usSEABED: Pacific Coast (California, Oregon, Washington) 

Offshore Surficial-Sediment Data Release, version 1 

By Jane A. Reid1

, Jamey M. Reid1, Mark Zimmermann2, Chris J. Jenkins3, S. Jeffress Williams1, 

and Michael E. Field1

1

 U.S. Geological Survey (USGS) 

2

 National Oceanic and Atmospheric Administration (NOAA) 

3

 University of Colorado 

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement 

by the U.S. Government 

U.S. Geological Survey Data Series 182 

2006, Version 1.0 

U.S. Department of the Interior 

U.S. Geological Survey 
U.S. Department of the Interior 

P. Lynn Scarlett, Acting Secretary 

U.S. Geological Survey 

P. Patrick Leahy, Acting Director 

U.S. Geological Survey, Menlo Park, California 

For additional information, see: 

http://walrus.wr.usgs.gov/usseabed

http://walrus.wr.usgs.gov/nearshorehab

http://woodshole.er.usgs.gov/project-pages/aggregates

Feedback on usSEABED is appreciated, both in usefulness and in error detection. Please use the 

following contact information for issues, questions and/or data to contribute to the growing usSEABED 

information system in the U.S. EEZ. 

Contact: 

Jane A. Reid for information about the National Sea-Floor Mapping and Benthic Habitats project and (or) 

adding Pacific Coast, Alaska or Hawaii data 

USGS, Pacific Science Center, 400 Natural Bridges Drive, Santa Cruz, CA 95060; jareid@usgs.gov 

S. Jeffress Williams for information about the Marine Aggregates Resources and Processes project and 

(or) adding Atlantic and (or) Gulf Coast Data 

USGS, Woods Hole Science Center, 384 Woods Hole Road, Woods Hole, MA 02543-1598; 

jwilliams@usgs.gov 

Chris J. Jenkins for information about the dbSEABED program and data around the world 

University of Colorado, Institute of Arctic and Alpine Research, 1560 30th Street, Campus Box 450, 

Boulder CO, 80309-0450; chris.jenkins@colorado.edu 

For more information about the USGS – the Federal source for science about the Earth, its natural and 

living resources, natural hazards, and the environments 

World Wide Web http://www.usgs.gov

Telephone 1-888-ASK-USGS 

Although this report is in the public domain, permission must be secured from the individual copyright 

owners to reproduce any copyrighted material contained within this report.
usSEABED: Pacific Coast (California, Oregon, Washington) 

Offshore Surficial Sediment Data Release, version 1.0 

U.S. Geological Survey Data Series 182 

by Jane A. Reid, Jamey M. Reid, Chris J. Jenkins, Mark Zimmermann, S. Jeffress 

Williams, and Michael E. Field 

ABSTRACT.................................................................................................................................. iii

INTRODUCTION ..........................................................................................................................1

Future Plans, Updates, and Online Usage in a GIS......................................................1

Applications...................................................................................................................1

National Sea-Floor Mapping and Benthic Habitat Studies ............................................2

usSEABED (DATA).......................................................................................................................5

How usSEABED is Built ................................................................................................5

Sources of Data.............................................................................................................5

Data Themes and Output Files .....................................................................................6

Relational keys ......................................................................................................6

Source data (SRC) ................................................................................................6

Textural and other basic information (EXT, PRS, CLC) ........................................6

Extracted data (EXT).............................................................................................7

Parsed data (PRS) ................................................................................................7

Calculated data (CLC)...........................................................................................7

Component/feature and facies data (CMP, FAC)..................................................8

Relationship between the PRS and CMP outputs.................................................9

Quality Control...............................................................................................................9

Spatial and Temporal Uncertainties ..............................................................................9

dbSEABED (PROCESSING) ......................................................................................................11

Data Import Methods...................................................................................................11

The Numeric Data Type (extracted, EXT)...................................................................12

The Linguistic Data Type (parsed, PRS).....................................................................12

A simplified description of dbSEABED processing......................................................13

Expansion of Data Coverage ......................................................................................15

Calibration ...................................................................................................................15

Statistical Tests .......................................................................................................15

i
Individual Tests .......................................................................................................16

DATA CATALOG ........................................................................................................................17

Data Files ....................................................................................................................17

Legends.......................................................................................................................17

Color............................................................................................................................18

Roughness ..................................................................................................................18

ACKNOWLEDGEMENTS ...........................................................................................................19

REFERENCES CITED................................................................................................................20

FIGURE 1: usSEABED data.......................................................................................................22

FIGURE 2. Marine sand bodies. ................................................................................................23

FIGURE 3: Statistical calibration of outputs for grain sizest.. .....................................................24

FIGURE 4: Crossplot of lab-based grain size values (EXT) against grain size values derived 

from word-based descriptions from the same samples.......................................................25

FIGURE 5. Grain-size distributions off Oregon,..........................................................................26

FIGURE 6. Relative presence of phosphorite in southern California using the component (CMP) 

data.. ...................................................................................................................................27

FIGURE 7. Presence of shells (orange) and worms (blues) in central California using the facies 

(FAC) file.............................................................................................................................28

TABLE 1. Key to data themes in usSEABED output files ...........................................................29

TABLE 2. usSEABED output files...............................................................................................29

TABLE 3. Field parameters, format, units, range, meaning, and comments for the extracted 

(EXT), parsed (PRS), and calculated (CLC) data files ........................................................30

TABLE 4. Components (features_F) processed within usSEABED (data file CMP)...................34

TABLE 5. Facies and their component makeup (data file FAC) .................................................40

TABLE 6. Most frequently occurring biological components that may have textural implications 

(U.S. waters only) ................................................................................................................42

TABLE 7. usSEABED Pacific (California, Oregon, Washington) data. .......................................43

TABLE 8. Base-map layers.........................................................................................................44

APPENDIX A. Data Sources......................................................................................................45

APPENDIX B. Published Articles about dbseabed ....................................................................56

APPENDIX C. Frequently Asked Questions about dbSEABED and usSEABED ......................57

APPENDIX D. onCALCULATION ..............................................................................................57

ii
ABSTRACT 

Over the past 50 years there has been an explosion in scientific interest, research effort, 

and information gathered on the geologic sedimentary character of the U.S. Pacific coast 

continental margin. Data and information from thousands of publications have greatly increased 

our scientific understanding of the geologic origins of the margin surface but rarely have those 

data been combined and integrated. 

This publication is the first release of the Pacific coast data from the usSEABED 

database. The report contains a compilation of published and unpublished sediment texture and 

other geologic data about the sea floor from diverse sources. usSEABED is an innovative 

database system developed to unify assorted data with the data processed by the dbSEABED 

system. Examples of maps displaying attributes such as grain size and sediment color are 

included. This database contains information that is a scientific foundation for the U.S. 

Geological Survey (USGS) Sea floor Mapping and Benthic Habitats project and the Marine 

Aggregate Resources and Processes assessment project, and will be useful to the marine 

science community for other studies of the Pacific coast continental margin. 

CITATION: This document should be cited as: Reid, J.A., Reid, J.M., Jenkins, C.J., 

Zimmermann, M., Williams, S.J., and Field, M.E., 2006, usSEABED: Pacific Coast (California, 

Oregon, Washington) Offshore Surficial-Sediment Data Release: U.S. Geological Survey Data 

Series 182, version 1.0. Available online at http://pubs.usgs.gov/ds/2006/182. 

Any use of trade names is for descriptive purposes only and does not imply 

endorsement by the U.S. Government. 

iii
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

INTRODUCTION 

This data release provides an improved and robust integrated database (usSEABED) of 

seabed characteristics for the Pacific continental margin of the United States (figure 1) that 

fulfills a need for information about seabed characteristics for use by geologists, ecologists, 

biologists, resource managers, and national defense investigators. usSEABED provides a 

digital, integrated database of existing physical data and information from the sea floor, 

including textural, statistical, geochemical, geophysical, and compositional information. It uses 

the dbSEABED data mining and processing software to extend the coverage of information in 

areas where data coverage is more descriptive than quantitative. The data coverage includes 

the U.S. Pacific coast from Cape Flattery (including Puget Sound) to the Mexican border, 

including major estuaries, for example, San Francisco and Willapa Bays and beaches, and 

extends seaward across the Continental Shelf and Slope. More than 100 different data sources 

containing over 65,000 data points from more than 25,000 sites are currently contained in 

usSEABED for the contiguous United States along the Pacific margin. 

This data-series publication is the third in a set of similar publications that covers the 

entire Exclusive Economic Zone of the United States (U.S. EEZ). Also available are the sister 

publications of usSEABED data from the Atlantic margin (Reid and others, 2005) and the Gulf of 

Mexico and Caribbean regions (Buczkowski and others, 2006). Another companion publication 

will include data from Alaska and Hawaii. Each of these publications will be updated as 

significant amounts of new data are included in usSEABED. Current information about 

publications and other issues are posted on the usSEABED website. 

This publication contains information on the usSEABED data collection, dbSEABED 

program processing, as well as a Data Catalog where the data are included (within compressed 

files) as GIS layers and comma-delimited text files. 

The overall usSEABED database holds data for the entire U.S. EEZ and is an ongoing 

task of the National Sea Floor Mapping and Benthic Habitats project and the Marine Aggregates 

Resources and Processes project being conducted by USGS Coastal and Marine Geology 

teams in Santa Cruz, CA, Woods Hole, MA, and St. Petersburg, FL, and the University of 

Colorado. 

Future Plans, Updates, and Online Usage 

It is expected that usSEABED will continue to expand by the incorporation of new data 

sets and by the utilization of the data in new and different ways. As significant changes are 

made, we expect to reissue updates of usSEABED. Data contributions and (or) additional 

partners are welcomed. 

Published usSEABED data from this region and others are accessible online (using 

ESRITM ArcIMS®) at http://coastalmap.marine.usgs.gov/regional/contusa/index.html. Data layers 

will also be submitted for viewing and downloading through www.geodata.gov. 

Applications 

The usSEABED database is a very large compilation, containing complex assortments 

of data and geologic information on the geology of the sea floor. Although this database was 

developed for use in conducting studies of offshore sedimentary character for assessing marine 

aggregates and characterizing benthic habitats, it has potential for greater application by the 

marine science community and other users. Users are encouraged to generate their own 

1 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

queries and extract information to meet specific needs. Some other possible applications where 

data and maps from usSEABED could be useful are: 

• Research ocean observation and monitoring 

• Coastal zone/ocean management and planning 

• Homeland security, military applications 

• Sea-floor engineering, planning, and design 

• Ocean disposal site placement, monitoring 

• Cultural resources 

• Fisheries management, marine protected areas 

• Determination of seabed roughness, bedform distribution, critical shear stress, and 

sediment transport flux 

• Public education 

• Determination of sea-floor bottom-friction values for calibration of modeling 

processes, such as the effects of storm waves on sediment mobility and transport 

National Sea-Floor Mapping and Benthic Habitat Studies 

The quality and protection of natural environments is a high priority for the Nation. This 

includes Federal lands in the coastal and marine realm, where a variety of human activities 

stress natural systems and resources. The USGS is a lead scientific agency conducting 

research on the Atlantic, Gulf of Mexico, and Pacific margins to better understand marine seafloor environments. This research on benthic habitats is conducted under the general topic of 

habitat geoscience, which is defined as the study and classification of seabed habitats in the 

context of their geologic framework, their response to seabed processes, and their function as 

substrate for invertebrates and fish, is underway in all three regions. This research requires 

close collaboration between geologists, biologists, and oceanographers. High-resolution and 

detailed knowledge of bottom characteristics and sediment distribution, a goal of the usSEABED 

database, is fundamental to these studies. 

The National Sea-Floor Mapping and Benthic Habitat Studies Project for the Pacific 

coast, works collaboratively with other federal, state, and local agencies, to investigate geologic 

controls on benthic habitats in bays, estuaries, fjords, and continental shelf environments. The 

project employs a multipronged approach, utilizing tools that include sidescan, backscatter 

imagery, and multibeam sonar, bottom video and photos, Laser In-Situ Scattering and 

Transmissometry (LISST), Light Detection And Ranging (LIDAR), physical sampling and 

underwater digital microscope imaging (for example, an eyeball camera) and usSEABED. The 

collocated information is integrated, leading to better maps and increased understanding of 

habitats on a variety of scales. An important analytical sidelight to this research is a useful 

understanding of the relations between the various mapping and analytical techniques that 

allows for better mapping and assessment abilities. 

A critical issue studied by the USGS National Sea-Floor Mapping and Benthic Habitats 

project for the Pacific is the impact of human activities on benthic habitats. These activities 

range from land development issues, watershed usage and pollutant transport, sanitary outfalls 

and waste disposal, shipping and anchoring, and dredging and spoil dumping to glacial retreat, 

uplift, the relative importance of artificial reefs as habitat, and invasive species. 

Endangered and threatened living resources, such as Pacific Coast rockfish (Sebastes) 

and white abalone, are of prime concern to the public and managing agencies. One approach to 

the restoration of these habitats is the establishment of Marine Protected Areas (MPAs). The 

USGS and its partners use their expertise to map and characterize benthic habitats at 

2 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

biologically relevant scales to assist in MPA design and other fisheries management efforts. 

These efforts are centered in areas managed by National Oceanic and Atmospheric 

Administration (NOAA) National Marine Fisheries Service, NOAA National Marine Sanctuaries 

Program, and the National Park Service. For more information about sea-floor mapping and 

benthic habitat research by the USGS in the Pacific, see 

http://walrus.wr.usgs.gov/nearshorehab/index.html. 

Marine Aggregate Resources 

Continental margins are products of complex geologic processes. They comprise 

submerged landforms that offer a variety of benthic habitats for fisheries, as well as affect 

navigation, homeland security, and engineering activities. Continental shelves also contain 

hard-mineral deposits such as, sand and gravel, which are potential aggregate resources. 

Coastal erosion, resulting from a combination of natural (storms, sea-level rise, sediment 

starvation, land subsidence) and anthropogenic processes (dams, dredging, coastal 

engineering structures), is pervasive in most U.S. coastal regions. Development in the coastal 

zone continues to increase, and demographic projections show that the trend of people moving 

to the coast will likely continue, placing more people and development at increasing risk from 

coastal hazards. With future global climate change likely to cause changes in storm frequency 

and resulting accelerated global sea-level rise, coastal regions are likely to experience even 

greater erosion, inundation, and storm-surge flooding. 

Beach nourishment, a practice of placing sand dredged from offshore area onto eroding 

beaches, is increasingly viewed as a cost-effective and environmentally acceptable method for 

mitigating coastal erosion, reducing storm and flooding risk, and restoring degraded coastal 

barrier-island ecosystems for developed coasts. For beach nourishment to be viable, however, it 

is necessary to locate high-quality sand; the sand bodies must ideally be reasonably close to 

beaches being considered for nourishment, and the sand volumes must be sufficient to meet 

recurring nourishment requirements for 50 years or longer. Sand bodies on inner Continental 

Shelf regions are often the most suitable sand sources for beach nourishment. Examples of 

marine sand bodies are shown in figure 2. 

