Marine Geoscience Data System
GPSM_Restreppo Interpretation:Geologic:SedimentaryEnvironments
Machine-learning predicted logarithmic values of marine benthic vertical sediment accumulation rate on the seafloor
This data set consists of logarithmic values of machine-learning-based vertical sediment accumulation rates along the seafloor, globally. The Geospatial Predictive Seafloor Model (GPSM) of the United States Naval Research Laboratory was trained on real-world observations from 89 peer-reviewed sources (n = 1031) to predict marine accumulation rates on a 5-arc-minute map using a k-nearest neighbor algorithm. Original (non-log space values) are in cm/yr. The model and results are described in Restreppo et al. (2020). The data files are in netCDF grid format. The file called contains the predicted sediment accumulation rate in cm/yr. File is the standard deviation.
Device Info
Not Applicable:NotApplicable
The data have been processed/modified to a level beyond that of basic quality control (e.g. final processed sonar data, photo-mosaics).

Data Files


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