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Home / Photogrammetric Engineering & Remote Sensing, Number 9 / September 2004

Open Access Predicting Seafloor Facies from Multibeam Bathymetry and Backscatter Data

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An empirical technique has been developed that is used to predict seafloor facies from multibeam bathymetry and acoustic backscatter data collected in central Santa Monica Bay, California. A supervised classification used backscatter and sediment data to classify the area into zones of rock, gravelly-muddy sand, muddy sand, and mud. The derivative facies map was used to develop rules on a more sophisticated hierarchical decision-tree classification. The classification used four images, the acoustic-backscatter image, together with three variance images derived from the bathymetry and backscatter data. The classification predicted the distribution of seafloor facies of rock, gravelly-muddy sand, muddy sand, and mud. An accuracy assessment based on sediment samples shows the predicted seafloor facies map is 72 percent accurate.

Document Type: Research Article

Publication date: 01 September 2004

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  • The official journal of the American Society for Photogrammetry and Remote Sensing - the Imaging and Geospatial Information Society (ASPRS). This highly respected publication covers all facets of photogrammetry and remote sensing methods and technologies.

    Founded in 1934, the American Society for Photogrammetry and Remote Sensing (ASPRS) is a scientific association serving over 7,000 professional members around the world. Our mission is to advance knowledge and improve understanding of mapping sciences to promote the responsible applications of photogrammetry, remote sensing, geographic information systems (GIS), and supporting technologies.
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