Articles | Volume 12, issue 4
https://doi.org/10.5194/essd-12-3367-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-12-3367-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
11 Dec 2020
Data description paper |
| 11 Dec 2020
| 11 Dec 2020
Deep-sea sediments of the global ocean
Geological Survey of Norway (NGU), P.O. Box 6315, Torgarden, 7491
Trondheim, Norway
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Total article views: 5,228 (including HTML, PDF, and XML)
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Cited
21 citations as recorded by crossref.
- Spatial lithological heterogeneity of the deep-sea sediments and its controlling factors in the northern West Caroline Basin, tropical West Pacific X. Guo et al. 10.1016/j.dsr.2023.104175
- Pan-Atlantic Comparison of Deep-Sea Macro- and Megabenthos K. Kürzel et al. 10.3390/d15070814
- Ion association behaviors in the initial stage of calcium carbonate formation: An ab initio study Y. Li et al. 10.1063/5.0206841
- Description of the first cultured representative of “Candidatus Synoicihabitans” genus, isolated from deep-sea sediment of South China Sea T. Ahmad et al. 10.1016/j.syapm.2024.126490
- An Interpretable Multi-Model Machine Learning Approach for Spatial Mapping of Deep-Sea Polymetallic Nodule Occurrences I. Gazis et al. 10.1007/s11053-024-10393-7
- Integrating Angular Backscatter Response Analysis Derivatives Into a Hierarchical Classification for Habitat Mapping P. Porskamp et al. 10.3389/frsen.2022.903133
- Improved environmental mapping and validation using bagging models with spatially clustered data B. Misiuk & C. Brown 10.1016/j.ecoinf.2023.102181
- Scheme design and flow performance analysis of double-bits combination wire-line coring technology for seafloor drill J. Wang et al. 10.1080/1064119X.2024.2309283
- Quaternary sedimentation rate revealed by semi-quantitative analysis in global ocean T. Huang et al. 10.1016/j.marpetgeo.2024.106900
- Trace Element Geochemistry in North Pacific Red Clay Sediment Porewaters and Implications for Water‐Column Studies Z. Steiner et al. 10.1029/2023GB007844
- Bacterial community and antibiotic resistance genes assembly processes were shaped by different mechanisms in the deep-sea basins of the Western Pacific Ocean Q. Jin et al. 10.1016/j.envpol.2024.125214
- What global biogeochemical consequences will marine animal–sediment interactions have during climate change? T. Bianchi et al. 10.1525/elementa.2020.00180
- Modelling mass accumulation rates and 210Pb rain rates in the Skagerrak: lateral sediment transport dominates the sediment input T. Spiegel et al. 10.3389/fmars.2024.1331102
- Ensemble Mapping and Change Analysis of the Seafloor Sediment Distribution in the Sylt Outer Reef, German North Sea from 2016 to 2018 D. Galvez et al. 10.3390/w13162254
- A global analysis of controls on submarine-canyon geomorphology L. Bührig et al. 10.1016/j.earscirev.2022.104150
- Accessing the energy-limited and sparsely populated deep biosphere: achievements and ongoing challenges of available technologies Y. Morono 10.1186/s40645-023-00551-5
- Importance of Spatial Autocorrelation in Machine Learning Modeling of Polymetallic Nodules, Model Uncertainty and Transferability at Local Scale I. Gazis & J. Greinert 10.3390/min11111172
- The necessary optimization of the data lifecycle: Marine geosciences in the big data era T. Lee et al. 10.3389/feart.2022.1089112
- Reanalysis datasets outperform other gridded climate products in vegetation change analysis in peripheral conservation areas of Central Asia H. Zandler et al. 10.1038/s41598-020-79480-y
- A Blueprint for an Inclusive, Global Deep-Sea Ocean Decade Field Program K. Howell et al. 10.3389/fmars.2020.584861
- Contributions to Satellite-Based Land Cover Classification, Vegetation Quantification and Grassland Monitoring in Central Asian Highlands Using Sentinel-2 and MODIS Data H. Zandler et al. 10.3389/fenvs.2022.684589
18 citations as recorded by crossref.