Because offshore areas are increasingly important, comprehensive, up-to-date and 

integrated databases that can be used as sources for modern Geographic Information Systems 

(GIS) are needed to produce base maps displaying thematic information, such as sea-floor 

geology, sediment character and texture, sea-floor roughness, and engineering properties. 

Digital geologic maps, based on unified national data sets and showing the sedimentary 

character of U.S. continental margins, are critical for scientists to better understand and interpret 

the geologic history and evolutionary processes of continental margins. These products are also 

useful to managers for protecting and managing coastal and marine environments 

The USGS, in collaboration with other Federal agencies (U.S. Navy Office of Naval 

Research (ONR), Minerals Management Service (MMS), U.S. Army Corps of Engineers 

(USACE), National Oceanic and Atmospheric Administration (NOAA) and others), coastal 

States, and universities, is leading a nationwide effort to gather legacy marine geologic data for 

use in conducting assessments of offshore sand and gravel resources and for producing GIS 

map products of sea-floor geology that can serve many additional needs. Assessments are 

being conducted in offshore Louisiana, the New York Bight (New York-New Jersey), and the 

Gulf of Maine regions. The GIS maps and usSEABED database from this study are providing 

fresh scientific insights into the geologic character and development of U.S. continental margins 

and useful information about the quality and potential availability of offshore sand and gravel 

aggregates. Additional details are available at http://woodshole.er.usgs.gov/projectpages/aggregates/index.htm. 

3 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Applications of research results include fishery management, habitat disturbance and 

recovery studies, impacts of invasive species, studies of deep-water coral habitats, the fates of 

contaminants from coastal sources, location and monitoring of disposal sites, the routes of 

cables and pipelines on the seabed, and the location of aggregate deposits having potential for 

use for beach nourishment. For more information on these and other research about coastal 

and marine issues, see http://walrus.wr.usgs.gov/, http://marine.usgs.gov/, and 

http://woodshole.er.usgs.gov/. 

4 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

usSEABED (DATA) 

The usSEABED database differs from a traditional relational database (RDB) because 

the data are processed and extended to maximize density and usability, making them more 

comprehensive for mapping and analysis. A traditional RDB often creates simplistic and sparse 

data summary coverages with thinly populated and unwieldy tables. The usSEABED database 

not only treats the usual forms of numerical data but also contains a vast store of data about the 

sea floor in word-based descriptions that can be rich in information but difficult to quantify, map, 

plot, or use in comparative analyses or models. The usSEABED database provides numeric 

values for typical seabed characteristics that are based on these descriptive data as well as 

numeric analytical data. 

The usSEABED database also differs from other marine databases in that it incorporates 

a wide variety of information about sea-floor sediment texture, composition, color, biota, and 

rocks; sea-floor characteristics such as hardness or sediment ripples, acoustic properties, and 

geochemical and geotechnical analyses. The usSEABED output files are produced in commadelimited text for ease of use and are ready for inclusion into many different GIS, RDB, and 

other software applications. 

How usSEABED is Built 

The usSEABED database is built using the dbSEABED processing software created at 

the University of Sydney (Australia) and the University of Colorado. It has companion databases 

built along similar lines: auSEABED for Australia, balticSEABED, and a global database, 

goSEABED. Each database relies on preexisting data from a variety of sources to mine and 

extrapolate useful information about the seabed. 

The dbSEABED program allows these source data sets to be compiled in a standardized 

format and integrates information across a series of data themes (table 1) and physical 

sampling equipment (grabs, cores, or probes) or remotely sensed sampling (descriptions from 

photographs and videos, geophysics, soundings). These data may be numeric lab- or 

instrument-based textural, acoustic, geochemical, and geophysical data and (or) verbal 

(linguistic) descriptions of grabs, cores, or photographs, or a combination of any of these 

In the usSEABED database, most data held in these reports are mined for additional 

information that increases the data density over the seabed, allowing for more complete 

information. Few source reports contain all data reportable in usSEABED; null values are given 

in those fields without data. 

Sources of Data 

usSEABED relies on previously existing and newly collected data, both published and 

unpublished, from Federal, State, regional, and local agencies and consortiums, as well as 

research institutions. For the Pacific coast, many of the data are from the USGS, including 

published and unpublished data from the 1980s to 2000s. 

Data gathered by NOAA National Ocean Service (NOS) during their many sounding 

surveys in the 1960s to 1990s are included, as archived by the Smithsonian Institution and 

provided by the National Geophysical Data Center (NGDC). Theses and dissertations from 

many universities, reports from University of California (Berkeley) Hydraulic Engineering Lab, 

University of Washington's data publications of the 1960s and 1970s, U.S. Army Corps of 

Engineers (USACE) reports, and local harbor and U.S. Navy (USN) reports are also included. A 

5 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

large data compilation, Deck 41, archived at NGDC is included, which is from a wide variety of 

data sources. A complete list of data sources for the Pacific coast is included in Appendix A. 

Although efforts have been made to reduce data duplications within usSEABED, they 

may exist within the input Pacific data sets as data from the same cruise or site may be 

published in more than one report or data compilation. For example, NGDC's Deck 41 

compilation contains information for several west coast sources; sites are decommissioned in 

our Deck 41 data set where these sources are included within usSEABED under the original 

sources. In other instances, data from different sources for a given site may be included if 

significant additional data are included. For example, one source may report only grain size for 

a particular site, but another source may include geophysical properties for the same 

sites/sample. 

Data Themes and Output Files 

Seabed data come in a variety of forms, which have information in different parameters. 

For example, textural analyses may have information for percentages of gravel, sand, and mud 

(silt and clay); statistical measurements such as mean, median, sorting, skewness, and kurtosis 

often accompany the textural information. Acoustical measurements include various velocities 

and derived densities. Benthic habitat studies may include a short description of the sea-floor 

sediment type and a numerical survey of animals and plants on the sea floor, or evidence of 

them. 

The original seabed information in usSEABED is entered into different data themes 

(table 1). The thematic basis of the values found in the outputs can be found in the DataType 

field of the extracted (EXT), parsed (PRS), and calculated (CLC) output files. Information on the 

contribution of each source report is in the accompanying source metadata files.

This publication provides six usSEABED output data files for the Pacific Coast (table 2). 

These files are downloadable from the Data Catalog. An additional output file type, although 

unpublished, provides quality control for the data and was used extensively prior to publication 

to debug and test the data. Field parameters for the data files are listed in tables 3, 4, and 5. 

Relational keys 

The usSEABED data file types are linked relationally by the foreign keys: DataSetKey

(for individual data sets), SiteKey (for individual sites), and the SampleKey (for individual 

analyses). The DataSetKey field gives the relationship of the data to the original source. The 

tables can be loaded into an RDB, relationships may be constructed, and the tables may be 

joined using the keys. 

Source data (SRC) 

Information about the original data are in the source (SRC) file, including links to 

metadata about the original data. Each of the output data files discussed below is relationally 

linked to the SRC file by the DataSetKey field. Source information is also provided in a more 

traditional bibliographic format in Appendix A. 

Textural and other basic information (EXT, PRS, CLC) 

Textural, statistical, geochemical, geophysical, dominant component, and color 

information are held in three separate, but similar, data files, based on the type of data: EXT, 

PRS, CLC. The three data file types have the same fields (table 3) and can be combined for 

more extensive coverage of the sea floor. 

6 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

It is important for users to understand the inherent limitations of each type of file in order 

to choose the best data file, or combination of data files, appropriate for a particular use. Other 

dbSEABED programs can combine the three files in a variety of ways, by concatenation or by 

telescoping, before they are mapped or used for other types of analysis. For access to these 

files, please see the contact information at the beginning of this report. 

Extracted data (EXT) 

The data file with the EXT tag is the "extracted" data: those data from strictly performed, 

lab-based, numeric analyses. Most data in this file are listed as reported by the source data 

report; only minor unit changes have been performed. In some cases, assumptions may be 

made about the thickness of the sediment analyzed based on the sampler type. Typical data 

themes include textural classes and statistics (TXR: gravel, sand, silt, clay, mud, and various 

statistics), phi grain-size classes (GRZ), chemical composition (CMP), acoustic measurements 

(ACU), color (COL), and geotechnical parameters (GTC). The EXT file is based on rigorous labdetermined values and forms the most reliable data set. Limitations, however, exist due to the 

uncertainty of the sample tested; for example, were the analyses performed on whole samples 

or only on the matrix, possibly with larger particles ignored? 

Parsed data (PRS) 

Numeric data mined from verbal logs, core or grab descriptions, shipboard notes, and 

(or) photographic descriptions are held in the parsed data set (PRS). The input data are 

maintained using the terms employed by the original researchers and are coded using 

phonetically sensible terms for easier processing by dbSEABED. Longer descriptions may have 

the data divided by theme (table 1). The descriptions often include information on associated 

biota, sea-floor features, and structure. Typical data themes for the parsed data set are 

lithologic descriptions (LTH), biology (BIO), color (COL), and (or) sea-floor type (SFT, 

descriptions from photos or videos). The values in the parsed data file are calculated using the 

dbSEABED parser that assigns field values based on the form and content of a description. See 

the section on dbSEABED processing and fuzzy set theory for a more complete explanation. 

The parsing process has been tested and calibrated by comparing the outputs against 

analytical results for the same samples. Due to the nature of visual descriptions by observers 

and the use of fuzzy set theory in the parser, the output data variously show the degree of 

representation in the sample or percent abundance values. An assumption in the process is that 

the output degrees of representation reflect absolute abundances to some degree of accuracy. 

The calibrations provide information on that accuracy. Although at first sight the descriptive 

results in the parsed file may seem less accurate than measured values in the extracted file, 

they are frequently more representative of the sample and seabed as a whole, as they include 

description of objects such as shells, stones, algae, and other objects (table 6) that are a 

textural component of the seabed and are often left out of laboratory analyses, particularly when 

a machine analysis is employed. 

Calculated data (CLC) 

For the extracted and parsed data, some values are not reported by the original source 

but can be calculated directly or estimated by standard derivative equations using assumptions 

(see Appendix C. Frequently Asked Questions) about the conditions or variables. These values 

are reported in the calculated (CLC) data files. Although the CLC data can be combined with the 

extracted and the parsed data (table 3), they are the least reliable of the three data file types 

and should be used with caution. 

7 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Component/feature and facies data (CMP, FAC) 

Two usSEABED data files contain information about the presence of certain sea-floor 

features, compositional content, biota, and sediment structure. These use senior synonyms 

defined by the thesaurus in the dbSEABED parsing software, which clusters comparable 

descriptive terms together (granite represents granite, aplite, granodiorite, pegmatite, whereas 

laminated represents laminated, laminations, or lamina). Individual components and features 

(terms like feldspar, phosphorite, bivalves, seagrass, and wood, for example) are held in the 

CMP data file (table 4). Appropriately combined components are held in the facies (FAC) data 

files (table 5). As with the parsed data files, the values held within the CMP and FAC files are 

the results of filters based on fuzzy-set membership to chosen sets and represent a measure of 

truth about the attribute, not percentages or defined values. These files only indicate presence, 

not absence, of material; it is rare that a report might state, "no bivalves" or "no phosphorite.” 

The CMP file contains information about compositional content (individual minerals, 

rocks), genesis (terrigenous, carbonate), and certain biota. These components are internally 

evaluated and the value for each attribute is based solely on the relationships of attributes within 

the original description. The flora and fauna included in the compositional components are those 

that may have an effect on textural determinations in the PRS data file, such as halimeda, 

bivalves, or foraminifera (table 6). The values within these attribute fields range between 0 (no 

membership, possibly due to no information), to 100 (complete membership, shell hash = 100 to 

the shell debris set). 

The CMP file also includes information on sea-floor features, such as bedforms, fissures, 

internal structure (bedding, bioturbation), and other flora and fauna. Unlike the compositional 

content information, which is construed as an abundance within the sample, these attributes are 

an intensity of development or density of occurrence relative to scales of development or 

density of occurrence observed elsewhere. The flora and fauna included in the feature category 

are soft-bodied, for example, those that do not have an input on the textural determination within 

the PRS data files, such as kelp, ophiuroids, or annelids. Values within the attribute fields range 

from 0 (no membership, possibly due to no information) up to 100 (maximum development). In 

contrast to the situation with component abundances, the sum of feature intensities in a sample 

is allowed to exceed 100. 

The 100 most common components (number limited by dbSEABED processing 

software) in the U.S. EEZ are given in the CMP file, and those attributes with "_F" denote 

features. Table 4 lists the components and gives basic forms of descriptive terms that may 

trigger membership for each. Included in this file are 27 components that are included in the 

facies (FAC) file only. The dbSEABED thesaurus used for usSEABED is also used for the sister 

data compilations (auSEABED, BalticSEABED, goSEABED), and the list of trigger terms may 

include some that are not known in U.S. waters. 

The second file, the facies file (FAC), is created from components only, similar to the 

CMP file. This file configures multiple components into appropriate groups or facies, such as 

igneous, metamorphic, ooze, foraminifera, and others. The dbSEABED processing software is 

restricted to a maximum of six components per facies. Table 5 lists the facies type and the 

components that comprise each facies group. 

Again, these files only indicate presence, not absence, of material; it is rare that a report 

might state, "no bivalves" or "no phosphorite." The values within this attribute field range 

between 0 (no membership, possibly due to no information) to 100 (complete membership, for 

example, schist = 100 to the metamorphic set).

8 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Relationship between the PRS and CMP outputs 

The dbSEABED processing software recognizes that many skeletonized biota, such as 

halimeda, rhodoliths, shells (broken and unbroken), and others often constitute a sediment 

sample. Such biological terms are included in the parsing of the textural values. The selected 

biota with textural implications are listed in table 6. When using the parsed data, it may be 

important to crosscheck with the component file using the relational foreign keys (SiteKey, 

SampleKey) to determine if biota are to be included in the textural outputs. 

Within the PRS file, the 'seabed class' and 'class membership' field indicate the 

dominant compositional class and the fuzzy-set membership of a sample to that class. Other 

components and mined information may also be listed for that sample in the CMP file, linked by 

the relational keys. 

Quality Control 

Quality control over the data is an iterative process implemented using criteria in the 

following steps. First, graphical plots of site locations and parameter values are used to detect 

outliers and edit them appropriately. Each data set is viewed in a GIS to ensure that data 

locations are reasonable relative to survey extents; those sites with unresolvable location issues 

or known incomplete analyses are deactivated and are not included in the usSEABED output 

files. (Note: usSEABED does contain a small number of onshore samples.) This step may be 

optional depending on the data set. Older sets may require more scrutiny at this step, whereas 

newer or well-exercised data sets require less. 

