Marine Geoscience Data System
GPSM_Restreppo Interpretation:Geologic:SedimentaryEnvironments
Machine-learning predicted logarithmic values of marine mass accumulation rates on the seafloor
This data set consists of logarithmic values of machine-learning-based mass accumulation rates and linear standard deviation on the seafloor, globally. The Geospatial Predictive Seafloor Model (GPSM) of the United States Naval Research Laboratory was trained on real-world observations from 42 peer-reviewed sources (n = 690) to predict marine mass accumulation rates on a 5-arc-minute map using a k-nearest neighbor algorithm. Original (non-log space values) are in g/cm2/yr. The model and results are described in Restreppo et al. (2021). The data files are in netCDF (.nc) grid format. The file called prediction.nc contains the predicted sediment accumulation rate in log10(g/cm2/yr). The file called prediction_sdev.nc is the linear standard deviation, in g/cm2/yr.
Device Info
NotApplicable
Not Applicable:NotApplicable
Platform
NotApplicable
Quality
2
The data have been processed/modified to a level beyond that of basic quality control (e.g. final processed sonar data, photo-mosaics).

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