This part of DS 781 presents the seafloor-character map Offshore of Salt Point, California (raster data file is included in "SeafloorCharacter_SaltPoint.zip," which is accessible from http://pubs.usgs.gov/ds/781/OffshoreSaltPoint/data_catalog_OffshoreSaltPoint.html)
This raster-format seafloor-character map shows four substrate classes offshore of Salt Point, California. The substrate classes mapped in this area have been further divided into the following California Marine Life Protection Act depth zones and slope classes: Depth Zone 2 (intertidal to 30 m), Depth Zone 3 (30 to 100 m), Slope Class 1 (0 degrees - 5 degrees), and Slope Class 2 (5 degrees - 30 degrees). Depth Zone 1 (intertidal), Depth Zone 4 (100 to 200 m), Depth Zone 5 (greater than 200 m), and Slopes Classes 3-4 (greater than 30 degrees) are not present in the region covered by this block. The map is created using a supervised classification method described by Cochrane (2008), available at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf
California Department of Fish and Game, 2008, California Marine Life Protection Act master plan for marine protected areas; Revised draft: California Department of Fish and Game, accessed April 5 2011, at http://www.dfg.ca.gov/mlpa/masterplan.asp
Cochrane, G.R., 2008, Video-supervised classification of sonar data for mapping seafloor habitat, in Reynolds, J.R., and Greene, H.G., eds., Marine habitat mapping technology for Alaska: Fairbanks, University of Alaska, Alaska Sea Grant College Program, p. 185-194, accessed April 5, 2011, at http://doc.nprb.org/web/research/research%20pubs/615_habitat_mapping_workshop/Individual%20Chapters%20High-Res/Ch13%20Cochrane.pdf
Sappington, J.M., Longshore, K.M., and Thompson, D.B., 2007, Quantifying landscape ruggedness for animal habitat analysis--A case study using bighorn sheep in the Mojave Desert: Journal of Wildlife Management, v. 71, p. 1419-1426.
These data are intended for science researchers, students, policy makers, and the general public. These data can be used with geographic information systems or other software to identify local seafloor character.