Synthetic shelf sediment maps for the Greenland Sea and Barents Sea

Synthetic shelf sediment maps for the Greenland Sea and Barents Sea
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格陵兰海和巴伦支海的合成陆架沉积物图

DOI:
10.1002/gdj3.154
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发表时间:
2022
影响因子:
3.2
通讯作者:
Laverick J
Laverick J
中科院分区:
地球科学4区
文献类型:
--
作者:
Laverick J

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海底沉积物图是各种海洋研究工作的基础。许多地区都有海底测绘数据,但这些数据通常提供离散的分类,从而模糊了沉积物的潜在连续特性。其他地区的调查很少,例如由于冰层覆盖而无法进入的极地地区。在这里,我们关注的是难以接近的格陵兰东北陆架,那里几乎没有海底沉积物数据。我们训练了一个随机森林模型,利用水深测量、海流和海浪的数据,从邻近巴伦支海的现有地图上预测沉积物类别。然后,我们用我们的模型预测了东格陵兰岛未知的沉积物分布。在此过程中,我们生成了一些关于巴伦支海以前未绘制的属性的新空间数据,如平均粒度、有机碳和氮含量、孔隙度和渗透率。这两个区域的地图可用于支持今后在北极的研究活动,例如,生态系统模式中底栖生物地球化学的参数化,或绘制物种分布图。
Seabed sediment maps underpin a variety of marine research endeavours. Seabed mapping data are available for many regions, but these usually provide discrete classifications which obscure underlying continuous properties of the sediments. Other areas are poorly surveyed, e.g., polar regions which are inaccessible due to ice cover. Here, we focus on the inaccessible North East Greenland shelf for which there are almost no seabed sediment data. We trained a random forest model to predict sediment classes from an existing map of the well‐surveyed neighbouring Barents Sea, using data on bathymetry, currents and waves. We then used our model to predict the unknown sediment distributions off East Greenland. In the process, we generated some new spatial data on previously un‐mapped properties of the Barents Sea, such as mean grain size, organic carbon and nitrogen content, porosity and permeability. The maps of both regions are available to support future research activities in the Arctic, e.g., the parameterization of benthic biogeochemistry in ecosystem models, or mapping species distributions.
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DOI: --
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