Automated Mapping of the Freshwater Ecosystem Functional Groups of the International Union for Conservation of Nature Global Ecosystem Typology in a Large Region of Arid Australia
The classification of freshwater ecosystems is essential for effective biodiversity conservation and ecosystem management, particularly with increasing threats. We developed an automated approach to mapping and classifying freshwater ecosystem functional groups based on the IUCN Global Ecosystem Typ...
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| Language: | English |
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MDPI AG
2025-04-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/9/1488 |
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| author | Roxane J. Francis Hedley S. Grantham David A. Keith Jose R. Ferrer-Paris Richard T. Kingsford |
| author_facet | Roxane J. Francis Hedley S. Grantham David A. Keith Jose R. Ferrer-Paris Richard T. Kingsford |
| author_sort | Roxane J. Francis |
| collection | DOAJ |
| description | The classification of freshwater ecosystems is essential for effective biodiversity conservation and ecosystem management, particularly with increasing threats. We developed an automated approach to mapping and classifying freshwater ecosystem functional groups based on the IUCN Global Ecosystem Typology (GET), offering a scalable, dynamic and efficient alternative to current manual methods. Our method leveraged remote sensing data and thresholding algorithms to classify ecosystems into distinct ecosystem functional groups, accounting for challenges such as the temporal and spatial complexities of dynamic freshwater ecosystems and inconsistencies in manual classification. Unlike traditional approaches, which rely on manual cross-referencing to adapt existing maps and contain subjective biases, our system is repeatable, transparent and adaptable to new incoming satellite data. We demonstrate the applicability of this method in the Paroo–Warrego region of Australia (~14,000,000 ha), highlighting the automated classification’s capacity to process large areas with diverse ecosystems. Although some functional groups require static datasets due to current limitations in satellite data, the overall approach had high accuracy (84%). This work provides a foundation for future applications to other freshwater ecosystems around the world, underpinning biodiversity management, monitoring and reporting worldwide. |
| format | Article |
| id | doaj-art-e0d0cab6deac42e0b354d00d02ebaaed |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-e0d0cab6deac42e0b354d00d02ebaaed2025-08-20T01:49:24ZengMDPI AGRemote Sensing2072-42922025-04-01179148810.3390/rs17091488Automated Mapping of the Freshwater Ecosystem Functional Groups of the International Union for Conservation of Nature Global Ecosystem Typology in a Large Region of Arid AustraliaRoxane J. Francis0Hedley S. Grantham1David A. Keith2Jose R. Ferrer-Paris3Richard T. Kingsford4Centre for Ecosystem Science, School of Biological Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, AustraliaCentre for Ecosystem Science, School of Biological Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, AustraliaCentre for Ecosystem Science, School of Biological Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, AustraliaCentre for Ecosystem Science, School of Biological Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, AustraliaCentre for Ecosystem Science, School of Biological Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, AustraliaThe classification of freshwater ecosystems is essential for effective biodiversity conservation and ecosystem management, particularly with increasing threats. We developed an automated approach to mapping and classifying freshwater ecosystem functional groups based on the IUCN Global Ecosystem Typology (GET), offering a scalable, dynamic and efficient alternative to current manual methods. Our method leveraged remote sensing data and thresholding algorithms to classify ecosystems into distinct ecosystem functional groups, accounting for challenges such as the temporal and spatial complexities of dynamic freshwater ecosystems and inconsistencies in manual classification. Unlike traditional approaches, which rely on manual cross-referencing to adapt existing maps and contain subjective biases, our system is repeatable, transparent and adaptable to new incoming satellite data. We demonstrate the applicability of this method in the Paroo–Warrego region of Australia (~14,000,000 ha), highlighting the automated classification’s capacity to process large areas with diverse ecosystems. Although some functional groups require static datasets due to current limitations in satellite data, the overall approach had high accuracy (84%). This work provides a foundation for future applications to other freshwater ecosystems around the world, underpinning biodiversity management, monitoring and reporting worldwide.https://www.mdpi.com/2072-4292/17/9/1488remote sensingsatelliteinundationglobalpolicywetlands |
| spellingShingle | Roxane J. Francis Hedley S. Grantham David A. Keith Jose R. Ferrer-Paris Richard T. Kingsford Automated Mapping of the Freshwater Ecosystem Functional Groups of the International Union for Conservation of Nature Global Ecosystem Typology in a Large Region of Arid Australia Remote Sensing remote sensing satellite inundation global policy wetlands |
| title | Automated Mapping of the Freshwater Ecosystem Functional Groups of the International Union for Conservation of Nature Global Ecosystem Typology in a Large Region of Arid Australia |
| title_full | Automated Mapping of the Freshwater Ecosystem Functional Groups of the International Union for Conservation of Nature Global Ecosystem Typology in a Large Region of Arid Australia |
| title_fullStr | Automated Mapping of the Freshwater Ecosystem Functional Groups of the International Union for Conservation of Nature Global Ecosystem Typology in a Large Region of Arid Australia |
| title_full_unstemmed | Automated Mapping of the Freshwater Ecosystem Functional Groups of the International Union for Conservation of Nature Global Ecosystem Typology in a Large Region of Arid Australia |
| title_short | Automated Mapping of the Freshwater Ecosystem Functional Groups of the International Union for Conservation of Nature Global Ecosystem Typology in a Large Region of Arid Australia |
| title_sort | automated mapping of the freshwater ecosystem functional groups of the international union for conservation of nature global ecosystem typology in a large region of arid australia |
| topic | remote sensing satellite inundation global policy wetlands |
| url | https://www.mdpi.com/2072-4292/17/9/1488 |
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