- Spatial lithological heterogeneity of the deep-sea sediments and its controlling factors in the northern West Caroline Basin, tropical West Pacific X. Guo et al. 10.1016/j.dsr.2023.104175
- Pan-Atlantic Comparison of Deep-Sea Macro- and Megabenthos K. Kürzel et al. 10.3390/d15070814
- Ion association behaviors in the initial stage of calcium carbonate formation: An ab initio study Y. Li et al. 10.1063/5.0206841
- Description of the first cultured representative of “Candidatus Synoicihabitans” genus, isolated from deep-sea sediment of South China Sea T. Ahmad et al. 10.1016/j.syapm.2024.126490
- An Interpretable Multi-Model Machine Learning Approach for Spatial Mapping of Deep-Sea Polymetallic Nodule Occurrences I. Gazis et al. 10.1007/s11053-024-10393-7
- Integrating Angular Backscatter Response Analysis Derivatives Into a Hierarchical Classification for Habitat Mapping P. Porskamp et al. 10.3389/frsen.2022.903133
- Improved environmental mapping and validation using bagging models with spatially clustered data B. Misiuk & C. Brown 10.1016/j.ecoinf.2023.102181
- Scheme design and flow performance analysis of double-bits combination wire-line coring technology for seafloor drill J. Wang et al. 10.1080/1064119X.2024.2309283
- Quaternary sedimentation rate revealed by semi-quantitative analysis in global ocean T. Huang et al. 10.1016/j.marpetgeo.2024.106900
- Trace Element Geochemistry in North Pacific Red Clay Sediment Porewaters and Implications for Water‐Column Studies Z. Steiner et al. 10.1029/2023GB007844
- Bacterial community and antibiotic resistance genes assembly processes were shaped by different mechanisms in the deep-sea basins of the Western Pacific Ocean Q. Jin et al. 10.1016/j.envpol.2024.125214
- What global biogeochemical consequences will marine animal–sediment interactions have during climate change? T. Bianchi et al. 10.1525/elementa.2020.00180
- Modelling mass accumulation rates and 210Pb rain rates in the Skagerrak: lateral sediment transport dominates the sediment input T. Spiegel et al. 10.3389/fmars.2024.1331102
- Ensemble Mapping and Change Analysis of the Seafloor Sediment Distribution in the Sylt Outer Reef, German North Sea from 2016 to 2018 D. Galvez et al. 10.3390/w13162254
- A global analysis of controls on submarine-canyon geomorphology L. Bührig et al. 10.1016/j.earscirev.2022.104150
- Accessing the energy-limited and sparsely populated deep biosphere: achievements and ongoing challenges of available technologies Y. Morono 10.1186/s40645-023-00551-5
- Importance of Spatial Autocorrelation in Machine Learning Modeling of Polymetallic Nodules, Model Uncertainty and Transferability at Local Scale I. Gazis & J. Greinert 10.3390/min11111172
- The necessary optimization of the data lifecycle: Marine geosciences in the big data era T. Lee et al. 10.3389/feart.2022.1089112
3 citations as recorded by crossref.
- Reanalysis datasets outperform other gridded climate products in vegetation change analysis in peripheral conservation areas of Central Asia H. Zandler et al. 10.1038/s41598-020-79480-y
- A Blueprint for an Inclusive, Global Deep-Sea Ocean Decade Field Program K. Howell et al. 10.3389/fmars.2020.584861
- Contributions to Satellite-Based Land Cover Classification, Vegetation Quantification and Grassland Monitoring in Central Asian Highlands Using Sentinel-2 and MODIS Data H. Zandler et al. 10.3389/fenvs.2022.684589
Discussed (final revised paper)
Latest update: 20 Nov 2024
Short summary
A new digital map of the sediment types covering the bottom of the ocean has been created. Direct observations of the seafloor sediments are few and far apart. Therefore, machine learning was used to fill those gaps between observations. This was possible because known relationships between sediment types and the environment in which they form (e.g. water depth, temperature, and salt content) could be exploited. The results are expected to provide important information for marine research.
A new digital map of the sediment types covering the bottom of the ocean has been created....
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