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USGS Geoscience Data Catalog

National Geochemical Atlas: The Geochemical Landscape of the Conterminous United States Derived from Stream Sediment and other Solid Sample Media Analyzed by the National Uranium Resource Evaluation (NURE) Program

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Metadata:

Identification_Information:
Citation:
Citation_Information:
Originator: Jeffrey N. Grossman
Title:
National Geochemical Atlas: The Geochemical Landscape of the Conterminous United States Derived from Stream Sediment and other Solid Sample Media Analyzed by the National Uranium Resource Evaluation (NURE) Program
Edition: 3.01
Publication_Date: 1998
Series_Information:
Series_Name: U.S. Geological Survey Open-File Report
Issue_Identification: 98-622
Publication_Information:
Publication_Place: Reston, VA
Publisher: U.S. Geological Survey
Geospatial_Data_Presentation_Form: raster digital data
Online_Linkage: http://mrdata.usgs.gov/nure-hssr/
Description:
Abstract:
This CD presents maps derived from a subset of the National Uranium Resource Evaluation (NURE) Hydrogeochemical and Stream Sediment Reconnaissance (HSSR) data. Approxiamately 260,000 samples were analyzed in the continental U.S. and consisted of solid samples, including stream, lake, pond, spring, and playa sediments, and soils.
Data for eleven elements were analyzed and included on this release of the National Geochemical Atlas CD: Na, Ti, Fe, Cu, Zn, As, Ce, Hf, Pb, Th, and U.
The National Uranium Resource Evaluation (NURE) program of the Department of Energy (DOE) collected a vast amount of chemical data on sediment, soil, and water samples from the United States in the late 1970's and early 1980's. This element of the NURE program was known as the Hydrogeochemical and Stream Sediment Reconnaissance (HSSR). The NURE HSSR data have long been available to the public in a variety of formats, ranging from the original paper reports produced by the DOE (see Averett, 1984), to comprehensive digital releases on CD-ROM by the U.S. Geological Survey in the last few years (Hoffman and Buttleman, 1994; 1996), to digital releases on the Internet of reformatted and cleaned data (Smith, 1998). While these publications remain the best sources of the complete, primary data, and are accompanied by documentation of the sampling protocols, sample characteristics, and analytical methods, they are difficult to use for geochemical research, especially when the study area covers a wide area of the United States. This publication is intended to allow the rapid visualization of the geochemical landscape of the United States using the NURE HSSR data. Here, the user is relieved of the responsibility of selecting and processing the raw data; this was done in the preparation of the CD. A powerful geographic-information system (GIS) tool, the ArcView program of Environmental Systems Research Institute, Inc. (ESRI), is provided to allow one to probe and manipulate the processed NURE data. Within the ArcView environment, multiple presentations of the NURE are provided, ranging from color-coded point maps, to bitmap-images on a national scale, to interpreted maps based on geologic and hydrologic units. Because the NURE HSSR data have been processed by the author for the production of this CD, the user must use a degree of caution in interpreting the maps produced here, and in using the data files found on the disc. One must understand the methods used in deriving the data on this CD in order to judge the significance of any particular map or data feature. Fortunately, the raw data used in the production of this CD are available in digital form (Hoffman and Buttleman, 1996), for examination by sophisticated users.
Purpose:
To make this portrayal of NURE Geochemical data available on the Internet.
Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 1964
Ending_Date: 1995
Currentness_Reference: publication date
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None planned
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -179.1
East_Bounding_Coordinate: -67.764
North_Bounding_Coordinate: 70.0
South_Bounding_Coordinate: 19.003
Keywords:
Theme:
Theme_Keyword_Thesaurus: USGS Thesaurus
Theme_Keyword: igneous rocks
Theme_Keyword: geochemistry
Theme_Keyword: geospatial datasets
Place:
Place_Keyword_Thesaurus: none
Place_Keyword: United States
Temporal:
Temporal_Keyword_Thesaurus: None
Temporal_Keyword: 1999
Theme:
Theme_Keyword_Thesaurus: National Geologic Map Database Catalog themes, augmented
Theme_Keyword: 1900 - Geochemistry
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Categories
Theme_Keyword: geoscientificInformation
Place:
Place_Keyword_Thesaurus: Augmented FIPS 10-4 and FIPS 6-4
Place_Keyword: US01 = Alabama
Place_Keyword: US04 = Arizona
Place_Keyword: US05 = Arkansas
Place_Keyword: US06 = California
Place_Keyword: US08 = Colorado
Place_Keyword: US09 = Connecticut
Place_Keyword: US10 = Delaware
Place_Keyword: US11 = District of Columbia
Place_Keyword: US12 = Florida
Place_Keyword: US13 = Georgia
Place_Keyword: US16 = Idaho
Place_Keyword: US17 = Illinois
Place_Keyword: US18 = Indiana
Place_Keyword: US19 = Iowa
Place_Keyword: US20 = Kansas
Place_Keyword: US21 = Kentucky
Place_Keyword: US22 = Louisiana
Place_Keyword: US23 = Maine
Place_Keyword: US24 = Maryland
Place_Keyword: US25 = Massachusetts
Place_Keyword: US26 = Michigan
Place_Keyword: US27 = Minnesota
Place_Keyword: US28 = Mississippi
Place_Keyword: US29 = Missouri
Place_Keyword: US30 = Montana
Place_Keyword: US31 = Nebraska
Place_Keyword: US32 = Nevada
Place_Keyword: US33 = New Hampshire
Place_Keyword: US34 = New Jersey
Place_Keyword: US35 = New Mexico
Place_Keyword: US36 = New York
Place_Keyword: US37 = North Carolina
Place_Keyword: US38 = North Dakota
Place_Keyword: US39 = Ohio
Place_Keyword: US40 = Oklahoma
Place_Keyword: US41 = Oregon
Place_Keyword: US42 = Pennsylvania
Place_Keyword: US44 = Rhode Island
Place_Keyword: US45 = South Carolina
Place_Keyword: US46 = South Dakota
Place_Keyword: US47 = Tennessee
Place_Keyword: US48 = Texas
Place_Keyword: US49 = Utah
Place_Keyword: US50 = Vermont
Place_Keyword: US51 = Virginia
Place_Keyword: US53 = Washington
Place_Keyword: US54 = West Virginia
Place_Keyword: US55 = Wisconsin
Place_Keyword: US56 = Wyoming
Access_Constraints: None
Use_Constraints:
The U.S. Geological Survey makes no warranties related to the accuracy of the data and users are required to determine the suitability of use for any particular purpose.
Point_of_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Jeffrey N. Grossman
Contact_Organization: U.S. Geological Survey
Contact_Address:
Address_Type: mailing and physical address
Address: 12201 Sunrise Valley Dr.
City: Reston
State_or_Province: VA
Postal_Code: 20192
Country: USA
Contact_Voice_Telephone: 703 648-6184
Contact_Electronic_Mail_Address: jgrossman@usgs.gov
Native_Data_Set_Environment:
ArcView 3.1 Windows NT 4.0 (SP3)
Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report: Refer to Open File Report 98-622
Logical_Consistency_Report: None
Completeness_Report: See Process Description below and Open File Report 98-622
Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report:
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Originator: Phillip A. Baedecker
Originator: Jeffrey N. Grossman
Originator: Kim P. Buttleman
Publication_Date: 1998
Title:
National Geochemical Data Base: PLUTO Geochemical Data Base for the United States
Series_Information:
Series_Name: U.S. Geological Survey Digital Data Series
Issue_Identification: DDS-47
Geospatial_Data_Presentation_Form: Tabular digital data
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 1964
Ending_Date: 1995
Source_Currentness_Reference: Publication date
Source_Citation_Abbreviation: PLUTO
Source_Contribution:
National Geochemical Data Base: PLUTO Geochemical Data Base for the United States
Type_of_Source_Media: CD-ROM
Process_Step:
Process_Description:
