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

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.

Data and resources

Additional information

DOIhttps://pid.geoscience.gov.au/dataset/ga/90645
Date (publication)2016-01-01
StatusonGoing
Update frequencyunknown
Metadata languageen
LicenseCreative Commons Attribution 4.0
Source metadataISO 19115 XML
Last updated2026-11-05
Created2026-11-05
APIpackage_show