 1126 – 1129), Fort Worth, TX.