Second, built-in filters in the dbSEABED processing software detect implausible values 

for numeric fields, unknown verbal terms, incomplete analyses (for example, Gravel-Sand-Silt 

Clay (mud) (GSSC(m)) greater than 105% or less than 95%), and incorrect field types (string or 

number). The software also detects samples that seem to belong to a core though they are 

described as independent samples. For the parsing of verbal descriptions, all terms must be 

known to the dbSEABED data processing program, with values assigned; those analyses that 

fail this test have null values given to all appropriate fields. Edits are made to the data at the 

level of the usSEABED input data files and metadata are entered explaining the changes. The 

edits (or deactivations) are then taken into account in the next dbSEABED program run. 

Finally, output data are analyzed in a GIS to test whether the data outputs "make sense" 

for a given geographic area. Users of the output data should, however, note the limitations 

imposed by the source data sets as to navigational precision, sampler type, and analytical 

technique. 

As issues about the data or the data processing may be discovered, errata will be 

posted on the usSEABED website. Corrections will be included in the next version of this 

publication. 

See the dbSEABED section and the Frequently Asked Questions for details about the 

usSEABED data mining program and the application of fuzzy set theory. 

Spatial and Temporal Uncertainties 

Users of usSEABED data are reminded that many seafloor regions are, by their nature, 

dynamic environments subject to a variety of physical processes, such as erosion, winnowing, 

reworking, and sedimentation or accretion that vary on different spatial and temporal scales, 

and sea-floor samples may represent a only moment in time. Because usSEABED is comprised 

of samples collected, described, and analyzed by many different organizations and individuals 

over a span of years, metadata are provided for each source report, linked both through the 

9 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

bibliographic list of data sources (Appendix A) and the relational link DataSetKey in the output 

files. In cases where original metadata are not available from the data source, metadata were 

created based on available information accompanying the data. Of particular importance, site 

locations are as given in the original sources, with uncertainties due to navigational techniques 

and datums ignored in the usSEABED compilation. As many reports are decades old, users of 

usSEABED should use their own criteria to determine the appropriateness of data from each 

source report for their particular purpose and scale of interest. 

In addition, there are uncertainties in data quality associated with both the extracted data 

(from lab-based analytical analyses) and parsed data (word-based descriptions). It may be that 

grain-size analyses are done solely on the sand fraction excluding coarser material, such as 

shell fragments and gravel, while word descriptions of sediment samples may emphasize the 

proportion of a sediment fraction over another and may disregard other important textural or 

biological components. Detailed information about issues such as these are noted in the source 

metadata files and known incomplete data are decommissioned in usSEABED. 

Users are encouraged to view the entire document before downloading the data files in 

the Data Catalog and should refer to the provided metadata files for information about individual 

sources' limitations, date of collection, and other pertinent information. 

10 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

dbSEABED (PROCESSING) 

The dbSEABED processing system was developed by Jenkins (1997, 2002, 2003) in 

collaboration with the USGS and others over the past decade. Currently, there is no opensource code for the program. This explanation of the system is intended to give information and 

guidance about how the data are compiled, integrated, and processed in the usSEABED 

database. The dbSEABED system aims to produce a unified mappable database from the 

multitude of data sets dealing with the seabed. The primary objective of the dbSEABED system 

is to produce integrated data that can be mapped, analyzed, and visualized. Data sets include 

both legacy and modern collections, involving data from samplings and visual inspections. 

Filtering routines within dbSEABED unify marine geologic data that originally may be disparate 

in purpose, function, style, and collection or analytical techniques. It works on data files that hold 

the source data in their original values (except for minor unit changes and phonetically sensible 

word codes) and provides standardized output data. It is important that users of the PRS and 

CLC output files understand the parsing process, the meanings of field values, and the 

limitations of the usSEABED output. More information about the dbSEABED software can be 

found on the dbSEABED Web site or in the Frequently Asked Questions section of this 

publication. 

Data Import Methods 

Incoming data files number in the hundreds and are diverse in content and format. The 

process of import begins with manual reformatting that usually involves rearranging the data in 

columns specific to each parameter, such as color, percent sand, seabed description, or 

multisensor core logger acoustic velocities. These columns are arranged according to a 

template specific to dbSEABED. Most data are prearranged in columns, but in some cases 

sections of written descriptions may need to be cut into their constituent parts. 

New parameters are sometimes encountered as a data set is imported. These new 

parameters are added to the template at the ends of the appropriate data theme, and the 

dbSEABED processing software is modified to take the new parameter(s) into account if 

possible. For future reference and to help editing, the original data are often held as 

commentary metadata alongside the active data. Some data that are not useful to dbSEABED 

are held only as commentary metadata. 

After import, the data are held in a type of written log arranged according to the nested 

sequence: data set / site / subbottom depth / subsample. Sites are specified by each new 

sampling operation. The written log structure is unusual for a database, having more in common 

with XML-format structure than relational databases. It has distinct advantages for dealing with 

sea-floor sampling data sets, such as 

An algorithm can perform highly useful calculations on the data for each sample, which 

has made it possible to meet user demands in a timely way despite the complexity and size of 

the data holdings; 

I. Data that are human readable, especially if metadata are interspersed; 

II. It conforms with data structures that are generated by core-loggers at sea 

and in the laboratory; 

III. It is efficient to import; 

IV. It is able to cope with variable data quality and incompleteness; and 

V. It is low maintenance, nonproprietary, and programs that address it have 

low cost of entry and are highly adaptable. 

11 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

The disadvantage of the written log structure is that specialized programs, such as those 

in dbSEABED are needed for conversion to the flat-file formats that most users require. These 

flat-file formats are provided in this publication. 

The Numeric Data Type (extracted, EXT) 

A primary function of the processing programs is to read, quality check, and then report 

numerical data that have been obtained from laboratory analyses of grain size, composition, 

color, shear strength, and other parameters. Although we describe these data as "numeric," 

they also include coded data such as Munsell color codes. In many cases, the numeric data can 

be echoed unchanged to outputs (in EXT files), for example, in percent sand, average grain 

sizes, carbonate, and porosities. Checks are performed, however, on whether a value is 

properly numeric or string and if it is within plausible ranges. Problems are reported to a 

diagnostics file that is a basis for quality and completeness checks, with possible corrective 

edits to the data file (along with explanatory metadata). Data items are often deactivated if they 

are suspected as incorrect. 

The numeric data output to EXT files have had minimal manipulation. The data in grainsize analyses (held at their original phi intervals) are summed into gravel, sand, silt, and clay 

percentages; the median, average, and standard deviations are calculated. If grain density is 

available, bulk densities and water contents are converted to porosities, with the porosity 

parameter adopted by dbSEABED. Many parameters that are available in the data are not 

reported to the EXT files, for example, skewness and kurtosis. They may, however, be obtained 

from RDB renderings of the data (not available on this publication). The dbSEABED output of 

Central Grain size is a composite of median (preferred), moment average, and graphical 

averages. Currently, only the second moment (standard deviation) is directly transferred to the 

sorting field. 

The reporting of consistent mappable values for geotechnical and acoustic parameters is 

not an easy task. The results of physical property tests are very dependent on experimental 

setup, such as strain rates, sample preparation, equipment dimensions, and detection of 

behavioral thresholds for the materials. The shear strength reported from dbSEABED is a 

composite of penetrometer, vane-shear values (undrained, unconfined) in the unremolded 

states (that is, for initial failure). Also included for the sake of maximizing mappability are the 

cohesions from shear box and low-pressure triaxial experiments. P-wave acoustic velocities are 

reported without regard to the frequencies of measurement. In both cases, investigators wanting 

more specific information on the analyses can resort to the original data and metadata. The 

extracted outputs based on numeric and coded data are put out separately from the parsed and 

calculated results of dbSEABED. It is recognized that some investigators will choose one over 

the other – or may wish to combine them in different ways. It must also be recognized that rarely 

can a sensible coverage of the seabed be obtained from the extracted data alone, as it is too 

sparse. 

The Linguistic Data Type (parsed, PRS) 

A feature of dbSEABED is its ability to parse word-based descriptive data, such as 

"brown fine sand with abundant shells; seagrass and some pebbles; whiff of H2S?". 

These types of data are held using their original terms although some abbreviation and coding 

is necessary. Thus dbSEABED is not a natural language parser even for the noun-phrase 

constructions, such as the above description. The ability to handle word-based data greatly 

extends the power of the system to map the seabed, because as a global estimate, 

approximately 85 percent or more of data characterizing the seabed are word based. 

12 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Calibrations are performed to validate this process relative to analytical data on the same 

sediments. A simplified description of the processing functions is included in this publication. 

The dbSEABED program applies these concepts to geological descriptions, using: 

• A parser that divides the descriptions into arithmetic equations; 

• A thesaurus that attaches meanings and memberships to the quantifiers, 

modifiers, and Objects; and 

• A linear-weighted assembly of the numerical totals. 

In the dbSEABED program, word memberships can be defined across many 

parameters, not just grain size. Fuzzy memberships are best thought of as a measure of truth or 

possibility (not probability). The outputs are fuzzy memberships of parameters such as mud, 

grain sizes, carbonate, organic carbon, grain types, sedimentary features, rock and weed 

coverages, and engineering strengths.Statistical comparisons can be made between the 

EXT and PRS data outputs, resulting in calibrations which are an overall guide to the accuracy 

of the regional mappings and a highlighting of areas and issues in the data where improvements 

can be made. 

A simplified description of dbSEABED processing 

Most descriptions, such as that noted above, 

"brown fine sand with abundant shells; seagrass and some pebbles; whiff of H2S?". 

consist of quantifiers, modifiers, and objects (qmO) and can be written as linear expressions 

q1*[m1]O1 + q2*[m2]O2 + q3*[m3]O3 ... = sample 

In most cases, the sediment fraction is the whole sample, but dbSEABED records 

explicitly where that is or is not the case in outputs. In the previous example which in 

dbSEABED coding is 

brn fne- snd wi_ab/ shls seagrs + som/ pbls ; whif_of/ h2s /? 

where "-" on modifiers points to modified object, and "/" on quantifiers points to the quantified 

object. The use of abbreviations helps distinguish data from metadata in the data files and 

makes descriptions shorter, easier to process and more human-readable. The qmO coding for 

texture is then 

m(fne)O(snd) + q(wi_ab)O(shls) + q(som)O(pbls) = sample 

where the "brown", "seagrass", and "h2s" are not shown because they are neutral for texture. 

The textural objects are each assigned a grain size that might be cast as Fuzzy Set 

Memberships across a range of grain sizes or may be a single-size fraction percentage (Crisp 

Set). The grain-size assignment is acquired from a dictionary and is usually based on published 

scales, such as Wentworth (1922) and Unified Soil Classification System (USCS), on analysis of 

a region's sediment components, or on the sedimentologic experience of one or more people. 

The grain size is the median of grain sizes observed for sediments that have been labeled 

simply as "sand", which is 1.5 phi. Where a modifer is applied, the grain size is adjusted. In the 

case of modifier "fine" the mean grain size of the sand becomes 2.5 phi. "Shells" has a textural 

meaning, typically at fine gravel (-2 phi) but ranging of course by species and preservation. 

"Pebble" is assigned its Wentworth scale grain size. 

The quantifiers "abundant" and "some" assign weights to the "shell" and "pebble" parts 

and adjust the memberships of the assigned phi grain sizes. These memberships are specified 

in the dictionary: "abundant" 0.5, "some" 0.3. The unquantified "sand" is usually assigned 1.0. 

13 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

After normalization to 1.0 the "sand", "shell", and "pebble" components have weights of 

0.56, 0.28, and 0.17, respectively. (Note: the normalization depends on the syntax, whether like 

the rear-significant ODP syntax, with weights increasing to the right; front significant naval data; 

or flat-significance syntax common in ecologic studies. At data entry which of these applies is 

specified in dbSEABED.) For the standard textural classes, gravel ("shell + pebble") 

membership totals 0.4, sand 0.6, and mud 0.0. (Note: silt and clay proportions cannot be 

determined from visual descriptive data.) 

To estimate the mean grain size for the entire sample, then 

0.56*(2.5 phi) + 0.28*(-2 phi) + 0.17*(-3.5 phi)] = 0.25 phi 

This is reported to the parsed outputs (PRS). The existence of shell and pebbles is also noted in 

the "shell" component outputs (CMP), with a relative membership of 0.28 and 0.17. 

A similar process is performed successively for the other parameters, for consolidation 

(no information here, sediment will be assumed loose), features such as "seagrass", and color. 

"Brown" will cause an output of the Munsell color code of 5YR 4/4 through calibrated processes 

described in Jenkins (2002). 

The numbers and results above are examples only, and the explanation is simplified. 

Iterative comparisons of hundreds of verbal descriptions with each other and with the results of 

lab-based analyses have established that the accuracy is about 1 standard deviation at +/- 2 phi 

range. 

Most input linguistic data are reasonably well organized, although there are a variety of 

descriptive linguistic structures familiar to geologists, ecologists, biologists, U.S. Navy divers, 

and other sea-floor samplers. To be usable in dbSEABED, sediment descriptions and analysis 

data do not need to be precise or fit a particular pattern. The dbSEABED program copes with a 

wide set of vocabularies (for example, foreign language, USACE codes, NOS Bottom Type 

Codes), and a variety of linguistic structures and ways of attaching quantities. There are 

currently more than 5300 terms defined in the parsing dictionary. 

Further, the data need not be absolutely complete. The dbSEABED program mines what 

data are there, giving outputs only where data are sufficiently complete to be reliable, while 

rejecting (and reporting for future attention) incomplete or erroneous structures. 

Each description is kept close to its original form and structure but is coded in 

phonetically sensible terms that include links between quantifiers, modifiers, and objects. Data 

coders choose between a variety of data types to organize the data so the dbSEABED program 

can quickly parse words into values. Table 1 gives the data types used in usSEABED output 

files. 

The dbSEABED program contains a thesaurus where various terms used to describe the 

seabed are given lithologic, textural, and biological classes and weightings. Modifers and 

quantifiers are given relative weightings, and values are assigned to other categories as 

needed. 

Several special semantic structures are catered for, notably the joint abundance 

structure, such as: "snd som/ { pbl + shl + blk- nods }", wherein the pebble, shell and nodules 

total 0.3 in abundance ('som'). Also, a component may be as a proportion of some special 

fraction such as: "snd // acid_residu", in effect the non-carbonate sand proportion. 

The parsing includes a number of quality control devices. If a term is not recognized in 

the dictionary, the process is aborted. The process is also aborted if component weightings from 

certain observations such as grain counts fail to total 100 percent. If a description is too complex 

(currently defined as greater than 32 terms) it is not parsed. Problems encountered are reported 

14 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

to a diagnostics file for later attention and perhaps correction. Homonym terms, such as "dense" 

for consolidation and abundance, are distinguished (as "dens(phy)", "dens(ab)"). Terms that are 

marked "meaning unknown" in the dictionary will cause parsing to fail. Terms that have a 

special meaning in one survey, such as "iron" in DSDP data, are also specially marked 

("iron(dsdp)"). XRD data are not parsed, as they are not regarded as reliable enough in 

comparison to petrologic counts or visual descriptions. At present, the location of structures in a 

core (for example, "below yellow layer") and gradients (for example, "grading upwards to") are 

not parsed. 

