Synergy of Satellite Remote Sensing and Numerical Ocean Modelling for Coastal Geomorphology Diagnosis
Sediment dynamics is the primary driver of the evolution of the coastal geomorphology and of the underwater shelf clinoforms. In this paper, we focus on mesoscale and sub-mesoscale processes, such as coastal currents and river plumes, and how they shape the sediment dynamics at regional or basin spa...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-11-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/11/22/2636 |
| _version_ | 1798018554667204608 |
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| author | Mario Benincasa Federico Falcini Claudia Adduce Gianmaria Sannino Rosalia Santoleri |
| author_facet | Mario Benincasa Federico Falcini Claudia Adduce Gianmaria Sannino Rosalia Santoleri |
| author_sort | Mario Benincasa |
| collection | DOAJ |
| description | Sediment dynamics is the primary driver of the evolution of the coastal geomorphology and of the underwater shelf clinoforms. In this paper, we focus on mesoscale and sub-mesoscale processes, such as coastal currents and river plumes, and how they shape the sediment dynamics at regional or basin spatial scales. A new methodology is developed that combines observational data with numerical modelling: the aim is to pair satellite measurements of suspended sediment with velocity fields from numerical oceanographic models, to obtain an estimation of the sediment flux. A numerical divergence of this flux is then computed. The divergence field thus obtained shows how the aforementioned mesoscale processes distribute the sediments. The approach was applied and discussed on the Adriatic Sea, for the winter of 2012, using data provided by the ESA Coastcolour project and the output of a run of the MIT General Circulation Model. |
| first_indexed | 2024-04-11T16:24:50Z |
| format | Article |
| id | doaj.art-c9784017897649348b3c75894a049491 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-04-11T16:24:50Z |
| publishDate | 2019-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-c9784017897649348b3c75894a0494912022-12-22T04:14:12ZengMDPI AGRemote Sensing2072-42922019-11-011122263610.3390/rs11222636rs11222636Synergy of Satellite Remote Sensing and Numerical Ocean Modelling for Coastal Geomorphology DiagnosisMario Benincasa0Federico Falcini1Claudia Adduce2Gianmaria Sannino3Rosalia Santoleri4CNR-ISMAR, Institute of Marine Sciences, National Research Council, 00133 Rome, ItalyCNR-ISMAR, Institute of Marine Sciences, National Research Council, 00133 Rome, ItalyDepartment of Engineering, Roma Tre University, 00146 Rome, ItalyENEA—Climate Modelling and Impacts Laboratory, 00060 Rome, ItalyCNR-ISMAR, Institute of Marine Sciences, National Research Council, 00133 Rome, ItalySediment dynamics is the primary driver of the evolution of the coastal geomorphology and of the underwater shelf clinoforms. In this paper, we focus on mesoscale and sub-mesoscale processes, such as coastal currents and river plumes, and how they shape the sediment dynamics at regional or basin spatial scales. A new methodology is developed that combines observational data with numerical modelling: the aim is to pair satellite measurements of suspended sediment with velocity fields from numerical oceanographic models, to obtain an estimation of the sediment flux. A numerical divergence of this flux is then computed. The divergence field thus obtained shows how the aforementioned mesoscale processes distribute the sediments. The approach was applied and discussed on the Adriatic Sea, for the winter of 2012, using data provided by the ESA Coastcolour project and the output of a run of the MIT General Circulation Model.https://www.mdpi.com/2072-4292/11/22/2636remote sensingsatellitesediment transportcoastal geomorphology |
| spellingShingle | Mario Benincasa Federico Falcini Claudia Adduce Gianmaria Sannino Rosalia Santoleri Synergy of Satellite Remote Sensing and Numerical Ocean Modelling for Coastal Geomorphology Diagnosis Remote Sensing remote sensing satellite sediment transport coastal geomorphology |
| title | Synergy of Satellite Remote Sensing and Numerical Ocean Modelling for Coastal Geomorphology Diagnosis |
| title_full | Synergy of Satellite Remote Sensing and Numerical Ocean Modelling for Coastal Geomorphology Diagnosis |
| title_fullStr | Synergy of Satellite Remote Sensing and Numerical Ocean Modelling for Coastal Geomorphology Diagnosis |
| title_full_unstemmed | Synergy of Satellite Remote Sensing and Numerical Ocean Modelling for Coastal Geomorphology Diagnosis |
| title_short | Synergy of Satellite Remote Sensing and Numerical Ocean Modelling for Coastal Geomorphology Diagnosis |
| title_sort | synergy of satellite remote sensing and numerical ocean modelling for coastal geomorphology diagnosis |
| topic | remote sensing satellite sediment transport coastal geomorphology |
| url | https://www.mdpi.com/2072-4292/11/22/2636 |
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