Four-class hardness prediction grids in the eastern Joseph Bonaparte Gulf of Timor Sea
收藏Research Data Australia2024-12-14 收录
下载链接:
https://researchdata.edu.au/four-class-hardness-timor-sea/688952
下载链接
链接失效反馈官方服务:
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:
Australian Ocean Data Network