More information about the dbSEABED software is obtainable from a number of articles 

listed in Appendix C. Frequently Asked Questions.

Expansion of Data Coverage 

A summary of the theoretical or empirical relationships that are used by dbSEABED to 

expand the coverages of seabed parameters (often not directly measured or calculated in 

individual reports) is given in the onCalculation document (Appendix D). 

Calibration 

dbSEABED is an information-processing system that can perform statistical and 

individual tests of accuracy across the range of output parameters. Issues of accuracy and 

reliability become apparent as soon as data are integrated. Tools for monitoring the integration 

process are required, with feedback to the input data, so that improvements can be made in the 

system. 

Basic uncertainties exist in all the incoming data that cannot be reduced and integrative 

systems cannot proceed past that uncertainty. Parallel studies in dbSEABED have determined 

on the basis of replicate analyses that analytical data, such as grain size analyses (Syvitski and 

others, 1991), has 1-sigma uncertainties on the order of 4 percent of the total parameter range, 

or 0.8 phi. With good maintenance of the data, the outputs from dbSEABED approach those 

levels of reliability. 

Statistical Tests 

In the case of the thousands of samples where both analytical and descriptive data 

exists, a statistical comparison can be made between the EXT and PRS data outputs. The 

results of this calibration are an overall guide to the accuracy of the regional mappings, and a 

highlighting of areas and issues in the data where improvements can be made. Those 

improvements involve both the analytical and descriptive raw input data. For example, grainsize analyses that appear to be the whole sediment but are really only of the sand fraction or 

analyses where gravel and (or) shell has been omitted from an analysis. 

The EXT and PRS outputs are imported into MS Access and links are created between 

the two files (based usually on the SampleKey). Entries with null values (-99) in either EXT or 

PRS are eliminated through a query. This query is brought into MS Excel and used to calculate 

the frequency distribution of deviations (+ and absolute) and plotted for inspection. Percentile 

statistics are calculated using the absolute deviation at the 50 (Median Absolute Deviation 

(MAD)), 68 and 95 percentiles (1s, 2s). Examples of the outputs are shown in the description of 

usSEABED. For most data sets the percentile statistics are 0.4, 0.8, and 4 phi for the 50, 68, 

and 95 percent levels, which may be acceptable over such a diverse set of input data sets but 

can be improved. An example of this analysis is shown in figure 3, for a data set that is under 

improvement. 

15 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

A second way of statistically evaluating the results uses a cross-plot between the EXT 

and PRS output data shown in figure 4. This type of plot serves to highlight some of the issues 

that may reduce the accuracy of dbSEABED with incoming data sets. 

Individual Tests 

The programs of dbSEABED have been equipped to detect problematic data, whether 

by values falling outside plausible limits or by mismatches between EXT and PRS results. 

These tools normally do not prevent the problem values being output, but they do report 

detections to a diagnostics file that is particularly useful in the preparation and cleaning of 

incoming data sets. The statistical data shown in figure 3 is employed to set the filters, usually at 

the 68 percent (1s) level. The original data can then be revisited, checked for issues such as 

those shown in figure 4, and can be corrected, deactivated, or left alone as appropriate. 

16 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

DATA CATALOG 

The data supplied in this publication are made available with geographic coordinates to 

allow the data to be incorporated into a Geographic Information System (GIS). The data layers 

along with additional base-map layers have been compiled into an ESRITM ArcView® project file 

(usSEABED_Pacific.apr, 32 MB zip file), which is located in the Data folder of this publication. 

The project file serves to provide examples of how the data can be displayed in a GIS (figure 5 

a-c). It contains several views demonstrating the possibilities of the various data fields. A 

variety of base map layers that can be used to accompany these data can be found on the 

Coastal and Marine Geology Program's U.S. Pacific West Coast Map Server. Several have 

been included below and are used in the project file. Other examples of ways to visualize these 

data are also included. 

For those who do not have the ESRITM software or a compatible GIS data browser 

available on their computer, a free viewer, ArcExplorer®, is available from ESRITM 

(http://www.esri.com/). Please note that the ArcExplorer® software is limited to the Microsoft 

Windows operating systems. 

Clicking on the layer name under the column header "Data Layer Name & Description" 

in the tables below will open a new window with a graphical representation of that layer. Federal 

Geographic Data Committee (FGDC) metadata are included with data layers in four formats in 

the tables below: (HTML, FAQ, XML, and text). 

A downloadable zip archive file containing the elements that comprise the ArcView 

shapefile for each data layer is also provided. In addition to the ArcView® shapefile, the 

usSEABED data layers are available in an ASCII text format as an alternate way to view and 

examine the data sets. The first record of the ASCII file contains the name of the data fields for 

that file. Each zip file includes: 

• ArcView® shapefile for each layer (with associated files); 

• Comma-delimited text version of the data file; 

• Metadata to accompany the data file (four versions); 

• Browse graphic of the data layer; and a 

• A readme file. 

The zip files were created using WinZip v. 9.0. Users may obtain a free version of the 

software from http://www.winzip.com/. 

Data Files 

Table 7 lists the usSEABED data layer name and description, metadata files, and zipped 

file names and sizes. Table 8 gives a list of base map layers available, metadata files, and 

zipped file names and sizes. 

A comma-delimited text file (PAC_SRC) of the list of sources is included with the output 

files. The DataSetKey number within this file gives a relational link between the source data set 

and the data files in tables 7 and 8. Also provided is a list of the data sources in bibliographic 

format (Appendix A). 

Legends 

To map the coded information on Color and Roughness in a GIS, load the ArcView®

legends "munsell.avl" or "rgh_pt.avl" which are available with the database. ArcView® legends 

17 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

may be imported into ArcGIS®. To make your own legends for other applications, employ a 

classification that uses a "unique value" process. 

Color 

Color of sediment is described either in terms (brown, light greenish gray) or in Munsell 

color codes given in values of hue (spectral content), value (lightness), and chroma (saturation). 

Munsell codes are explained in a publication of the Geological Society of America (Goddard, 

and others, 1951).The dbSEABED program converts the former into average values of Munsell 

codes, rounded to increments of 5 in hue, 3 in value, and 3 in chroma (Jenkins, 2003). An 

ESRITM ArcView® legend is included for ease of mapping. 

Roughness 

This is a coded output representing the V:H of the seabed roughness element which is 

observed with greatest aspect ratio. That feature may be fixed roughness like a cobble, or 

moveable roughness like ripples. The outputs can only report observed roughness elements, so 

are influenced by the size scales of samplers and observations. The V and H values are the 

centimeter values of the height and horizontal dimensions written in integer log 2 (base 2). For 

example "4:6" represents 16 cm height over length scale of 64 cm. Powers <0 are set to zero 

(i.e., scales <1 cm are not considered). The horizontal length H is the length of expression of a 

feature, rather than wavelength of repetition. Where a feature is elongated, H is taken normal to 

elongation (i.e., equals ripple wavelength). 

18 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Acknowledgements 

We thank the following people and agencies for their contribution of data to usSEABED 

on the Pacific coast: 

Clark Alexander, Skidaway Institution of Oceanography, Savannah, Georgia; Jeff 

Borgeld, Humboldt State University, Arcata, Calif.; Larry Cooper, Southern California Coastal 

Water Research Project, Westminster, Calif.; Donn Gorsline, University of Southern California, 

Los Angeles, Calif.; Rick Fletcher, Olympic Coast National Marine Sanctuary, Port Angeles, 

Wash.;Brian Foss, Santa Cruz Harbor, Santa Cruz, Calif.; Charles Nittrouer, University of 

Washington, Seattle, Wash; Chris Rooper, University of Washington, Seattle, Wash.; Scott 

Wing and Anna Weitzman, Smithsonian Institution, Washington D.C.; and Moss Landing 

Harbor, Moss Landing, Calif. 

We thank the following interns for their patient assistance in entry, coding, and testing of 

data and assistance with metadata: K. Halimeda Kilbourne, Carolynn Box, Tara Kneeshaw, 

Jennifer Mendonca, April Villagomez, Monica Iglecia, and Adam Jackson. Guy Cochrane and 

Page Valentine helped with the description of the USGS National Sea-Floor Mapping and 

Benthic Habitats projects. 

We thank VeeAnn Cross, Jim Flocks, Jodi Harney, Guy Cochrane, Debbie Hutchinson, 

Don Woodrow, Rob Thieler, and Kathy Scanlon, all at the USGS, for their thoughtful and 

thorough reviews; and Carolyn Degnan and Valerie Paskevich (USGS) for their insightful 

reviews of the metadata. Jim Gardner, then at the USGS, was instrumental in the creation of 

usSEABED. We also thank John Goff (University of Texas) and Matt Arsenault (USGS) for their 

quality-control testing of the data and formats. 

dbSEABED has benefited from the contributions of many people and institutions. It is a 

community structure, currently managed from the University of Colorado. Funding from the 

Australian Department of Defence, Commonwealth Scientific and Industrial Research 

Organisation (CSIRO) Australia, Geosciences Australia, Institute of Arctic and Alpine Research 

(INSTAAR) / University of Colorado, Institute fur Ostseewissenschaften-Warnemunde (IOW, 

Germany), Lamont Doherty Earth Observatory, NOAA National Geophysical Data Center 

(Boulder), ONR (Office of Naval Research), and Victorian DNR (Australia). Mike Field and Jim 

Gardner, who first arranged to apply dbSEABED to the U.S. EEZ, in 1999. Ideas for 

development of dbSEABED have been contributed in discussions by L. Hamilton and P. 

Mulhearn (Defence Science and Technology Organization (DSTO)), G. Rawson, A. Short (Univ. 

Sydney), P. Sliogeris (Royal Australian Navy METOC Services (Australia)), T. Wever 

(Forschungsanstalt der Bundeswehr für Wasserschall und Geophysik, Germany (FWG)), J. 

Harff, B. Bobertz and B. Bohling (IOW), P. Morin (Univ. Minnesota), M. Kulp and S. Briuglio 

(Univ. New Orleans), J. Goff (Univ. Texas), G. Sharman and C. Moore (NOAA/NGDC), and J. 

Flocks and C .Polloni (USGS). 

19 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

References cited 

Black, K.S., Tolhurst, T.J., Paterson, D.M., and Hagerthey, S.E., 2002, Working with natural 

cohesive sediments: Journal of Hydraulic Engineering, v. 128, no. 1, p. 2-8. 

Buczkowski, B. J., Reid, J.A., Jenkins, C.J., Reid, J.M., Williams, S.J., Flocks, J.G., 2006, 

usSEABED: Gulf of Mexico and Caribbean Offshore Surficial-Sediment Data Release; U.S. 

Geological Survey Data Series 146, version 1.0, online at 

http://pubs.usgs.gov/ds/2006/146. 

Folk, R.L., 1954, The distinction between grain size and mineral composition in sedimentary 

rock nomenclature: Journal of Geology, v. 62, no.4, p. 344-359. 

Folk, R.L., 1974, The petrology of sedimentary rocks: Austin, Tex., Hemphill Publishing Co., 182 

p. 

Gassmann, F., 1951, Elastic waves through a packing of spheres: Geophysics, v. 16, no. 673-

685. 

Goddard E.N., Trask, P.D., de Ford, R.K., Rove, O.N., Singewald, J.T. and Overbeck, R.M., 

1951, Rock Color Chart: Geological Society of America, 6 p. 

Jenkins, C.J., 1997, Building offshore soils databases: Sea Technology, v. 38, no. 12, p. 25-28.* 

Jenkins, C., 2002, Automated digital mapping of geological colour descriptions: Geo-Marine 

Letters, v. 22, no. 4, p.181-187.* 

Jenkins, C., 2003, Data management of MARGINS geologic data, with emphasis on efficiency, 

quality control and data integration: MARGINS Newsletter, number 10, Spring 2003, p. 8-

10.* 

Jimenez, J.A., and Madsen, O.S., 2003, A simple formula to estimate settling velocity of natural 

sediments: Journal of Waterway, Port, Coastal and Ocean Engineering, March/April 2003, 

p. 70-78. 

Kirchner, J.W., Dietrich, W.E., Iseya, F., and Ikeda, H., 1990, The variability of critical shear 

stress, friction angle, and grain protrusion in water-worked sediments: Sedimentology, v. 

37, p. 647-672. 

National Ocean Service (NOS), 1997, Chart no. 1, United States of America, Nautical chart 

symbols, abbreviations and terms: U.S. National Ocean Service [Chart]. 

Poppe, L.J., Eliason, A.H., Fredericks, J.J., Rendigs, R.R., Blackwood, D., and Polloni, C.F., 

2000, Grain size analysis of marine sediments: methodology and data processing, in

Poppe, L.J., and Polloni, C.F., eds., USGS east-coast sediment analysis; procedures, 

database, and georeferenced displays: U.S. Geological Survey Open-File Report 00-358, 

one CD-ROM. 

Reid, J.M., Reid, J.A., Jenkins, C.J., Hastings, M.E., Williams, S.J., and Poppe, L.J., 2005, 

usSEABED: Atlantic Coast Offshore Surficial-Sediment Data Release; U.S. Geological 

Survey Data Series 118, version 1.0. Online at http://pubs.usgs.gov/ds/2005/118. 

20 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Richardson, M.D., and Briggs, K.B., 1993, On the use of acoustic impedance values to 

determine sediment properties: Proceedings of Instuments of Acoustics, v. 15, p. 15-24. 

Shepard, F.P., 1954, Nomenclature based on sand-silt-clay ratios: Journal of Sedimentary 

Petrology, v. 24, p. 151-158. 

Syvitski, J.P.M., LeBlanc, K.W.G., and Asprey, K.W., 1991, Interlaboratory, interinstrument 

calibration experiments, in Syvitski, J.P.M., ed., 1991, Principles, methods, and application 

of particle size analysis: Cambridge, Cambridge University Press, p. 174-193. 

Thorsos, E.I., Williams, K.L., Jackson, D.R., Richardson, M.D., Briggs, K.B., and Tang, D., 

2001, An experiment in high-frequency sediment acoustics; SAX99: IEEE Journal of 

Oceanic Engineering, v. 26, p. 4-25. 

UK Hydrographic Office (UKHO), 2005, Chart symbols and abbreviations: Chart BA 5011 

[Booklet], UK Hydrographic Office, 38 p. 

Wentworth, C.K., 1922, A scale of grade and class terms for clastic sediments: Journal of 

Geology, v. 30, p. 377-392. 

Whitehouse, R., Soulsby, R., Roberts, W., and Mitchener, H., 2000, Dynamics of estuarine 

muds; A manual for practical applications: London, Thomas Telford, 209 p. 

Williams, S.J., Jenkins, C., Currence, J.M., Penland, S., Reid, J., Flocks, J., Kindinger, J., 

Poppe, L., Kulp, M., Manheim, F., Hampton, M., Polloni, C., and Rowland, J., 2003, New 

digital maps of U.S. continental margins; Insights to seafloor sedimentary character, 

aggregate resources and processes: Proceedings of the International Conference on 

Coastal Sediments 2003: Corpus Christi, Texas, World Scientific Publishing Corporation 

and East Meets West Productions, Corpus Christi, one CD-ROM. 

