The future of coastal monitoring through satellite remote sensing
Satellite remote sensing is transforming coastal science from a “data-poor” field into a “data-rich” field. Sandy beaches are dynamic landscapes that change in response to long-term pressures, short-term pulses, and anthropogenic interventions. Until recently, the rate and breadth of beach change ha...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Cambridge University Press
2023-01-01
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| Series: | Cambridge Prisms: Coastal Futures |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S275472052200004X/type/journal_article |
| _version_ | 1827949278445699072 |
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| author | Sean Vitousek Daniel Buscombe Kilian Vos Patrick L. Barnard Andrew C. Ritchie Jonathan A. Warrick |
| author_facet | Sean Vitousek Daniel Buscombe Kilian Vos Patrick L. Barnard Andrew C. Ritchie Jonathan A. Warrick |
| author_sort | Sean Vitousek |
| collection | DOAJ |
| description | Satellite remote sensing is transforming coastal science from a “data-poor” field into a “data-rich” field. Sandy beaches are dynamic landscapes that change in response to long-term pressures, short-term pulses, and anthropogenic interventions. Until recently, the rate and breadth of beach change have outpaced our ability to monitor those changes, due to the spatiotemporal limitations of our observational capacity. Over the past several decades, only a handful of beaches worldwide have been regularly monitored with accurate yet expensive in situ surveys. The long-term coastal-change data of these few well-monitored beaches have led to in-depth understanding of many site-specific coastal processes. However, because the best-monitored beaches are not representative of all beaches, much remains unknown about the processes and fate of the other >99% of unmonitored beaches worldwide. The fleet of Earth-observing satellites has enabled multiscale monitoring of beaches, for the very first time, by providing imagery with global coverage and up to daily frequency. The long-standing and ever-expanding archive of satellite imagery will enable coastal scientists to investigate coastal change at sites vulnerable to future sea-level rise, that is, (almost) everywhere. In the past decade, our capability to observe coastal change from space has grown substantially with computing and algorithmic power. Yet, further advances are needed in automating monitoring using machine learning, deep learning, and computer vision to fully leverage this massive treasure trove of data. Extensive monitoring and investigation of the causes and effects of coastal change at the requisite spatiotemporal scales will provide coastal managers with additional, valuable information to evaluate problems and solutions, addressing the potential for widespread beach loss due to accelerated sea-level rise, development, and reduced sediment supply. Monitoring from Earth-observing satellites is currently the only means of providing seamless data with high spatiotemporal resolution at the global scale of the impending impacts of climate change on coastal systems. |
| first_indexed | 2024-04-09T13:07:55Z |
| format | Article |
| id | doaj.art-54759061fb394d36a808288618086e71 |
| institution | Directory Open Access Journal |
| issn | 2754-7205 |
| language | English |
| last_indexed | 2024-04-09T13:07:55Z |
| publishDate | 2023-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Cambridge Prisms: Coastal Futures |
| spelling | doaj.art-54759061fb394d36a808288618086e712023-05-12T11:18:20ZengCambridge University PressCambridge Prisms: Coastal Futures2754-72052023-01-01110.1017/cft.2022.4The future of coastal monitoring through satellite remote sensingSean Vitousek0https://orcid.org/0000-0002-3369-4673Daniel Buscombe1https://orcid.org/0000-0001-6217-5584Kilian Vos2https://orcid.org/0000-0002-9518-1582Patrick L. Barnard3https://orcid.org/0000-0003-1414-6476Andrew C. Ritchie4https://orcid.org/0000-0001-5826-9983Jonathan A. Warrick5https://orcid.org/0000-0002-0205-3814Pacific Coastal and Marine Science Center, U.S. Geological Survey, Santa Cruz, CA, USA Department of Civil, Materials, and Environmental Engineering, University of Illinois Chicago, Chicago, IL, USAMarda Science, Contracted to Pacific Coastal and Marine Science Center, U.S. Geological Survey, Santa Cruz, CA, USAWater Research Laboratory, University of New South Wales, Sydney, NSW, AustraliaPacific Coastal and Marine Science Center, U.S. Geological Survey, Santa Cruz, CA, USAPacific Coastal and Marine Science Center, U.S. Geological Survey, Santa Cruz, CA, USAPacific Coastal and Marine Science Center, U.S. Geological Survey, Santa Cruz, CA, USASatellite remote sensing is transforming coastal science from a “data-poor” field into a “data-rich” field. Sandy beaches are dynamic landscapes that change in response to long-term pressures, short-term pulses, and anthropogenic interventions. Until recently, the rate and breadth of beach change have outpaced our ability to monitor those changes, due to the spatiotemporal limitations of our observational capacity. Over the past several decades, only a handful of beaches worldwide have been regularly monitored with accurate yet expensive in situ surveys. The long-term coastal-change data of these few well-monitored beaches have led to in-depth understanding of many site-specific coastal processes. However, because the best-monitored beaches are not representative of all beaches, much remains unknown about the processes and fate of the other >99% of unmonitored beaches worldwide. The fleet of Earth-observing satellites has enabled multiscale monitoring of beaches, for the very first time, by providing imagery with global coverage and up to daily frequency. The long-standing and ever-expanding archive of satellite imagery will enable coastal scientists to investigate coastal change at sites vulnerable to future sea-level rise, that is, (almost) everywhere. In the past decade, our capability to observe coastal change from space has grown substantially with computing and algorithmic power. Yet, further advances are needed in automating monitoring using machine learning, deep learning, and computer vision to fully leverage this massive treasure trove of data. Extensive monitoring and investigation of the causes and effects of coastal change at the requisite spatiotemporal scales will provide coastal managers with additional, valuable information to evaluate problems and solutions, addressing the potential for widespread beach loss due to accelerated sea-level rise, development, and reduced sediment supply. Monitoring from Earth-observing satellites is currently the only means of providing seamless data with high spatiotemporal resolution at the global scale of the impending impacts of climate change on coastal systems.https://www.cambridge.org/core/product/identifier/S275472052200004X/type/journal_articleCoastal monitoringShoreline changeMachine learningBeach erosionremote sensing |
| spellingShingle | Sean Vitousek Daniel Buscombe Kilian Vos Patrick L. Barnard Andrew C. Ritchie Jonathan A. Warrick The future of coastal monitoring through satellite remote sensing Cambridge Prisms: Coastal Futures Coastal monitoring Shoreline change Machine learning Beach erosion remote sensing |
| title | The future of coastal monitoring through satellite remote sensing |
| title_full | The future of coastal monitoring through satellite remote sensing |
| title_fullStr | The future of coastal monitoring through satellite remote sensing |
| title_full_unstemmed | The future of coastal monitoring through satellite remote sensing |
| title_short | The future of coastal monitoring through satellite remote sensing |
| title_sort | future of coastal monitoring through satellite remote sensing |
| topic | Coastal monitoring Shoreline change Machine learning Beach erosion remote sensing |
| url | https://www.cambridge.org/core/product/identifier/S275472052200004X/type/journal_article |
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