Satellite-derived bathymetry combined with Sentinel-2 and ICESat-2 datasets using machine learning
Most satellite-derived bathymetry (SDB) methods developed thus far from passive remote sensing data have required in situ water depth, thus limiting their utility in areas with no in situ data. Recently, new Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) observations have shown great potentia...
| 出版年: | Frontiers in Earth Science |
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| 主要な著者: | , , , |
| フォーマット: | 論文 |
| 言語: | 英語 |
| 出版事項: |
Frontiers Media S.A.
2023-03-01
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| 主題: | |
| オンライン･アクセス: | https://www.frontiersin.org/articles/10.3389/feart.2023.1111817/full |