Wyllie, M., Gardner, G., and Gregory, A., 1963, Studies of elastic wave attenuation in porous 

media: Geophysics, v. 27, p. 569-589. 

*Reprints of these articles are included in this publication 

. 

21 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Figure 1: usSEABED data for the Pacific coast showing the 

locations of the extracted (EXT, in red) and parsed (PRS, in yellow) 

outputs. The EXT data are from numeric, lab-based analyses. The 

PRS data consist of numeric values parsed from text-based 

descriptions. Black line delineates the limit of the U.S. Exclusive 

Economic Zone. back

22 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Figure 2. Marine sand bodies, having diverse origins and evolutionary histories, can be 

buried or exposed on continental shelves and often have been greatly modified by marine 

processes associated with the Holocene transgression. Nearshore marine sand bodies of 

the types shown above may offer the best potential sources for high quality sand for beach 

nourishment. (Williams and others, 2003). back

23 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Figure 3: Statistical calibration of outputs for grain sizes, shown using a frequency plot of the 

deviations between PRS and EXT data, using an improving Atlantic Coast data set. Deviations 

are the results of inaccuracies in the EXT and PRS input data, as well as in identifiable issues in 

the data as highlighted below in figure 4. The 50, 68, and 95 percent confidences are 90.8, 1.3, 

4.3 phi, respectively. back

24 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Figure 4: Crossplot of lab-based grain size values (EXT) against grain size values derived from 

word-based descriptions from the same samples. Areas of large differences noted by letters: 

A. PRS coarser than GRZ, apparently due to outsized shells / clasts being omitted from lab 

grain size analyses; B. Sediment described as very fine in PRS, but only the sand fraction is 

represented by the EXT analysis data; C. Detailed analyses of grain sizes does not go beyond 

coarsest class of about -2.5 phi; and D. Descriptive PRS data does not distinguish grades of 

sand, and is apparently dominated by reports of very large clasts, such as cobbles or shell, that 

were not analyzed. With the detection and fixing of these problems the accuracy of outputs is 

substantially improved over that shown here. Notice that overall the PRS outputs extend further 

in coarse grades and the EXT outputs extend further in the fine grades, reflecting their common 

observational biases. back

25 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Figure 5a. Example of usSEABED data: grain-size distributions of sand (yellows) and mud 

(greens) with areas of hard-bottom (purples) off Oregon, using extracted (EXT) and parsed data 

(PRS). Image created in a GIS. back

26 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Figure 5b. Example of usSEABED data: relative presence of phosphorite in southern California 

using the component (CMP) data. Image created in a GIS. back

27 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Figure 5c. Example of usSEABED data: presence of shells (orange) and worms (blues) in 

central California using the facies (FAC) file. Image created in a GIS. back

28 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Table 1. Key to data themes in usSEABED output files 

back 

Acronym Meaning 

ACU Acoustic properties 

BIO Biota descriptions 

CMP Sediment composition analyses 

COL Sediment color 

GRZ Grain size analyses 

GTC Geotechnical properties 

LTH Lithologic descriptions 

MSL Multisensor core-logger analyses 

PET Grain petrologic analyses 

SFT Sea-floor type descriptions 

TXG Graphical texture statistics 

TXR Texture and statistics 

Table 2. usSEABED output files 

back

Data File Contents 

EXT Extracted (numeric, lab-based) 

PRS Parsed (word-based) 

CLC Calculated (calculated variables) 

CMP Components (content and features) 

FAC Facies (components only) 

SRC Source information 

29 
Reid and others, 2006, usSEABED Pacific Coast Surficial-

U.S. Geological 

Table 3. Field parameters, format, units, range, meaning, and comments for the extracted (EXT)

and calculated (CLC) data files 

backField Name Parameter Data Format Units, Range, Meaning Comment Latitude Latitude Decimal 00.00000 Decimal degrees, 90° to - 90° range World Geodetic System 1984 (Longitude Longitude Decimal 000.00000 Decimal degrees, -180° to 180° range WGS 84 Spheroid. WaterDepth Water depth Integer 00000 Meters Not always tidally correct. SampleTop Sample top Decimal 000.00 Meters below seabed surface Sample top as noted in source SampleBase Sample base Decimal 000.00 Meters below seabed surface Sample bottom as noted in souSiteName Site name Character XXX: XXX 

Survey or 

laboratory code 

for the sampling 

site 

Not unique; Site name as givesometimes linked to cruise naminformation to decrease sitena

DataSetKey Dataset number key Integer 000 For audit only Relational key to data source (

contains links to source metad

SiteKey Site number key Integer 0000000 For audit only 

Relational key to other data filesequentially as total output; comore than one sample per site

SampleKey Sample number key Integer 0000000 For audit only Relational key to other data file

sequentially as total output; Mube at each site (that is, within c

Sampler Sampler type Character Xxxxxxxx.... Type of sampling device 

As given in source report; recopenetration ("pen") length appesource report. For more complsampler, see source metadata
Reid and others, 2006, usSEABED Pacific Coast Surficial-

U.S. Geological 

DataType Data types Character XXX: XXX For audit principally Source data types (table 1). 

Gravel Gravel Integer 000 Gravel grain size fraction, % Textural class. Sand Sand Integer 000 Sand grain size fraction, % Textural class. Mud Mud Integer 000 Mud grain size fraction, % Textural class. Clay Clay Integer 000 Clay grain size fraction, % Textural class; output for EXT 

can be determined only by ana

Grain size Grain size Decimal 00.00 Phi characteristic grain size Consensus of mean and mediaSorting Sorting Decimal 0.00 Phi grain size dispersion Standard deviation, sorting onlSeafloorClass Seafloor class Character Xxxxx... 

That class (or 

facies) with the 

maximum fuzzy 

membership, if 

above 30% 

Output for PRS table only. 

ClassMbrshp Class membership Decimal 000 

Fuzzy 

membership (%) 

of the class (or 

facies), noted 

above 

Output for PRS table only. 

Folk Folk classification Character xx.X... Shepard Shepard classification Character XXX...RockMbrshp Rock index Integer 000 Fuzzy membership (%) Membership of sample to ‘rock

only in PRS data 

WeedMbrshp Weed index Integer 000 Fuzzy membership (%) Membership of sample to wee

only in PRS data 

Carbonate Carbonate Integer 000 

%; may be Fuzzy 

membership 

(PRS) 
Reid and others, 2006, usSEABED Pacific Coast Surficial-

U.S. Geological 

MunsellCode Munsell color code Character XXXXX 

Standard 

alphanumeric 

coding of color 

partitioned into 

Hue, Value, and 

Chroma 

Ex: "5YR 6/4", See "Rock-ColoSociety of America, 1991). 

OrganicCarbon Organic carbon Integer 000 % Minimum value from descriptio

0.1%. 

ShearStrength Log shear strength Decimal 00.0 kiloPascals, undrained, unconfined From a variety of instrumentatiPorosity Porosity Decimal 00.00 % P-waveVelocity P-wave velocity Decimal 00.0 m/sec Usually not corrected for P/T eBottom Roughness Roughness Decimal 0000.00 

Coded to 

express the 

height and length 

of the bottom 

feature with 

greatest aspect 

ratio 

In a coding that expresses the the bottom feature with greatescoded output representing the element with greatest aspect rexpressed as (rounded) intege

CriticalShearStress Log critical shear stress Decimal 0000.00 Log10 of Tau in kPa 

Log 10 of tau in kPa, being the required to initiate easily obsertransport, whether by traction ofrom a compilation of published ranging from large boulder to mrange of grain shapes (for exa
Reid and others, 2006, usSEABED Pacific Coast Surficial-

U.S. Geological 

Sample phase Where in sample the data are from Character Xxxxx.... Where sample is from 

Records whether the results asediment, or just to some specinside a nodule, burrow-infill, thporewater (chemistry), a layer gradient observed in the core, specimen, a layer that is not psample with questionable locata type of analysis or observatiopotentially unrepresentative (e(XRD) smear slide (XRD). Outbased description that may invfield will need to be selected amappings of the bulk sedient cmapped. Only blank entries shsuch a mapping. 
Reid and others, 2006, usSEABED Pacific Coast Surficial-

U.S. Geological 

Table 4. Components (features_F) processed within usSEABED (data file CMP)Only the descriptive terms found in source reports are defined in the dbSEABED thesaurus. Conversely, as usS

same thesaurus as its sister data compilations (auSEABED, goSEABED), some terms listed below may not occOnly one of possible variations is listed below; for example, laminated (laminae, lamination), and mollusc (mollu

Senior synonym Triggering Words (word variations not included) andest andesite, augite andesite, benmoreite, trachyandesite anmne_F anemone, tube anemone, cerinth, cerianthid, coryanactid annld_F annelid, arenicola, beachworm, bloodworm, bristleworm, funnelworm, nereid worm, polycharen_frm arenaceous foraminfera, agglutinated foramifera, ammobaculite, ammodiscus, textularid foartif_F artificial, soot, anchor, brass, cinder, coal, contaminated, lumber, obstruction, petroleum, oi

snag, tar, wood chip, wreck 

asterd_F asteroid, basket star, briseaster, sea star, starfish barit barite (-concretion -vein) baslt basalt, diorite, metabasalt, scoria, trap rock, trachybasalt bioturb bioturbation bitumn bitumin biv bivalve, arctica, astarte, cardium, chama, chione, chlmys, clam (-shell -flat material -hash -v

(anadara -shell), donax, glycymeris, katalysia, lamellibranch, macoma, mercenaria, mulinia-shell), mya, mytilus, nucula, pelecypod, quahog, rangia, seep mytilid, slipper shells, surf clvenerid, venus clams, vesicomyid, yoldia 

bluschst blue schist, crossite-albite schist, crossite-quartz schist, glaucophane, quartz crossite schis

glaucophane schist 

bnth_frm benthic foraminfera, archaias, bolivina, bulimina, coralline forams, discorbis, eponides, hom

lenticulina, loxostema, miliolid, nodosirid, nonien, notosirid, peneroplis, porcellanous, rotaiid

borng_F boring, bioeroded brach brachiopod, lingula brncl barnacle bryz bryozoa, polyzoa burw_F burrow, chondrite, clam siphon, crab hole, lebensspurren, Thalassinoides c_alg calcareous algae, purple algae, red algae 
Reid and others, 2006, usSEABED Pacific Coast Surficial-

U.S. Geological 

calc_ooz calcareous ooze, nannofossil (-mud -ooze), pteropod (-mud -ooze), foraminiferal (-marl -oo

(-mud -ooze) 

calcrst calcareous crust, tufa calct calcite (-cement -core -filling -veinlets) carb allogenic grain, authigenic carbonate, biogenic, calcareous, calcilutite, calcarenite, calcirud

biogenic, carbonate, limey, marl, skeletal micrite 

chrcoal_F charcoal, fire debris chrt chert, flint, porcellanite claymin clay mineral, bentonite, chlorite, collophane, illite, kaolinite clypeast clypeasteriod, sand dollar coal coal, lignite, bituminous coralgl algal coral, coralgal crab crab, hermit crab, sand crab, spider crab, swimming crab crinod_F crinoid, basket star crl coral, Acropora palmata, brain coral, Dendrophyllia, Madrepore, Manicina, Porite, sea twig crl_dbr coral debris crlrf coral reef, coral heads, shingle bank, reefal shoal crnalg coralline algae, calcareous algae, lithothamnion crustac crustacea, decapods, lobster, shrimp shell defrmn_F deformation, convolute, flame structure, flow structure, load (-cast -structure), pull apart diat diatom, diatomite/diatomaceous dolmt dolomite, ankerite, molar magnesium carbonate echnd echinoid, heart urchin, keyhole urchin, sea urchin, spiny urchin echndrm_F echinoderm fault_F fault fces feces, coprolite ferug ferruginous, iron fragment, iron (-cement -streak -flake -stain), iron stone, laterite, limonite flasr_bed_F flaser bed fld feldspar, albite, andesine, anorthorite, K-feldspar, labradorite, orthoclase, plagioclase frm calcareous foramifera, foraminifera, globigerina bit, planktonic gas foamy, gas 
Reid and others, 2006, usSEABED Pacific Coast Surficial-

U.S. Geological 

gbbro gabbro, diabase, diorite, dolerite, meta-dolerite, monzodiorite, monzonite, quartz diorite 

glacl glacial, diamicton, erratic, moraine, till glauc glauconite, greensand gniss gneiss, diorite gneiss, granite gneiss gradd_F coarsening upward, fining upward, increasing grain size, normally graded, reverse graded granit granite, aplite, granodiorite, pegmatite grnschst greenschist gstrpd gastropod, cerithium, conch, turitella, snail, nassarius, olivella, tenebrae, turitella h2s hydrogen sulfide, hydrogen sulfide (-odor -smell), sulfur odor halmda halimeda, Peyssonnelia holoth holothurian, sea cucumber hvy_min heavy mineral, anatase, andalusite, apatite, black sand, brookite, cassiterite, clinozoisite, c

dumortierite, epidote, garnet, ilmenite, jadeite, kyanite, leucoxene, magnetite, monazite, ore piedmontite, rutile, sillimanite, sphene, spinel, staurolite, titanomagnetite, titanite, tourmalinzoisite 

hydrt hydrate, gas hydrate ign_rck igneous rock, acidic rock, alkali basinite, augite plagioclase porphyry, augite porphyry, basi

olivine plagioclase clinopyroxene, olivine plagioclase phyric, plagioclase andesite porphyryporphyry, plagioclase porphyry, plutonic rock, porphyry, rhyolite, syenite, trachyte 

klp_F kelp, brown algae, ecklonia, M. vertebralis, red brown algae lamintd_F laminated lenticlr_bed lenticular bed, lenticular mass limstn limestone, beach rock, bioclastic (-floatstone -grainstone -limestone -rudstone), boundston

floatstone -grainstone -rudstone), calcareous (-chip -rubble -rock), coral limestone, floatstopackstone, rudstone, wackestone 

lmp_F lump, aggregate, ball, cast, clump, compact clot, intraclast, pellet, pisolitic, peloid lrg_frm large foram, foraminferal gravel, amphistegina, heterostegina, macro foraminifera, marginomaf mafic, actinolite, aegirite, amphibole, augite, (brown- green- basaltic-) hornblende, bronzite

ferromagnesian, hypersthene, olivine, orthopyroxene, oxyhornblende, pyroxene, titanaugitetremolite 

met metamorphic, calcsilicate, granitized, mylonite, porphyroblast, saussurite methne methane metlif metalliferous 
Reid and others, 2006, usSEABED Pacific Coast Surficial-

