A case study comparing approaches to mask satellite-derived bathymetry
Abstract Satellite-derived bathymetry (SDB) is a cost-effective method for estimating water depth in inland and coastal waters, but is only applicable to optically shallow water (OSW). Determining the appropriate extent of SDB maps and the depth threshold for accurate SDB model predictions has there...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-08-01
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| Series: | Discover Geoscience |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44288-025-00219-1 |
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| Summary: | Abstract Satellite-derived bathymetry (SDB) is a cost-effective method for estimating water depth in inland and coastal waters, but is only applicable to optically shallow water (OSW). Determining the appropriate extent of SDB maps and the depth threshold for accurate SDB model predictions has therefore been a challenge for practical applications of SDB. Previous studies have used either a numeric cut-off value or manually delineated OSW to determine where to apply, and where not to apply, SDB models. We compared the use of a threshold applied to the predicted depth, automated delineation of OSW using a published model, and manual delineation of OSW, to determine which method of masking unsuitable pixels for SDB performs best. We used a water-leaving reflectance Sentinel-2 image of the St. Lawrence River, and a Random Forest model using neighbouring pixel information to predict SDB. We then compared the different approaches to masking unsuitable pixels in terms of the mean absolute error (MAE) of the retained predictions and the total mapped area. The application of a model-predicted depth threshold is easy to implement and achieved an MAE of 0.54 m, outperforming automated and manual OSW delineation methods, which had MAEs of 1.39 m and 1.64 m respectively over an approximately 100 km2 study area. Future studies should further investigate these and other methods for masking pixels unsuitable for SDB under a wider range of environmental conditions. |
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| ISSN: | 2948-1589 |