Long-Term Wetland Monitoring Using the Landsat Archive: A Review
Wetlands, which provide multiple functions and ecosystem services, have decreased and been degraded worldwide for several decades due to human activities and climate change. Managers and scientists need tools to characterize and monitor wetland areas, structure, and functions in the long term and at...
| Главные авторы: | , , , |
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| Формат: | Статья |
| Язык: | English |
| Опубликовано: |
MDPI AG
2023-01-01
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| Серии: | Remote Sensing |
| Предметы: | |
| Online-ссылка: | https://www.mdpi.com/2072-4292/15/3/820 |
| _version_ | 1827759578873331712 |
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| author | Quentin Demarquet Sébastien Rapinel Simon Dufour Laurence Hubert-Moy |
| author_facet | Quentin Demarquet Sébastien Rapinel Simon Dufour Laurence Hubert-Moy |
| author_sort | Quentin Demarquet |
| collection | DOAJ |
| description | Wetlands, which provide multiple functions and ecosystem services, have decreased and been degraded worldwide for several decades due to human activities and climate change. Managers and scientists need tools to characterize and monitor wetland areas, structure, and functions in the long term and at regional and global scales and assess the effects of planning policies on their conservation status. The Landsat earth observation program has collected satellite images since 1972, which makes it the longest global earth observation record with respect to remote sensing. In this review, we describe how Landsat data have been used for long-term (≥20 years) wetland monitoring. A total of 351 articles were analyzed based on 5 topics and 22 attributes that address long-term wetland monitoring and Landsat data analysis issues. Results showed that (1) the open access Landsat archive successfully highlights changes in wetland areas, structure, and functions worldwide; (2) recent progress in artificial intelligence (AI) and machine learning opens new prospects for analyzing the Landsat archive; (3) most unexplored wetlands can be investigated using the Landsat archive; (4) new cloud-computing tools enable dense Landsat times-series to be processed over large areas. We recommend that future studies focus on changes in wetland functions using AI methods along with cloud computing. This review did not include reports and articles that do not mention the use of Landsat imagery. |
| first_indexed | 2024-03-11T09:27:40Z |
| format | Article |
| id | doaj.art-b2d7a82456894015baad4cf5d702ab00 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T09:27:40Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-b2d7a82456894015baad4cf5d702ab002023-11-16T17:54:43ZengMDPI AGRemote Sensing2072-42922023-01-0115382010.3390/rs15030820Long-Term Wetland Monitoring Using the Landsat Archive: A ReviewQuentin Demarquet0Sébastien Rapinel1Simon Dufour2Laurence Hubert-Moy3Place du Recteur Henri Le Moal, LETG UMR 6554 CNRS, University of Rennes, 35000 Rennes, FrancePlace du Recteur Henri Le Moal, LETG UMR 6554 CNRS, University of Rennes, 35000 Rennes, FrancePlace du Recteur Henri Le Moal, LETG UMR 6554 CNRS, University of Rennes, 35000 Rennes, FrancePlace du Recteur Henri Le Moal, LETG UMR 6554 CNRS, University of Rennes, 35000 Rennes, FranceWetlands, which provide multiple functions and ecosystem services, have decreased and been degraded worldwide for several decades due to human activities and climate change. Managers and scientists need tools to characterize and monitor wetland areas, structure, and functions in the long term and at regional and global scales and assess the effects of planning policies on their conservation status. The Landsat earth observation program has collected satellite images since 1972, which makes it the longest global earth observation record with respect to remote sensing. In this review, we describe how Landsat data have been used for long-term (≥20 years) wetland monitoring. A total of 351 articles were analyzed based on 5 topics and 22 attributes that address long-term wetland monitoring and Landsat data analysis issues. Results showed that (1) the open access Landsat archive successfully highlights changes in wetland areas, structure, and functions worldwide; (2) recent progress in artificial intelligence (AI) and machine learning opens new prospects for analyzing the Landsat archive; (3) most unexplored wetlands can be investigated using the Landsat archive; (4) new cloud-computing tools enable dense Landsat times-series to be processed over large areas. We recommend that future studies focus on changes in wetland functions using AI methods along with cloud computing. This review did not include reports and articles that do not mention the use of Landsat imagery.https://www.mdpi.com/2072-4292/15/3/820ecosystem servicesLandsattime seriesartificial intelligencemachine learningcloud-computing |
| spellingShingle | Quentin Demarquet Sébastien Rapinel Simon Dufour Laurence Hubert-Moy Long-Term Wetland Monitoring Using the Landsat Archive: A Review Remote Sensing ecosystem services Landsat time series artificial intelligence machine learning cloud-computing |
| title | Long-Term Wetland Monitoring Using the Landsat Archive: A Review |
| title_full | Long-Term Wetland Monitoring Using the Landsat Archive: A Review |
| title_fullStr | Long-Term Wetland Monitoring Using the Landsat Archive: A Review |
| title_full_unstemmed | Long-Term Wetland Monitoring Using the Landsat Archive: A Review |
| title_short | Long-Term Wetland Monitoring Using the Landsat Archive: A Review |
| title_sort | long term wetland monitoring using the landsat archive a review |
| topic | ecosystem services Landsat time series artificial intelligence machine learning cloud-computing |
| url | https://www.mdpi.com/2072-4292/15/3/820 |
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