U.S. Geological 

mica mica, biotite, chlorite, muscovite, sericite, talc 

mlsc mollusc mn_crst manganese crust, manganese iron oxide crust, manganese nodule, manganese pavement

phosphate material 

mn_nod manganese nodule, iron manganese nodule, manganese concretion, micronodule mnoxd manganese oxide, iron-manganese (-coat -stain -veneer), iron-manganese oxide motl_F mottle, chickwire mottle mudlmp_F mud lump, armored mud ball, silty lump, clay (-aggregate -ball -chip -clast -gall -lump -mas

aggregate -ball -chunk -clump -clot -clast -lump -pebble -pellet), claystone (-chip -gall), sanpebble, shale (-fragment -concretion) 

mudstn mudstone, calcareous (-mudstone- siltstone), clay (-rock -shale -stone), marlstone, mud (-r

shale, siliceous shale, siltstone 

nan nannofossil coccolith, nannofossil (-coccolith- ooze), silicoflagellate nod_F nodule, concretion odr odor, anoxic, fetid, foul, fishy, organic, sewage, smell oil oil, oil glob, oil sheen ool oolite, sporbo ooz ooze ophiurd_F ophiuroid, brittle star, ophiomusium orgcbn organic carbon, carbonaceous, organic (-streak -detritus -matter -mud -content -enriched -m

-rich -rimmed), sapropel 

oyst oyster, jingle shell peat peat, lignite pelag pelagic, hemipelagic, planktic, planktonic phspht phosphate, phosphorite pit_F pit, crater, feeding depression, hole, pockmark, mound, resting trace planr_bed_F planar bed plnk_frm planktonic foramifera, globerina, globorotalid, planktic foraminfera plnt_F plant, mangrove, root, vegetation, weed, root ptr pteropod pumc pumice, ash pyrt pyrite, marcasite 
Reid and others, 2006, usSEABED Pacific Coast Surficial-

U.S. Geological 

qtz quartz, arkosic sand, calcareous quartz sand, milky vein quartz, quartz (-content -fragment 

groundmass -mass -rich -vein -veinlet -crystal), quartzose, quartzite (-cobble -gravel -pebb

chunk -fragment), silica 

rad radiolaria ripl ripple, bedform rlct_F relict root_struct root structure, root clast, root trace rzr_clm razor clam, ensis, pinna, pteria, pelecypod schst schist, (-albite-chlorite-epidote, -albite-chlorite, -albite-mica, -albite-quartz-chlorite, -biotit -q

-chlorite-quartz-albite, -chlorite, -phyllitic, -quartz-albite, -quartz-albite-chlorite, -quartz-biotit

scllp scallop, astropecten, pecten, placopecten scour scour, crag and tail, erosional, lag deposit scphpd scaphopod, dentalium seagrs_F seagrass, acetabularia, amphibolis, batophora, eel grass, grass, halophila, heterozostera, p

posidonia, sargassum, strap grass, syringodium, manatee grass, thallassia, zostera 

sft_alg_F soft algae, algal (-scum -filament -mush -strand), Bossea, green algae, macrophytic, red alsftcrl_F soft coral, alcynacian, ascidian, coelentrate, gorgonian, hydrozoa shl shell, shell (-bed -bank -carpet -fraction -content -material), shellfish, valves shl_dbr shell debris, shell hash, coquina, shell (-bit -conglomerate -fragments -festoon -grit -lag -ma

particle) 

shrmp_F shrimp, amphipod, ampelisca, copepod, isopod, tanid sidrt siderite, siderite nodule sil_ooz siliceous ooze, siliceous mud slte slate, phyllite, quartzite, metamorphic rock sndstn sandstone, gritstone, graywacke, labile sandstone, sandstone reef, wacke sol_crl solitary coral, cup coral, disc coral, horn coral, lophelia coral spng_F sponge, calcareous sponge, glass sponge, hard sponge, hexactinellid sponge, porifera, Th

sponge 

spoil_F spoil, brick, coke, dumped sediment srpul serpulid, serpulid tube, serpulid worm tube sulf sulfide, chalcopyrite trail_F trail, trace (animal), track 
Reid and others, 2006, usSEABED Pacific Coast Surficial-

U.S. Geological 

trrg terrigenous, lithic, inorganic 

umafic ultramafic, amphibolite, anorthosite, dunite, greenstone, harzburgite, lherzolite, norite, ortho

periodotite, picrite, pyroxenite, serpentinite, troctolite, wehrlite 

vol_rck volcanic rock, volcanic -cobble -pebble volgls volcanic glass, obsidian, hyaloclastite, pyroclastic, quenched, vitric, subvitreous volrck volcanic rock, welded tuff volsed volcanic sediment, ash, tuff, lapilli wood wood, bark, twig wrm_F worm, chordate, echiurid, (fan- flat- glob- juicy- long- sand-) tube worm, maldanid, pogonop

sliverfish, siphunculid, tunicate 

wrm_tbe_F worm tube (-agglutinated -amphipod -annelid -arenicola -chitinous -diopatra -polychaete - p

vestimetiform) 

wavy_bed_F wavy bed 
Reid and others, 2006, usSEABED Pacific Coast Surficial-

U.S. Geological 

Table 5. Facies and their component makeup (data file FAC) Facies values are determined by a combination of components and their mined values from word-based descriptextural, geochemical, and geophysical information held in PRS data files. Values represent memberships to fuzpercents. A minimum of 30 percent component presence is required to trip a given facies, and a component mafacies. See the facies (FAC) file for actual data, and table 4 for component information. Facies notes presence obackField Name Parameter Data Format, units Information/ triggering componentLatitude Latitude Decimal 00.00000 Decimal degrees, 90° to -90° range Longitude Longitude Decimal 000.00000 Decimal degrees, -180° to 180° range WaterDepth Water depth Integer 00000 Meters SampleTop Sample top Decimal 000.00 Meters below seabed surface SampleBase Sample base Decimal 000.00 Meters below seabed surface SiteName Site name Character XXX: XXX Survey or laboratory code for the samDataSetKey Dataset number key Integer 000 Relational key to data source (SRC) f

links to source metadata 

SiteKey Site number key Integer 0000000 

Relational key to other data files. Eacsequentially as total output; core data one sample per site. 

SampleKey Sample number key Integer 0000000 

Relational key to other data files. Eacsequentially as total output; Multiple seach site (i.e., in core). 

Terrigenous Terrigenous (%) Fld, hvy_min, maf, mica, qtz, trrg Carbonate Carbonate (%) Calcrst, calct, carb, dolmt, limstn, sidIgneous Igneous (%) Andest, baslt, gbbro, granit, ign_rck, Volcanic Volcanic (%) Baslt, pumc, vol_rck, volgls, volrck, vMetamorphic Metamorphic (%) Bluschst, gniss, grnschst, met, schst, Mineralized Mineralized (%) Barit, metlif, phspht, pyrt, sulf AuthFeMn Authigenic Fe Mn (%) Mn_crust, mn_nod, mnoxd, ferug Ooze Ooze (%) Ooz, calc_ooz, sil_ooz Carbon Carbon (%) Coal, bitumn, orgcbn, peat 
Reid and others, 2006, usSEABED Pacific Coast Surficial-

U.S. Geological 

GeochemSignal Geochemical signal (%) Gas, h2s, hydrt, methne, odr, oil 

Forams Forams (%) Aren_frm, bnth_frm, frm, lrg_frm, plnkOtherCalcPelag Other calcareous pelagics (%) Nan, ptr, calc_ooz SilcPelag Siliceous pelagics (%) Diat, rad, sil_ooz Shell Shell (%) Shl, shl_dbr Coral Coral (%) Crl, crl_dbr, crlrf, sol_crl HardPlant Hard plants (%) C_alg, coralgl, crnalg, halmda 
Reid and others, 2006, usSEABED Pacific Coast Surficial-

U.S. Geological 

Table 6. Most frequently occurring biological components that may have textural implications (

back

barnacles coralline algae fish debris_F pteropods serbivalves corals forams radiolaria shebrachiopods crabs halimeda razor clams spobryozoa crustaceans molluscs reefs wocalcareous algae diatoms nannofossils scaphopods clypeasts echinoids 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Table 7. usSEABED Pacific (California, Oregon, Washington) data

back

Data Layer Name 

& Description Metadata Files File Size 

pac_ext usSEABED 

extracted data for the 

U.S. West Coast 

HTML 

FAQ 

XML 

txt

pac_ext.zip 1.0 MB 

pac_prs - usSEABED 

parsed data for the 

U.S. West Coast 

HTML 

FAQ 

XML 

txt

pac_prs.zip 859 KB 

pac_clc - usSEABED 

calculated data for 

the U.S. West Coast 

HTML 

FAQ 

XML 

txt

pac_clc.zip 1.5 MB 

pac_cmp - 

usSEABED 

component data for 

the U.S. West Coast 

HTML

FAQ 

XML

txt

pac_cmp.zip 601 KB 

pac_fac - usSEABED 

facies data for the 

U.S. West Coast 

HTML 

FAQ

XML 

txt

pac_fac.zip 380 KB 

43 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Table 8. Base-map layers 

back

Data Layer Name 

& Description Metadata Files File Size 

NOS80K - Medium 

Resolution Digital 

Vector Shoreline 

(Source: NOAA) 

HTML

FAQ

txt

nos80k.zip 25.9 MB 

U.S. EEZ Boundary - 

Boundaries of the 

Exclusive Economic 

Zone (EEZ) 

(Source: NOAA) 

HTML

FAQ

txt

useez.zip 179 KB 

State Boundaries - 

internal U.S. State 

boundaries 

(Source: 

USGS/CMGP) 

HTML

FAQ

txt

state_bounds.zip 1.7 MB 

44 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Appendix A. Data Sources 

Achstetter, Eugene V., Kelly, Eugene V., Loomis, P. Burr, McKellar, Scott M., 1970, A summary 

of sediment size composition and engineering properties of three cores from the eastern 

Pacific April 1970: U.S. Naval Oceanographic Office (NAVOCEANO) Laboratory Item 398, 

16 p. National Geophysical Data Center (MGG_09695001, data set 383). 

Achstetter. Eugene V., P. Burr Loomis, and Cary M. Ross, 1970, A summary of sediment size 

and compositions of twelve grabs, May 1970: U.S. Naval Oceanographic Office 

(NAVOCEANO) Laboratory Item 400, 19 p., National Geophysical Data Center 

(MGG_09625001, data set 375). 

Anderson, Franz E., 1967, Stratigraphy of later Pleistocene and Holocene sediments from the 

Strait of Juan de Fuca: Seattle, University of Washington, Ph.D. dissertation, 167 p. 

(Anderson_PhD_1967, data set 393). 

Andrews, Robert S., 1965, Modern sediments of Willapa Bay, Washington: A coastal plain 

estuary: Seattle, University of Washington, Department of Oceanography Technical Report 

no. 118, Reference M65-8, 43 p. (TechRep118, data set 390). 

Ballard, Ronald L., Distribution of beach sediment near the Columbia River: Seattle, University 

of Washington, Department of Oceanography Technical Report no. 98, February 1964, 

Reference M64-16, 75 p. with appendices (TechRep98, data set 389). 

Barnard, William D., 1973, Late Cenozoic sedimentation of the Washington continental slope: 

Seattle, University of Washington, Ph.D. dissertation, 255 p. (Barnard_PhD_1973, data set 

421). 

Barnes, Peter W., 1970, Marine geology and oceanography of Santa Cruz Basin off southern 

California: Los Angeles, University of Southern California, Ph.D. dissertation; also published 

as USC Report Number: USC-GEOL 70-3, 175 p. (Barnes_PhD_1970, data set 406). 

Bockman, Peter, Hill, David S., and Achsetter, Eugene, 1966, A summary of sediment size, 

composition, and engineering properties for PMR project 121/02; September – October 

1965: U.S. Naval Oceanographic Office (NAVOCEANO) Laboratory Item 277, 44 p. 

National Geophysical Data Center (MGG_09005011, data set 365). 

Borgeld, Jeffry C., 1985, Holocene stratigraphy and sedimentation on the northern California 

continental shelf: Seattle, University of Washington, Ph.D. dissertation, 177 p. (J. Borgeld, 

additional data, written commun. 1999 to Mark Zimmermann, National Marine Fisheries 

Service, (Borgeld_PhD_1985, data set 385). 

Bouma, Arnold and Marshall, Neil, 1964, A method for obtaining and analyzing undisturbed 

oceanic sediment samples: Marine Geology v. 2 no. 1/2, p. 81-99 

(Bouma_&_Marshall_1964, data set 408). 

Burnett, Thomas L., 1968, Bottom sediment data from the continental shelf of Washington – 

Grays Harbor to Cape Flattery: Seattle, University of Washington, Department of 

Oceanography Special Report no. 39, 1005 p. in three volumes (SpecReps57_40_39, data 

set 388). 

45 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Bushnell, David C., 1964, Continental shelf sediments in the vicinity of Newport, Oregon: 

Corvallis, Oregon State University, Masters thesis, 107 p. (Bushnell_MS_1963, data set 

397). 

Butcher, William S., 1951, Lithology of the offshore San Diego area and foraminifera of 

Coronado Bank and vicinity, California: Los Angeles, University of California, Ph.D. 

dissertation, 117 p. (Butcher_PhD_1951, data set 420). 

Cacchione, David, and Drake, David, 1983, Variability of sea-floor roughness within the Coastal 

Ocean Dynamics Experiment (CODE) region: Woods Hole Oceanographic Institution, 

Technical Report 83-25, 44 p. (WHOI_TR_83-25, data set 298). 

Carter, Lee S., 1971, Recent marine sediments of Carmel Bay California: Monterey, U.S. Naval 

Postgraduate School, Masters thesis, 57 p. (Carter_MS_71, data set 358). 

Chambers, David M., 1968, Holocene sedimentation and potential placer deposits on the 

continental shelf off the Rogue River, Oregon: Corvallis, Oregon State University, Masters 

thesis, 103 p. (Chambers_MS_1968, data set 396). 

Cherry, John A., 1962, Sand movement along a portion of northern California coast: Berkeley, 

University of California, Masters thesis, 125 p. (also published as U.S. Army Coastal 

Engineering Research Center Technical Memorandum no. 14, CERC_TM14, data set 12). 

Coleman, Jess B., and Grimes, Alvin R., 1965, A summary of sediment size, composition and 

engineering properties for PMR project 5R-006: U.S. Naval Oceanographic Office 

(NAVOCEANO) Laboratory Item 242, 31 p., National Geophysical Data Center 

(MGG_09185006, data set 372). 

Colomb, Herbert P., Jr., 1973, Recent marine sediments of the central California continental 

shelf between Point Lobos and Point Sur: Monterey, U.S. Naval Postgraduate School, 

Masters thesis, 40 p. (Colomb_MS_73, data set 359). 

Conomos, T. John, 1963, Geologic aspects of recent sediments of south San Francisco Bay: 

San Jose, San Jose State University, Masters thesis, 118 p. (Conomos_MS_1963, data set 

411). 

Daetwyler, Calvin C. Jr., 1965, Marine geology of Tomales Bay, Central California: San Diego, 

University of California, Ph.D. dissertation, 219 p. (Daetwyler_PhD_1965, data set 422). 

