Bathymetry-guided multi-source remote sensing image domain adaptive coral reef benthic habitat classification Article Swipe
Hui Chen
,
Liang Cheng
,
Zhang Ka
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1080/15481603.2025.2471193
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1080/15481603.2025.2471193
Coral reefs are among the most complex and biodiverse ecosystems on Earth, providing immense ecological, economic, and social value. They offer critical habitats, support fisheries and tourism, and play a key role in coastal protection. However, global climate change, overfishing, and pollution have severely threatened their survival. Therefore, accurate classification and monitoring of coral reef benthic habitats (CRBH) are essential for understanding ecosystem health and developing effective conservation strategies. Due to the complexity of marine environments, multi-source remote sensing images often exhibit significant domain shifts caused by differences in imaging conditions and platform orientations, posing challenges to the generalization of substrate classification models. To address this issue, we propose a computationally efficient Bathymetry-Guided Domain Adaptation (BGDA) method. By leveraging the domain-invariant properties of bathymetric data, the BGDA method learns the styles and cross-domain spatial relationships of CRBH under bathymetric guidance, thereby achieving cross-domain consistency and significantly enhancing the performance of unsupervised domain-adaptive substrate classification. A domain-adaptive CRBH classification dataset was constructed using Sentinel-2, PlanetScope, and Gaofen-2 satellite images. Four domain-adaptation tasks demonstrated that the BGDA method achieved a mean Intersection over Union (mIoU) of over 80%, surpassing 90% of single-domain classification performance. Additionally, the BGDA method successfully classified CRBH across 50 coral reefs in the Nansha Islands. Model transfer experiments further validated the global generalization capability of the proposed method. BGDA offers a scalable, cost-effective solution for large-scale, high-frequency CRBH classification, supporting international efforts in coral reef monitoring and conservation.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1080/15481603.2025.2471193
- https://www.tandfonline.com/doi/pdf/10.1080/15481603.2025.2471193?needAccess=true
- OA Status
- gold
- Cited By
- 4
- References
- 51
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4407994503
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4407994503Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1080/15481603.2025.2471193Digital Object Identifier
- Title
-
Bathymetry-guided multi-source remote sensing image domain adaptive coral reef benthic habitat classificationWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-02-27Full publication date if available
- Authors
-
Hui Chen, Liang Cheng, Zhang KaList of authors in order
- Landing page
-
https://doi.org/10.1080/15481603.2025.2471193Publisher landing page
- PDF URL
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https://www.tandfonline.com/doi/pdf/10.1080/15481603.2025.2471193?needAccess=trueDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://www.tandfonline.com/doi/pdf/10.1080/15481603.2025.2471193?needAccess=trueDirect OA link when available
- Concepts
-
Bathymetry, Coral reef, Benthic habitat, Remote sensing, Reef, Geography, Habitat, Geology, Oceanography, Benthic zone, Cartography, Ecology, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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4Total citation count in OpenAlex
- Citations by year (recent)
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2025: 4Per-year citation counts (last 5 years)
- References (count)
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51Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| referenced_works_count | 51 |
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