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Four-class hardness prediction grids in the eastern Joseph Bonaparte Gulf of Timor Sea

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DataCite Commons2020-09-18 更新2025-04-15 收录
下载链接:
http://pid.geoscience.gov.au/id/dataset/ga/90645
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资源简介:
This dataset contains four-class hardness (i.e., hard-1, hard-soft-2, soft-3 and soft-hard-4) prediction data from seabed mapping surveys on the Van Diemen Rise in the eastern Joseph Bonaparte Gulf of the Timor Sea. This dataset was generated based on hard90 seabed hardness classification scheme using random forest methods based on the point data of seabed hardness classification using video images and multibeam data. Refer to Selecting optimal random forest predictive models: a case study on predicting the spatial distribution of seabed hardness for further information on processing techniques applied [1]. [1] Li, J., Tran, M., Siwabessy, J., 2016. Selecting optimal random forest predictive models: a case study on predicting the spatial distribution of seabed hardness PLOS ONE 11(2) e0149089.
提供机构:
Geoscience Australia
创建时间:
2016-04-08
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