Demirpolat, Suleyman, 1981, Continental shelf sediments off the Russian River, northern 

California: Seattle, University of Washington, Masters thesis, 99 p. (Demirpolat_MS_1981, 

data set 423). 

Dorman, Craig E., 1968, The southern Monterey Bay littoral cell; A preliminary sediment budget 

study: Monterey, U.S. Naval Postgraduate School, Masters thesis, 233 p. (Dorman_MS_68, 

data set 360). 

Edwards, Brian D., Gardner, James V., and Medrano, Marjorie D., 1997, Grain size, organic 

carbon, and CaCO3 of surface sediments from the southern Monterey Bay continental shelf 

sea floor in Southern Montery Bay continental shelf Investigations in Stephen L. Eittreim 

46 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

(ed.) Former Fort Ord restricted zone: U.S. Geological Survey Open-file report 97-450, p. 

22-75 (OFR_01-107, data set 306). 

Emery, K.O., and Hülsemann, Jobst, 1963, Submarine canyons of southern California: Allan 

Hancock Pacific Expeditions v. 27 pt. 1, 80 p. (Emery_&_Hülsemann_1963, data set 409). 

Emery, K.O., and Shepard, F.P., 1941, Lithology of the sea floor off of Southern California: 

Bulletin of the Geological Society of America v.56, p. 431-473 (Emery_&_Shepard_1941, 

data set 407). 

Field, Michael E., Clarke, Samuel H., Jr., and White, Michael E., 1980, Geology and geologic 

hazards of offshore Eel River basin, northern California continental margin: U.S. Geological 

Survey Open-file Report 80-1080, 80 p. (OFR_80-1080, data set 296). 

Gardner, James V. and Klise, David H., 1983, Mineralogic and sedimentological data collected 

on the shelf and upper slope adjacent to the Russian River northern California: U.S. 

Geological Survey Open-file report 83-517, 83 p. (OFR_83-517, data set 297). 

Gardner, James V., Barron, John A., Dean, Walter E., Heusser, Linda E., Poore, Richard Z., 

Quinterno, Paula J., Stone, Sean M., and Wilson, Christine R., 1984, Quantitative 

microfossil, sedimentologic, and geochemical data on core L13-81-G138 and surface 

samples from the continental shelf and slope off northern California: U.S. Geological Survey 

Open-file Report 84-369, 49 p. (OFR_84-369, data set 299). 

Gardner, James V., Dean, Walter E., and Kayen, Robert, 1992, Cruise report; USGS Cruise F2-

92, Central and Southern California margin; Paleoceanography of the California Current; 

Redwood City, Calif. to Redwood City, Calif., March 11 to March 30, 1992: U.S. Geological 

Survey Open-file Report 92-342, 354 p. (OFR_92-342, data set 312). 

Glover, Linda K., Hill, David S., Knoop, John W., and Ross, Cary M., 1967, A summary of 

sediment size and composition analysis of cores and grabs of San Clemente Island: U.S. 

Naval Oceanographic Office (NAVOCEANO) Laboratory Item 318, National Geophysical 

Data Center, (MGG_09005004, data set 363). 

Gorsline, Donn S., 1958, Marine geology of San Pedro and Santa Monica basins and vicinity, 

California: Los Angeles, University of Southern California, Ph.D. dissertation, 301 p. 

(Gorsline_PhD_1958, data set 425). 

Hampton, Margaret A., Snyder, Noah P., Chin, John L., Allison, Dan W., and Rubin, David M., 

2003, Bed-sediment grainsize and morphological data from Suisun, Grizzly, and Honker 

Bays: U.S. Geological Survey Open-file Report 03-250, 25 p. (OFR_03-250, data set 284). 

Hands, Edward B., 1968, Inner continental shelf sediments in the vicinity of Cape Flattery, 

Washington: Seattle, University of Washington, Department of Oceanography Special 

Report no. 40, 39 p. (SpecReps57_40_39, data set 388). 

Heiner W.R., 1967, A summary of sediment size and chemistry of ten cores and thirty-six grabs 

from off Southern California, Dec. 1967: U.S. Naval Oceanographic Office (NAVOCEANO) 

Laboratory Item 353, 59 p., National Geophysical Data Center (MGG_09595002, data set 

373). 

47 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Hill, David S., Oser, Robert K., and Rohrhirsch, Joseph M., 1965, A summary of sediment size, 

composition and engineering properties for PMR project R-006: US Naval Oceanographic 

Office (NAVOCEANO) Laboratory Item 227, 40 p., National Geophysical Data Center 

(MGG_09005019, data set 366). 

Horn, D.R., Acoustic provinces of the north Pacific based on deep sea cores, unpublished data 

from Cruises VEMA 20, VEMA 21, and Robert Conrad 10: U.S. Naval Oceanographic 

Department (NAVOCEANO), collected 1964-1966, National Geophysical Data Center 

(MGG_01995001, data set 362). 

Humboldt State University, Arcata, CA, unpublished data from the STRATAFORM project (Eel 

River area, northern California), cruises aboard R/V Wecoma (cruise IDs W9807, W9509A) 

and R/V Tommy Thompson (cruise ID TT141): Jeff Borgeld, written commun., 1999, to 

Michael E. Field, USGS (Strataform, data set 386). 

Ingram, C., Bowman, J., and Ross, C., 1975, Lab Item 486, A summary of sediment size, Xradiography, engineering and mass properties of three cores from the Pacific: U.S. Naval 

Oceanographic Office (NAVOCEANO) Laboratory Item 486, 19 p., National Geophysical 

Data Center (MGG_09635008, data set 380). 

Isselhardt, C., Osuch, L., Wilde, P., and Yancey, T., 1969, Recent sediments of Bolinas Bay 

California, Part B: Mineralogical Data: Hydraulic Engineering Laboratory Report HEL 2-22, 

University of California, Berkeley, 155 p. (HEL 2-19&2-22, data set 416). 

Isselhardt, C., Osuch, L., and Wilde, P, 1968, Recent sediments of Bolinas Bay California, Part 

A: Introduction and grain size analysis: Hydraulic Engineering Laboratory Report HEL 2-19, 

University of California, Berkeley, 55 p. (HEL 2-19&2-22, data set 416). 

Karl, Herman A., Drake, David E., Schwab, William C., Edwards, Brian D., Lee, Homa J., and 

Chin, John L., 1990, Progress report on status of analysis and interpretation of data on 

Farallon Escarpment: U.S. Geological Survey Woods Hole Science Center Report 90027, 

83 p. (WHSC_90027, data set 308). 

Kelly, Eugene V., and Loomis, P. Burr, 1970, A summary of sediment size and composition of 

ten grabs, February 1970: U.S. Naval Oceanographic Office (NAVOCEANO) Laboratory 

Item 393, National Geophysical Data Center, 16 p. (MGG_09635001, data set 376). 

Klise, David H., 1983, Modern sedimentation on the California continental margin adjacent to 

the Russian River: San Jose, San Jose State University, Masters thesis, 138 p. (see OFR 

83-517, data set 297). 

Kravitz, J.H., Ross, C.M., and Loomis, P.B., 1972, A summary of sediment size, composition, Xradiogrpahy, structure, and engineering properties of 7 cores and 20 grabs from the east 

Pacific: U.S. Naval Oceanographic Office (NAVOCEANO) Laboratory Item 426, 67 p., 

National Geophysical Data Center (MGG_09635003, data set 378). 

Lavoie, Dawn, 1982, Analysis of six cores from the Washington state continental shelf: U.S. 

Naval Research and Development Activity (NORDA), Technical Report 6-82, 14 p., 

National Geophysical Data Center (MGG_09635014, data set 382). 

48 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Lee, J., Glogoczowski, M., Yancey, T., and Wilde, P., 1971, Recent sediments of the central 

California continental shelf, Pillar Point to Pigeon Point, Part B. Mineralogical data: 

Berkeley, University of California, Hydraulic Engineering Laboratory, Technical Report HEL 

2-30, 63 p. (HEL 2-26&2-30, data set 417). 

Lee, J., Yancey, T., and Wilde, P., 1970, Recent sediments of the central California continental 

shelf, Pigeon Point to Sand Hills Bluff: Berkeley, University of California, Hydraulic 

Engineering Laboratory Technical Report HEL 2-28, 62 p. (HEL 2-28, data set 418). 

Locke, J.L., 1971, Sedimentation and foraminiferal aspects of the recent sediments of San 

Pablo Bay: San Jose, San Jose State University, Masters thesis, 100 p. (Locke_MS_1971, 

data set 412). 

Loomis, P.B., Bowman, J.C., and Kelly, E.V., 1973, A summary of sediment size and chemistry 

of 3 cores and twenty-five grabs from San Francisco Bay, California and Mayport, Florida: 

U.S. Naval Oceanographic Office (NAVOCEANO) Laboratory Item 446, 27 p., National 

Geophysical Data Center (MGG_09005039, data set 367). 

Loomis, P.B., Bowman, J.C., and Kelly, E.V., 1973, A summary of sediment size and chemistry 

of 4 cores from San Diego, California and St John's River, Jacksonville, Florida: U.S. Naval 

Oceanographic Office (NAVOCEANO) Laboratory Item 447, 19 p., National Geophysical 

Data Center (MGG_09005040, data set 368). 

Loomis, P.B., and Bowman, J.C., 1973, A summary of sediment size and chemistry of thirty 

cores from San Francisco Bay and Norfolk Harbor: U.S. Naval Oceanographic Office 

(NAVOCEANO) Laboratory Item 444, 23 p., National Geophysical Data Center 

(MGG_09635003, data set 378). 

Loomis, P.B., and Bowman, J.C., 1973, A summary of sediment size and chemistry of ten cores 

from San Francisco Bay area: U.S. Naval Oceanographic Office (NAVOCEANO) 

Laboratory Item 445, 23 p., National Geophysical Data Center (MGG_09635004, data set 

379). 

Maher, Norman M., Karl, Herman A., Chin, John L., and Schwab, William. C., 1991, Station 

locations and grain-size analysis of surficial sediment samples collected on the continental 

shelf, Gulf of the Farallones during cruise F2-89-NC, January 1989: U.S. Geological Survey 

Open-file Report 91-375A, 42 p. (OFR_91-375A, data set 307). 

Maloney, Neil, and Byrne, John, 1964, Sedimentary rocks from the continental shelf and slope 

off the central coast of Oregon: The ORE Bin v. 26, no. 5, p. 77-83 

(Maloney_&_Byrne_1964, data set 399). 

Maloney, Neil J., 1965, Geology of the continental terrace off the central coast of Oregon: 

Corvallis, Oregon State University, Ph.D. dissertation, 233 p. (Maloney_PhD_1965, data set 

398). 

McLaren, Patrick, 2000, Moss Landing Harbor District, A sediment trend analysis (STA®) and an 

acoustic bottom classification (ABC) in eastern Monterey Bay, Moss Landing; Implications 

to dredge disposal operations: GeoSea Consulting (Canada) Ltd., CD-ROM, (ML Harbor, 

data set 27). 

49 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

McLaren, Patrick, 2000, Sediment trend analysis (STA®) of Santa Cruz harbor: GeoSea® 

Consulting (Canada) Ltd., CD-ROM, (SC Harbor, data set 26). 

Milliman, John D., 1964, Recent marine sediments in Grays Harbor, Washington: Seattle, 

University of Washington, Masters thesis, 172 p. (Milliman_MS_1964, data set 392). 

Moore, D.B., 1965, Recent coastal sediments Double Point to Point San Pedro, California: 

Berkeley, University of California, Hydraulic Engineering Laboratory Technical Report HEL 

2-14, 86 p. (HEL 2-14, data set 414). 

Moore, David G., 1962. Bearing strength and other physical properties of some shallow and 

deep-sea sediments from the North Pacific: Geological Society of America Bulletin, v. 73, p. 

1163-1166 (Moore_1962, data set 361). 

Muehlberg, Gary E., 1971, Structure and stratigraphy of Tertiary and Quaternary strata, Heceta 

Bank, Central Oregon: Corvallis, Oregon State University, Masters thesis, 78 p. 

(Muehlberg_MS_1971, data set 400). 

National Geophysical Data Center, 2004, Sea-floor surficial sediment descriptions (Deck 41): 

downloaded 2004, (Deck41, data sets 124, 171, 172, 199, 202, 203, 227, 242, 243, 244, 

245, 246, 259). 

National Geophysical Data Center, 2004, Sea floor surficial sediment descriptions (Deck 41): 

NODCref 871 [no source information available], downloaded 2004, (Deck41, data set 259 

National Oceanic and Atmospheric Administration, 2004, National Status and Trends Mussel 

Watch digital database: downloaded 2004, (NS&TMusselWatch, data set 268). 

National Oceanic and Atmospheric Administration, 2004, National Status and Trends Benthic 

Surveillance digital database: downloaded 2004, (NS&TBenthic Surveillance, data set 269). 

Nittrouer, Charles A., 1978, The process of detrital sediment accumulation in a continental shelf 

environment: An examination of the Washington shelf: Seattle, University of Washington, 

Ph.D. dissertation, 243 p. (Nittrouer_PhD_1978, data set 394). 

NOAA Olympic Coast National Marine Sanctuary, Unpublished data gathered in the Olympic 

Coast National Marine Sanctuary in 2000: Rick Fletcher, written commun., 2001, to Mark 

Zimmermann, NOAA National Marine Fisheries Service (OCNMS_2000_grabs, data set 

270). 

Orzech, Kevin M., Dahl, Wendy E., and Edwards, Brian D., 2001, Core descriptions, core 

photgraphs, physical property logs and surface textural data of sediment cores recovered 

from the continental shelf of the Monterey Bay national Marine Sanctuary during the 

research cruises M196MB, P295MB, and P197MB: U.S. Geological Survey Open-file 

Report 01-107, CD-ROM, (OFR_01-107, data set 306). 

Oser, Robert and Bowman, J., 1974, A summary of sediment size and chemistry of four cores 

from the Long Beach Naval Shipyard: U.S. Naval Oceanographic Office (NAVOCEANO) 

Laboratory Item 462, 14 p., National Geophysical Data Center (MGG_09005053, data set 

370). 

50 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Oser, Robert, Coleman, Jess, Achstetter, Eugene, Hill, David, Johnson, William, Ross, Cary, 

Knoop, John, and Williams, Vernon, 1966, A summary of engineering properties, sediment 

size, and composition analyses of cores from the continental borderland near San 

Clemente Island; October 1966-December 1966: U.S. Naval Oceanographic Office 

(NAVOCEANO) Laboratory Item 303, 139 p., National Geophysical Data Center 

(MGG_09595003, data set 374). 

Poppe, L.J.; and Polloni, C.F. (eds.), 2000, USGS east-coast sediment analysis: Procedures, 

database, and georeferenced displays: U.S. Geological Survey Open-file Report 00-358, 

CD-ROM (OFR_00-358, data set 357). 

Roberts, Richard W., 1974, Marine sedimentological data of the Washington continental shelf: 

Seattle, University of Washington, Department of Oceanography Special Report No. 57, 

129 p. (SpecRep57, data set 388). 