The backbone of this CD is a series of DBase (DBF) files, each containing the point data for a single element in a set of solid (sediment) samples from the NURE HSSR program. All of the images and map coverages on the CD are derived from these DBF files. This section outlines the steps used in creating these files. The starting point for data processing on this CD is the set of quadrangle-by-quadrangle DBF files of NURE HSSR data found in Hoffman and Buttleman (1996). Note that these files are not the raw NURE data, but are themselves processed from the original digital files (on tape) produced by DOE. Indeed, the DOE tapes are also not the true raw data from the program, as there was a manual data-processing step to transfer data from paper reports. 308 quadrangle files (covering the continental U.S.) from Hoffman and Buttleman (1996) contained data for stream, lake, or spring sediments, and a subset of 43 of these files also contained data for soils (Table 1). qqqRecords covering these sample media were selected for inclusion in this CD. Most of the selection of records from the original DBF files, and other primary data extraction tasks were done with the Paradox database program. The steps in this procedure were as follows: Records were extracted from the quadrangle DBF files for the appropriate sample media using one or more of the field codes listed in Table 2. (See Hoffman and Buttleman, 1994, for explanation of codes.) After surveying each file (through a series of Paradox queries), a new query was constructed that extracted all records for stream sediments (wet and dry), lake and pond sediments (including dry lakes), spring sediments, and soils. Data fields were chosen from the selected records for further processing. These included several label fields, the sample-type fields listed in Table 2, the geographic coordinates, fields for the 54 chemical elements appropriate for solid samples (Ag, Al, As, Au, B, Ba, Be, Bi, Ca, Cd, Ce, Co, Cr, Cs, Cu, Dy, Eu, Fe, Hf, Ho, K, La, Li, Lu, Mg, Mn, Mo, Na, Nb, Nd, Ni, P, Pb, Pt, Rb, Ru, Sb, Sc, Se, Si, Sm, Sn, Sr, Ta, Tb, Th, Ti, U, V, W, Y, Yb, Zn, Zr), and 5 miscellaneous fields that contain chemical data (CONCN01 through CONCN05). A Paradox query extracted these fields, and all other data were discarded (including things like stream characteristics, contamination codes, various labels, and fields not used for solid sample media). Most chemical data in the quadrangle DBF files are stored in parts-per-billion (ppb). Paradox was used to convert each field into a more appropriate unit: parts-per-million (ppm) for trace elements, and wt.% for major elements (Al, Ca, Fe, K, Mg, and Na). Many samples were analyzed by more than one laboratory, or by more than one method. In these cases, there are multiple records in the quadrangle DBF files for an individual sample location, each with analyses for different elements. These records were found and combined into a single record. Paradox was used to sort the records by latitude and longitude. A temporary DBF file was generated, and read by a DOS FORTRAN program, ECLEAN, written by the author (unpublished). This program searched for consecutive records that had identical or nearly identical geographic coordinates (within 0.0005 degrees, or ~50 m, of each other). These were assumed to be the same sample, as round-off errors sometimes affected the 4th decimal place. ECLEAN then combined these records, element by element, into a single new record. In the few cases where data for the same element was present in two or more records, the highest value was arbitrarily chosen. This process also had the effect of consolidating samples actually collected as duplicates at a single location into single records. ECLEAN also eliminated records with no chemical data (and there were many of these). The program then created a new DBF file with the consolidated data. At the beginning of this processing stage, the 308 original quadrangle DBF files have been reduced to 308 new DBF files containing only the geographic and chemical-element fields of the sediment and soil data, without any duplicate or blank records. Major systematic problems, as discussed above, have been corrected. The following processing steps were used to find and correct additional problems in the datasets, to search for regional inconsistencies in the data, and to establish the usefulness of data reported as upper limits (e.g.,<10 ppm). The reduced DBF files were surveyed with a DOS FORTRAN program, also written by the author, called GRIDPLOT. This program reads in multiple DBF files, and produces a simple, color, gridded map of the data for one element on the computer screen. It is extremely efficient, and allows the rapid visualization of the data (all 308 files can be read, and a plot generated on a 200 MHz PentiumPro PC in about 1 minute). Systematic errors that were not found during primary data processing can be seen visually, as discontinuities in the colored map. In some cases, these could be traced to systematic errors in the quadrangle DBF files, especially errors in the position of decimal points. These were corrected by repeating the primary processing for the affected quadrangle. Other discontinuities are caused by analytical errors, and are handled in step 2.2.
