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Predicted Seafloor Facies of Central Santa Monica Bay, California

Peter Dartnell1 and James V. Gardner2


1 - U.S. Geological Survey, Menlo Park, Calif.
2 - University of New Hampshire, Durham, N.H.

Open-File Report 2004-1081


oblique view of predicted facies in central Santa Monica Bay  

Perspective view of predicted seafloor facies in central Santa Monica Bay. Reds indicate exposed rock, green are areas of gravelly muddy sand, yellow are areas of muddy sand, and blue are areas of mud. The vertical exaggeration of the image is 10x and the distance across the bottom of the image is about 3 km.


Mapping surficial seafloor facies (sand, silt, muddy sand, rock, etc.) should be the first step in marine geological studies and is crucial when modeling sediment processes, pollution transport, deciphering tectonics, and defining benthic habitats. This report outlines an empirical technique that predicts the distribution of seafloor facies for a large area offshore Los Angeles, CA using high-resolution bathymetry and co-registered, calibrated backscatter from multibeam echosounders (MBES) correlated to ground-truth sediment samples. The technique uses a series of procedures that involve supervised classification and a hierarchical decision tree classification that are now available in advanced image-analysis software packages. Derivative variance images of both bathymetry and acoustic backscatter are calculated from the MBES data and then used in a hierarchical decision-tree framework to classify the MBES data into areas of rock, gravelly muddy sand, muddy sand, and mud. A quantitative accuracy assessment on the classification results is performed using ground-truth sediment samples. The predicted facies map is also ground-truthed using seafloor photographs and high-resolution sub-bottom seismic-reflection profiles.

This Open-File Report contains the predicted seafloor facies map as a georeferenced TIFF image along with the multibeam bathymetry and acoustic backscatter data used in the study as well as an explanation of the empirical classification process.

For more information of the classification process see,

Dartnell, P., and J.V. Gardner, in press. Predicted Seafloor Facies from Multibeam Bathymetry and Acoustic Backscatter Data, Central Santa Monica Bay, California. Photogrammetric Engineering and Remote Sensing


FGDC Metadata
Bathymetry Data
XYZ Format ArcInfo GRID Format
Text Format bathyxyz.txt bathygrd.txt
HTML Format bathyxyz.html bathygrd.html
Frequently Anticipated Questions (FAQ) bathyxyzfaq.html bathygrdfaq.html
XML Format bathyxyz.xml bathygrd.xml

Backscatter Data
XYZ Format ArcInfo GRID Format
Text Format mosxyz.txt mosgrd.txt
HTML Format mosxyz.html mosgrd.html
Frequently Anticipated Questions (FAQ) mosxyzfaq.html mosgrdfaq.html
XML Format mosxyz.xml mosgrd.xml


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