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Retrieval of nearshore bathymetry from Sentinel-1 SAR data in high energetic wave coasts: The Portuguese case study

2022Journal article Restricted access
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dc.contributor.authorSantos, Diogo
dc.contributor.authorFernández-Fernández, Sandra
dc.contributor.authorAbreu, Tiago
dc.contributor.authorSilva, Paulo A.
dc.contributor.authorBaptista, Paulo
dc.date.accessioned2023-01-24T09:17:58Z
dc.date.embargo2035
dc.date.issued2022
dc.description.abstractThe ability to derive bathymetry using remote sensing techniques enables rapid and cost-efficient mapping of large coastal areas. This contribution focuses on the application of both fast Fourier transform (FFT) and wavelet spectral analysis to obtain satellite-derived bathymetry maps of the nearshore, from freely available and easily accessible Sentinel-1 synthetic aperture radar (SAR) data with 10 m pixel resolution. For this purpose, an extension of 220 km of the Portuguese west coast is analyzed using six satellite images obtained during the years 2018, 2019 and 2020. This extension allows to assess the applicability to coastal sectors with distinct geomorphological constraints. The peak wave periods corresponding to the acquisition of these images approximately range between 11 and 16 s. The spectral analysis is carried to estimate the water depths in near-shore water regions from the observed wavelength patterns. This signature of the sea surface, reflected in the variations of the wavelengths, is captured by the satellite images, making it possible to infer the underlying bathymetry. The bathymetric estimates obtained from both methodologies are compared with data extracted from the Coastal Nautical Charts provided by the Portuguese Hydrographic Institute. Wavelet image processing methodology shows very positive results, particularly extending the depth inversion limits of the FFT methodology, allowing to obtain bathymetric data for the entire shoaling zone where the wavelength patterns are visible. The achieved results also highlight that both FFT and wavelet methodologies are dependent from the seabed slope. For gentle slopes, the inferred depths from 2018 SAR images lead to relative errors between 2.5 and 20% when compared with the observed isobaths (10, 20 and 30 m). For steeper slopes, the errors are generally greater than 20% and increase with depth. The capabilities of the wavelet methodology to map shallow marine environments for high energetic coasts seems promising, regarding research purposes and management interventions.pt_PT
dc.description.sponsorshipThis research was funded by Direção Geral da Política do Mar, through project NAVSAFETY of the Fundo Azul program. Thanks are due to FCT/MCTES for the financial support to CESAM (UIDP/50017/2020+UIDB/50017/2020), through national funds. S.F.-F. was awarded fellowship (BPD/DGEO/7559/2019) by project Space For Shore funded through EOEP-5 Coastal Erosion Program (ESA/AO/1–9219/18/I-LG).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1016/j.rsase.2021.100674pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/21800
dc.language.isoengpt_PT
dc.publisherElsevierpt_PT
dc.relationBPD/DGEO/7559/2019pt_PT
dc.relationCentre for Environmental and Marine Studies
dc.relationCentre for Environmental and Marine Studies
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S235293852100210X?via%3Dihubpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectBathymetry inversionpt_PT
dc.subjectWavelengthpt_PT
dc.subjectFast Fourier transformpt_PT
dc.subjectWavelet transformpt_PT
dc.titleRetrieval of nearshore bathymetry from Sentinel-1 SAR data in high energetic wave coasts: The Portuguese case studypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCentre for Environmental and Marine Studies
oaire.awardTitleCentre for Environmental and Marine Studies
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F50017%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50017%2F2020/PT
oaire.citation.startPage100674pt_PT
oaire.citation.titleRemote Sensing Applications: Society and Environmentpt_PT
oaire.citation.volume25pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameAbreu
person.givenNameTiago
person.identifier1092691
person.identifier.ciencia-id6312-F126-2D6D
person.identifier.orcid0000-0003-3438-3479
person.identifier.ridC-9326-2019
person.identifier.scopus-author-id35745774800
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication.latestForDiscoverye3e5d952-f1be-4cf0-b5d8-b8b1171dbf81
relation.isProjectOfPublicationda57e4e8-cd82-4b95-bdc6-0524b7efb2f9
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