In some areas, generally in the western U.S., one or more quadrangles, or parts of quadrangles, would appear to be discontinuous with adjacent quadrangles for a given element, when viewed with GRIDPLOT. In many such instances, a good case can be made that there is a systematic analytical error (i.e., an accuracy problem, probably due to different analytical methods or interlaboratory calibration problems) across the discontinuity. The best argument for the occurrence of this type of error is that regional chemical trends are seen on both sides of the discontinuity, and the application of a simple correction factor can make the data appear continuous. In these cases, a correction factor is supplied to GRIDPLOT for the affected areas, and the factor is adjusted until the gridded map appears smooth and continuous. Such corrections can be displayed graphically in ArcView, by examining the Data Processing themes for each element (see below). In other cases, either no correction factor can correct the discontinuity, or regional trends are absent in certain quadrangles and the data appear to be random. Such data were deleted from this CD, and the Data Processing theme will show a correction factor of zero (see, as a good example, the hafnium data in ArcView). A negative concentration of an element in the quadrangle DBF files indicates that the value is an upper limit (e.g., -10 implies <10 ). These values present a special problem in creating map coverages of geochemical data. The philosophy adopted here is a simple one: steps are taken to ensure that all upper limits fall within the lowest interval in the final map legend, and thus are known to be correctly categorized. First, two histograms are prepared for each element, one showing the concentration range of unqualified data, the other showing only upper limits For most elements, the vast majority of the data fall in the first histogram, and markers are inserted into this plot showing the values of every 5th percentile (for reference). The second histogram is displayed below the first, and compared visually. The strategy is to select a cutoff value below which upper limits are to be retained, such that they do not affect the accuracy of the map. Above this cutoff, upper limits are deleted from the final dataset. In the case shown in Fig. 1, it would be possible to construct maps using a color legend that has as its lowest interval the lowest 5th percentile of the data. Upper limits with values of <2 ppm fall unambiguously within this lowest color interval, and can be merged into the final dataset without affecting the appearance or accuracy of the map; in practice, the < is dropped, and the value multiplied by 0.5. However, those upper limits with values of <6 ppm could have real values (had they be measured more precisely) that fall anywhere within the lowest 30% of the concentration distribution. Such values cannot be assigned with certainty to the correct color interval in the map legend, and are simply deleted. The graphical result of deletions of this type may be small holes in the map where grid cells could not be assigned real values. Table 3 shows the values of these cutoffs for each of the elements compiled on this CD.
Once the data are leveled, upper limit cutoffs are established, and areas of bad data are identified, the GRIDPLOT program is run again to utilize its secondary function, which is to extract values for a single element from all 308 processed quadrangle DBF files. For the special case of uranium, GRIDPLOT was programmed to make choices about which data field to use for the final value. Uranium is typically stored in one of five fields in the original quadrangle DBF files: one labeled as CONU , the others as CONCN01, CONCN02, CONCN05, and CONUDN. The CONC05 field was given priority over the CONU field if both were filled, and data in the CONCN01 and CONCN02 fields were used in the absence of data in the first two fields. The CONUDN field (U by delayed neutron) was only coded in few percent of the samples (in only 9 quadrangles), but these data were not used here. The output from this data processing step is a series of elemental DBF files of useable NURE data.
Several major errors in the NURE HSSR data were identified and corrected during the above data-processing steps. These errors are present in the original DBF files and composite database of Hoffman and Buttleman (1994; 1996). The errors will be corrected in the a new database (Smith, 1998), but as of this time only a small part of the United States is covered by this. The data survey conducted for each quadrangle DBF file in step 1.1 uncovered a block of stream-sediment samples miscoded as stream water in seven quadrangles in the northeastern U.S. (Boston, Glen Falls, Lake Champlain, Lewiston, Newark , Scranton, and Williamsport). These records were altered to give them the correct coding prior to any data processing. In ~30,000 samples collected and analyzed by Oak Ridge Gaseous Diffusion Plant (ORGDP) and tabulated in the quadrangle DBF files, major elements (Al, Ca, Fe, K, Mg, and Na) plus As and Se were all tabulated incorrectly in units other than ppb. Over 70 quadrangles contain data affected by this problem. These records can be identified from the lack of coding in the SAMPTYP field, and a value of 4 coded in the SAMPMDC field. These problems were corrected as a group. A group of ~15,000 records found in several dozen quadrangles in the western U.S. (samples analyzed but not collected by ORGDP) also contain major element data in ppm instead of ppb, although trace elements are all coded correctly. Most of these are coded as soils (SAMPTYP=59), talus (SAMPTYP=62), or uncoded in this field (SAMPTYP=blank), and all have a value of M coded in the LTYPC field, which stands for sediment. These were also corrected by special handling. Themes with names of the form Grid: Cu are elemental concentration maps, produced from a gridded version of the point data. These bitmap files (Tiff) are based on grids made with the MINC program of Webring (1981), which employs a minimum curvature interpolation of the point data to create a smooth surface. The grid-cells used were 2 km on each side. Following the gridding operation, the program GCLR (unpublished, by R. W. Simpson, USGS, Menlo Park, Calif.) was used to produce a color-shaded relief map. The color-scheme of these maps is similar to that used in the point-data themes, as it is based upon the distribution of the underlying point data. Here, seven intervals are used, corresponding to the lowest 40th, the 40th-80th, the 80th-90th, the 90th-95th, the 95th-98th, the 98th-99th, and the 99th-100th percentiles. The legends for all these maps, showing the actual concentration values corresponding to each color interval, are shown in a special view called Gridded Elemental Map Legends. Gridded elemental map legends. This view contains an image showing the concentrations of each element corresponding to each color interval in the gridded elemental maps. Taking just the left side of this legend as an example: the gridded elemental map shown in the Arsenic Geochemistry view has its dark blue color corresponding to <2.4 ppm As, light blues representing 2.4 to 5.2 ppm, greens representing 5.2 to 7.6 ppm As, etc., up to magenta representing >22 ppm As. Note that because the grid is actually a shaded-relief rendition of the data, each color grades somewhat from high saturation (left side of color bar) to low saturation (right side of color bar).
