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Inferring surface currents within submerged, vegetated deltaic islands and wetlands from multi-pass airborne SAR

Ayoub, F. and Jones, C. E. and Lamb, M. P. and Holt, B. and Shaw, J. B. and Mohrig, D. and Wagner, W. (2018) Inferring surface currents within submerged, vegetated deltaic islands and wetlands from multi-pass airborne SAR. Remote Sensing of Environment, 212 . pp. 148-160. ISSN 0034-4257. http://resolver.caltech.edu/CaltechAUTHORS:20180627-111516644

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Abstract

Water flow patterns across coastal and deltaic wetlands affect biogeochemical cycling, denitrification, organic carbon burial, and coastal landscape evolution. Our understanding of such patterns across these important landscapes is incomplete, however, because of the inherent difficulty of conducting spatially and temporally dense ground- or boat-based surveys in shallow, vegetated terrain. We conducted an airborne L-band synthetic aperture radar (SAR) acquisition campaign on Wax Lake Delta, Louisiana, USA, in May 2015, to investigate whether water velocities and flow patterns over kilometer scales can be determined from remote sensing. Thirteen SAR flight lines over the delta region were acquired in 3 h with six different flight directions, concurrently with a small boat campaign. We show that SAR azimuth displacement due to Doppler shift can be used to estimate the surface water flow relative to the static and submerged vegetation interspersed on delta islands, using a simple Bragg wave scattering model and accounting for the Bragg wave's free velocity and wind drift. At Wax Lake Delta, we find that ~0.40 m/s water velocities within the main deltaic channels slow to 0.1–0.2 m/s as flow spreads laterally across, and converges within, the vegetated islands, coinciding with shallow (<0.5 m) depths and heightened flow resistance. This SAR-based technique opens up new avenues for understanding shallow submerged, vegetated coastal wetlands and deltas.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1016/j.rse.2018.04.035DOIArticle
ORCID:
AuthorORCID
Ayoub, F.0000-0002-7389-8400
Lamb, M. P.0000-0002-5701-0504
Additional Information:© 2018 Elsevier Inc. Received 4 October 2017, Revised 1 April 2018, Accepted 19 April 2018, Available online 5 May 2018. The research described in this paper was funded by the California Institute of Technology, and the Jet Propulsion Laboratory, under a contract with the National Aeronautics and Space Administration, and with additional support from a NSF FESD Delta Dynamics Collaboratory grant (EAR-1135427) and a NSF postdoctoral grant (EAR-1250045). The UAVSAR data are courtesy of NASA Jet Propulsion Laboratory/California Institute of Technology and are openly available at https://www.asf.alaska.edu. Raw boat survey data are available for download in Supplementary Material. The authors thank the boat survey crew Daniel D. Duncan, Max S. Daniller-Varghese, and Daniel Aylward, and the UAVSAR team for their help in acquiring these datasets. Mention of trade names or commercial products is not an endorsement or recommendation for use by the U.S. Government.
Funders:
Funding AgencyGrant Number
NASA/JPL/CaltechUNSPECIFIED
NSFEAR-1135427
NSF Postdoctoral FellowshipEAR-1250045
Subject Keywords:Airborne SAR; Doppler shift; Multi-pass SAR; Water surface current; Wetlands; Delta environment
Record Number:CaltechAUTHORS:20180627-111516644
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20180627-111516644
Official Citation:F. Ayoub, C.E. Jones, M.P. Lamb, B. Holt, J.B. Shaw, D. Mohrig, W. Wagner, Inferring surface currents within submerged, vegetated deltaic islands and wetlands from multi-pass airborne SAR, Remote Sensing of Environment, Volume 212, 2018, Pages 148-160, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2018.04.035. (http://www.sciencedirect.com/science/article/pii/S0034425718301913)
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:87397
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:27 Jun 2018 18:40
Last Modified:27 Jun 2018 18:40

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