Roberts, Richard, W., 1974, Marine sedimentological data for the inland waters of Washington 

state (Strait of Juan de Fuca and Puget Sound): Seattle, University of Washington, 

Department of Oceanography Special Report 56, 120 p. (SpecRep56, data set 387). 

Rooper, C.N., Armstrong, D.A., and Gunderson, D., 2002, Habitat use by juvenile Dungeness 

crabs in coastal nursery estuaries: in Crabs in Cold Water Regions: Biology, Management, 

and Economics, Alaska Sea Grant College Program, p. 609-629. Sediment data collected 

in support of this study by University of Washington, Chris Rooper, written commun., 2003, 

to Mark Zimmermann, NOAA National Marine Fisheries Service (Rooper et al. 2002, data 

set 395). 

Ross, C., Kelly, E.V., Bowman, J., Ingram, C., and Stiles, N.T., 1975. A summary of sediment 

size of one core and thirty-three grab samples from the Strait of Juan de Fuca: U.S. Naval 

Oceanographic Office (NAVOCEANO) Laboratory Item 491, 46 p., National Geophysical 

Data Center (MGG_09635012, data set 381). 

Roush, Robert C., 1970, Sediment textures and internal structures: A comparison between 

central Oregon continental shelf sediments and adjacent coastal sediments: Corvallis, 

Oregon State University, Masters thesis, 75 p. (Roush_MS_1970, data set 401). 

Royse, Chester F., 1964, Sediments of Willapa submarine canyon: Seattle, University of 

Washington, Department of Oceanography, Technical Report no. 111, Reference M64-60, 

62 p. (TechRep111, data set 391). 

Runge, Erwin J., Jr., 1966. Continental shelf sediments, Columbia River to Cape Blanco 

Oregon: Corvallis, Oregon State University, Ph.D. dissertation, 143 p. (Runge_PhD_1966, 

data set 402). 

Schatz, Byron, 1963, A restudy of bottom sediments near the entrance of the Golden Gate: 

Berkeley, University of California, Hydraulic Engineering Laboratory, Wave Research 

Project, Technical Report HEL 4-3, 8 p. with appendices (HEL 4-3, data set 419). 

Scholl, David W., 1959, Geology and surrounding recent marine sediments of Anacapa Island: 

Los Angeles, University of Southern California, Masters thesis, 105 p. (Scholl_MS_59, data 

set 384). 

51 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Skidaway Institution of Oceanography, Savannah, GA, unpublished data from the 

STRATAFORM project (Eel River area, northern California), cruises aboard R/V Wecoma 

(cruise IDs W9502A, W9509A) and R/V [unknown] (cruise ID TN062): Clark Alexander, 

written commun., 1999, to Michael E. Field, USGS (Strataform, data set 386). 

Smith, J.M., Messmer, L.W., Phipps, J.B., Samuelson, D.F., and Schermer, E.D., 1980, Grays 

Harbor and Chehalis River improvements to navigation environmental studies - Grays 

Harbor ocean disposal study: literature review and preliminary benthic sampling: U.S. Army 

Corps of Engineers Internal Report, cited in Twichell, David C., VeeAnn A. Cross, Kenneth 

F. Parolski, 2000, Sidescan-sonar imagery, surface sediment samples, and surficial 

geologic interpretation of the southwestern Washington inner continental shelf based on 

data collected during Corliss cruises 97007 and 98014, South Washington Coastal Erosion 

Study, U.S. Geological Survey Open-file Report 00-167, CD-ROM, (Smith et al., 1980, data 

set 16). 

Smith, Stephen V., 1970, Calcium carbonate budget of the southern California continental 

borderland: Honolulu, University of Hawaii, Ph.D. dissertation, also published as Hawaii 

Institute of Geophysics Report no. HIG-70-11, 174 p. (Smith_PhD_1970, data set 405). 

Smithsonian Institution, National Ocean Service digital database: Carla Moore, National 

Geographic Data Center, 2001, personal communication to Jane Reid, USGS; used by 

permission of Scott Wing, Smithsonian Institution, 2004 (Smithsonian_NOS_File, data set 

279). 

Smithsonian Institution, 2004, Raw data sheets of bottle samples 1844-1884: NODCref 619, 

Deck 41 data compilation, National Geophysical Data Center, (Deck41, data set 124). 

Smithsonian Institution, 2004, Coded NODC forms: NODCref 781, Deck 41 data compilation, 

National Geophysical Data Center, (Deck41, data set 227). 

Southern California Coastal Water Research Project (SCCWRP), 1996, 1994 Pilot Project 

Survey report: online, downloaded 1999, (SCCWRP94, data set 28). 

Southern California Coastal Water Research Project (SCCWRP), 2000, Bight98 Survey: online, 

downloaded 2005 (SCCWRP98, data set 29). 

Spigai, Joseph J., 1971, Marine geology of the continental margin of southern Oregon: 

Corvallis, Oregon State University, Ph.D. dissertation, 214 p. (Spigai_PhD_1971, data set 

403). 

Tetra Tech, Inc., 1990, Puget Sound ambient monitoring program 1989, Marine sediment 

monitoring, Report to the Washington (State) Department of Ecology Ambient Monitoring 

Section, TC 3838 Final Report, 262 p. (TC_3838, data set 25). 

U.S. Coast and Geodetic Survey, 2002, Unpublished bottom sediment data from cruise OPR 

411, collected 1968 to 1970: National Geophysical Data Center, 30 p. (MGG_03995001, 

data set 272). 

U.S. Coast and Geodetic Survey, 2004, Unpublished oceanographic log sheets – M: Bottom 

sediment data from Surveyor OPR. No. 441: NODCref 717, Deck 41 data compilation, 

National Geophysical Data Center (Deck41, data set 199). 

52 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

U.S. Geological Survey, unpublished data from southern California, aboard the R/V Auriga, 

cruise A298SC, collected 1998, Homa Lee and Brian Edwards, Chief Scientists, 

(Cruise_A298SC, data set 295). 

U.S. Geological Survey, unpublished data from northern California, aboard the R/V Farnella, 

cruise F1288NC, collected 1988, Michael E. Field and James V. Gardner, Chief Scientists 

(Cruise_F1288NC, data set 300). 

U.S. Geological Survey, unpublished data from southern California, aboard the R/V Farnella, 

cruise F592SC, collected 1992, Homa Lee and Brian Edwards, Chief Scientists 

(Cruise_F592SC, data set 309). 

U.S. Geological Survey, unpublished data from northern California, aboard the R/V S.P. Lee, 

cruise L486NC, collected 1986, David Cacchione and David Drake, Chief Scientists 

(Cruise_L486NC, data set 301). 

U.S. Geological Survey, unpublished data from northern California, aboard the R/V McArthur II, 

cruise M102NC, collected 2001, Ian Hartwell, NOAA, Chief Scientist (Cruise_M102NC, data 

set 315). 

U.S. Geological Survey, unpublished data from northern California, aboard the R/V Point Sur, 

cruise P188NC, collected 1988, David Cacchione and Michael Field, Chief Scientists 

(Cruise_P188NC, data set 302). 

U.S. Geological Survey, unpublished data from northern California, aboard the R/V Sea 

Sounder, cruise S5a79NC, collected 1979, David Cacchione and David Drake, Chief 

Scientists (Cruise_S5a79NC, data set 305). 

U.S. Geological Survey, unpublished data from northern California, aboard the R/V Susan K, 

cruise S186NC (SK86NC), collected 1986, David Cacchione and David Drake, Chief 

Scientists (Cruise_S186NC, data set 303). 

U.S. Geological Survey, unpublished data from southern California, aboard the R/V Sea 

Sounder, cruise S193SC, collected 1993, Dave Drake, Chief Scientist (Cruise_S193SC, 

data set 310). 

U.S. Geological Survey, unpublished data from southern California, aboard the R/V Sproul, 

cruise S297SC, collected 1997, Homa Lee and Brian Edwards, Chief Scientists, 

(Cruise_S297SC, data set 294). 

U.S. Geological Survey, unpublished data from northern California, aboard the R/V Tommy 

Thompson, cruise TT197 [USGS Cruise T286NC], collected 1986, Michael Field, Chief 

Scientist (Cruise_TT197/T286NC, data set 304). 

U.S. Naval Civil Engineering Laboratory, Analyses of marine sediment in Area H, eastern 

Pacific: unpublished report, 269 p., National Geophysical Data Center (MGG_09005007, 

data set 364). 

U.S. Naval Oceanographic Office, 1969, 2003, Submarine sediment investigation near planned 

Sealab 3 Habitat: U.S. Naval Oceanographic Office (NAVOCEANO) Informal Report 69-28, 

National Geophysical Data Center, (MGGID_09005004, data set 363). 

53 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

U.S. Naval Oceanographic Office, unpublished coded NODC geology forms, R/V Davis (TAGOR 5), cruise 056716, NODCref 837, Deck 41 data compilation, National Geophysical 

Data Center, (Deck41, data set 246). 

University of Southern California, Los Angeles, CA, SEDDATA digital database: Donn Gorsline, 

written commun., 2001, to Jane Reid, USGS (SEDDATA, data set 404). 

University of Southern California, 2004, unpublished oceanographic log sheets – M: Bottom 

sediment data from Velero IV, cruise 670: NODCref 721, Deck 41 data compilation, 

National Geophysical Data Center, (Deck41, data set 202). 

University of Southern California, 2004, unpublished raw data sheets and coded NODC geology 

forms, Velero IV, cruise 866 NODCref 722: Deck 41 data compilation, National Geophysical 

Data Center, (Deck41, data set 203). 

University of Southern California, 2004, unpublished oceanographic log sheets – M: Bottom 

sediment data from Velero IV, cruise 909: NODCref 831, Deck 41 data compilation, 

National Geophysical Data Center, (Deck41, data set 242). 

University of Southern California, 2004, unpublished oceanographic log sheets – M: Bottom 

sediment data from Velero IV, cruise 910: NODCref 832, Deck 41 data compilation, 

National Geophysical Data Center, (Deck41, data set 243). 

University of Southern California, Unpublished oceanographic log sheets – M: Bottom sediment 

data from Velero IV, cruise 911: NODCref 833, Deck 41 data compilation, National 

Geophysical Data Center, (Deck41, data set 244). 

University of Southern California, Unpublished oceanographic log sheets – M: Bottom sediment 

data from Velero IV, cruise 914: NODCref 834, Deck 41 data compilation, National 

Geophysical Data Center, (Deck41, data set 245). 

University of Washington, Seattle, unpublished data from the STRATAFORM project (Eel River 

area, northern California) cruises aboard the R/V Pacific Hunter (cruise IDs PH950304, 

PH950515, PH951110, PH951216, PH960317, PH960424); R/V Point Sur (cruise IDs 

PS9705, PS9803); R/V Wecoma (cruise IDs W9606A, W9701A, W9801); and R/V Warrior 

II (cruise ID WR9611): Charles Nittrouer, 1999, written commun., 1999, to Michael Field, 

USGS, (Strataform, data set 386). 

University of Washington, Seattle, 2004, Coded NODC forms, R/V Tommy Thompson, Cruise 

TT8: NODCref 678, Deck 41 data compilation, National Geophysical Data Center, (Deck41, 

data set 171). 

Valent, P. J., and Lee, H. J., 1971, Reconnaissance study for the proposed California undersea 

aqueduct: Naval Civil Engineering Lab Report Number 1, NCEL core data – Santa Barbara 

Channel area, Naval Civil Engineering Laboratory, 137 p. National Geophysical Data 

Center (MGG_09005058, data set 371). 

Vedder, J.G., Taylor, J.C., Arnal, R.E., and Bukry, D., 1976, Preliminary description of selected 

samples of pre-Quaternary ag: U.S. Geological Survey Miscellaneous Field Studies MF 

737, 3 sheets (MF-737, data set 311). 

54 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Wilde, Pat, 1965, Recent sediments of the Monterey deep-sea fan: Berkeley, University of 

California, Hydraulic Engineering Laboratory Technical Report HEL 2-13, 153 p. (HEL 2-13, 

data set 413). 

Wolf, Stephen C., 1968, Current patterns and mass transport of clastic sediments in the nearshore regions of Monterey Bay, San Jose, San Jose State University, Masters thesis, 176 

p. (Wolf_MS_1968, data set 410). 

Wong, Florence L., 1995, Sediment distribution on a stream-dominated continental margin, 

northern California; Implications from heavy-mineral studies: U.S. Geological Survey Openfile Report 95-614, 21 p. (OFR_95-614, data set 296). 

Wright, Frederick F., 1967, The marine geology of the San Miguel gap off Point Conception, 

California: Los Angeles, University of Southern California, Ph.D. dissertation, 257 p. 

(Wright_PhD_1967, data set 424). 

Yancey, T.E, Isselhardt, C., Osuch, L., Lee, J., and Wilde, P., 1970, Recent sediments of the 

central California continental shelf, Pillar Point to Pigeon Point, Part A, Grain size data: 

Berkeley, University of California, Hydraulic Engineering Laboratory, Technical Report HEL 

2-26, 64 p. (HEL 2-26 & 2-30, data set 417). 

Yancey, T.E., 1968, Recent sediments of Monterey Bay: Berkeley, University of California, 

Hydraulic Engineering Laboratory Technical Report HEL 2-18, 145 p. (HEL 2-18, data set 

415). 

55 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Appendix B. Published Articles about dbseabed 

The following published articles provide more detailed information about various aspects of 

dbSEABED and are included in this publication: 

Jenkins, C., 1997, Building offshore soils databases: Sea Technology, v. 38, no. 12, p. 25-28. 

(Permission for reproduction granted by Sea Technology Magazine. For additional 

information contact Sea Technology.) 

Jenkins, C., 2002, Automated digital mapping of geological colour descriptions: Geo-Marine 

Letters, v. 22, no. 4, p. 181-187. (Permission for reproduction granted by Springer. For 

additional information about the SpringerLink free abstract program, please see Springer 

Online Products.) 

Jenkins, C., 2003, Data management of MARGINS geologic data, with emphasis on efficiency, 

quality control and data integration: MARGINS Newsletter. 10, Spring 2003, p. 8-10.* 

*(Permission for reproduction granted by MARGINS. Since this article was published, a 

MARGINS data management system (DMS) (http://data.nsf-margins.org/) has been established 

within the Marine Geoscience Data Management System (http://www.marine-geo.org/). This 

DMS is the designated MARGINS repository for metadata relating to all data types and for 

digital data for which no standard repository exists. Central to the larger system are visualization 

and search tools that facilitate integrated access to data and metadata across diverse scales 

and disciplines. Ultimately, all MARGINS data and samples will be traceable through metadata 

maintained in the DMS.) 

56 
Reid and others, 2006, usSEABED Pacific Coast Surficial-Sediment Data Release 

U.S. Geological Survey Data Series 182 

Appendix C. Frequently Asked Questions about dbSEABED and usSEABED 

See separate sheet: DS182_FAQs.pdf 

Appendix D. onCALCULATION 

See separate sheet: DS182_onCalculation.pdf 

57