SATELLITE-DERIVED BATHYMETRY USING CONVOLUTIONAL NEURAL NETWORKS AND MULTISPECTRAL SENTINEL-2 IMAGES

6 citations as recorded by crossref.

1. Development of a Fully Convolutional Neural Network to Derive Surf-Zone Bathymetry from Close-Range Imagery of Waves in Duck, NC A. Collins et al. 10.3390/rs13234907
2. Integration of Photogrammetric and Spectral Techniques for Advanced Drone-Based Bathymetry Retrieval Using a Deep Learning Approach E. Alevizos et al. 10.3390/rs14174160
3. Extracting Coastal Water Depths from Multi-Temporal Sentinel-2 Images Using Convolutional Neural Networks Y. Lumban-Gaol et al. 10.1080/01490419.2022.2091696
4. Incorporation of neighborhood information improves performance of SDB models A. Knudby & G. Richardson 10.1016/j.rsase.2023.101033
5. Coastal Bathymetry Estimation from Sentinel-2 Satellite Imagery: Comparing Deep Learning and Physics-Based Approaches M. Najar et al. 10.3390/rs14051196
6. Lyzenga Algorithm for Shallow Water Mapping Using Multispectral Sentinel-2 Imageries in Gili Noko Waters D. Pratomo et al. 10.1051/bioconf/20248907006