Process_Date: 1998
Process_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Jeffrey N. Grossman
Contact_Organization: U.S. Geological Survey
Contact_Address:
Address_Type: mailing and physical address
Address: 12201 Sunrise Valley Dr.
City: Reston
State_or_Province: VA
Postal_Code: 20192
Country: USA
Contact_Electronic_Mail_Address: jgrossman@usgs.gov
Contact_Voice_Telephone: 703-648-6184
Process_Step:
Process_Description: Creation of original metadata record
Process_Date: 20110519
Process_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Tom Kress
Contact_Organization: U.S. Geological Survey
Contact_Address:
Address_Type: mailing and physical address
Address: 12201 Sunrise Valley Dr.
City: Reston
State_or_Province: VA
Postal_Code: 20192
Country: USA
Contact_Voice_Telephone: 703-648-6184
Contact_Electronic_Mail_Address: thkress@usgs.gov
Spatial_Data_Organization_Information:
Raster_Object_Information:
Raster_Object_Type: Pixel
Direct_Spatial_Reference_Method: Raster
Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Planar:
Map_Projection:
Albers_Conical_Equal_Area:
Standard_Parallel: 29.5
Longitude_of_Central_Meridian: -96.0
Latitude_of_Projection_Origin: 23.0
False_Easting: 0
False_Northing: 0
Map_Projection_Name: Albers Conical Equal Area
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: row and column
Planar_Distance_Units: kilometer
Geodetic_Model:
Horizontal_Datum_Name: North American Datum of 1927
Ellipsoid_Name: Clarke 1866
Semi-major_Axis: 6370997 meters
Denominator_of_Flattening_Ratio: 294.98
Distribution_Information:
Distributor:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Peter N Schweitzer
Contact_Organization: U.S. Geological Survey, ER
Contact_Position: Geologist
Contact_Address:
Address_Type: mailing address
Address:
Mail Stop 954
12201 Sunrise Valley Drive
City: Reston
State_or_Province: VA
Postal_Code: 20192
Country: USA
Contact_Voice_Telephone: 703-648-6533
Contact_Facsimile_Telephone: 703-648-6252
Contact_Electronic_Mail_Address: pschweitzer@usgs.gov
Resource_Description: OFR 98-622
Distribution_Liability:
The U.S. Geological Survey (USGS) provides this vector data as is. The USGS makes no guarantee or warranty concerning the accuracy of information contained in the raster data. The USGS further makes no warranties, either expressed or implied as to any other matter whatsoever, including, without limitation, the condition of the product, or its fitness for any particular purpose. The burden for determining fitness for use lies entirely with the user. Although this data has been processed successfully on computers at the USGS, no warranty, expressed or implied, is made by the USGS regarding the use of this data on any other system, nor does the fact of distribution constitute or imply any such warranty.
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Format_Name: TIFF
Format_Version_Number: 6
Format_Information_Content: Colorized images of element concentration
File_Decompression_Technique: unzip
Transfer_Size: 8.5
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Fees: none
Metadata_Reference_Information:
Metadata_Date: 20160610
Metadata_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Peter N Schweitzer
Contact_Organization: USGS Midwest Area
Contact_Position:
Collection manager, USGS Geoscience Data Clearinghouse, http://geo-nsdi.er.usgs.gov/
Contact_Address:
Address_Type: mailing address
Address:
Mail Stop 954
12201 Sunrise Valley Dr
City: Reston
State_or_Province: VA
Postal_Code: 20192-0002
Country: USA
Contact_Voice_Telephone: 703-648-6533
Contact_Facsimile_Telephone: 703-648-6252
Contact_Electronic_Mail_Address: pschweitzer@usgs.gov
Metadata_Standard_Name: Content Standard for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998

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