Coastal sediment grain size estimates on gravel beaches using Satellite Synthetic Aperture Radar (SAR)

Mann, Sophie; Novellino, Alessandro; Hussain, Ekbal; Grebby, Stephen; Bateson, Luke; Capsey, Austin; Marsh, Stuart. 2024 Coastal sediment grain size estimates on gravel beaches using Satellite Synthetic Aperture Radar (SAR). Remote Sensing, 16 (10), 1763. https://doi.org/10.3390/rs16101763

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Official URL: http://dx.doi.org/10.3390/rs16101763

Abstract/Summary

first_page settings Order Article Reprints Open AccessArticle Coastal Sediment Grain Size Estimates on Gravel Beaches Using Satellite Synthetic Aperture Radar (SAR) by Sophie Mann 1,* [ORCID] , Alessandro Novellino 2 [ORCID] , Ekbal Hussain 2 [ORCID] , Stephen Grebby 1 [ORCID] , Luke Bateson 2 [ORCID] , Austin Capsey 3 and Stuart Marsh 1 [ORCID] 1 Nottingham Geospatial Insitute, University of Nottingham, Triumph Road, Nottingham NG7 2TU, UK 2 British Geological Survey, Nicker Hill, Keyworth, Nottingham NG12 5GG, UK 3 UK Hydrographic Office, Admiralty Way, Taunton TA1 2DN, UK * Author to whom correspondence should be addressed. Remote Sens. 2024, 16(10), 1763; https://doi.org/10.3390/rs16101763 Submission received: 10 April 2024 / Revised: 1 May 2024 / Accepted: 11 May 2024 / Published: 16 May 2024 (This article belongs to the Special Issue Coastal and Littoral Observation Using Remote Sensing) Download keyboard_arrow_down Browse Figures Versions Notes Abstract Coastal sediment grain size is an important factor in determining coastal morphodynamics. In this study, we explore a novel approach for retrieving the median sediment grain size (D50) of gravel-dominated beaches using Synthetic Aperture Radar (SAR) spaceborne imagery. We assessed this by using thirty-six Sentinel-1 (C-band SAR) satellite images acquired in May and June 2022 and 2023, and three NovaSAR (S-band SAR) satellite images acquired in May and June 2022, for three different training sites and one test site across England (the UK). The results from the Sentinel-1 C-band data show strong positive correlations (R2≥0.75 ) between the D50 and the backscatter coefficients for 15/18 of the resultant models. The models were subsequently used to derive predictions of D50 for the test site, with the models which exhibited the strongest correlations resulting in Mean Absolute Errors (MAEs) in the range 2.26–5.47 mm. No correlation (R2 = 0.04) was found between the backscatter coefficients from the S-band NovaSAR data and D50. These results highlight the potential to derive near-real time estimates of coastal sediment grain size for gravel beaches to better inform coastal erosion and monitoring programs.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.3390/rs16101763
ISSN:	2072-4292
Date made live:	26 Jun 2024 11:12 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/537636

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.3390/rs16101763

ISSN:

2072-4292

Date made live:

26 Jun 2024 11:12 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/537636