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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Frequently anticipated questions:

What does this data set describe?

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
A subset of the National Uranium Resource Evaluation (NURE) Hydrogeochemical and Stream Sediment Reconnaissance (HSSR) data were used to produce a set of map images depicting the general geochemistry of the conterminous US.

Approxiamately 260,000 samples from the continental US were analyzed. These 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: Na, Ti, Fe, Cu, Zn, As, Ce, Hf, Pb, Th, and U.
Because the NURE HSSR data have been processed by the author for the production of these images, the user must use a degree of caution in interpreting the maps produced here. One must understand the methods used in deriving the data in order to judge the significance of any particular map feature. For reference, the raw data used to produce these images are available in digital form (Hoffman and Buttleman, 1996), for examination by sophisticated users.
  1. How might this data set be cited?
    Grossman, Jeffrey N., 1998, 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: U.S. Geological Survey Open-File Report 98-622, U.S. Geological Survey, Reston, VA.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -179.1
    East_Bounding_Coordinate: -67.764
    North_Bounding_Coordinate: 70.0
    South_Bounding_Coordinate: 19.003
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 1964
    Ending_Date: 1995
    publication date
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: raster digital data
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
      This is a Raster data set. It contains the following raster data types:
      • Dimensions, type Pixel
    2. What coordinate system is used to represent geographic features?
      The map projection used is Albers Conical Equal Area.
      Projection parameters:
      Standard_Parallel: 29.5
      Longitude_of_Central_Meridian: -96.0
      Latitude_of_Projection_Origin: 23.0
      False_Easting: 0
      False_Northing: 0
      Planar coordinates are encoded using row and column
      Abscissae (x-coordinates) are specified to the nearest 1
      Ordinates (y-coordinates) are specified to the nearest 1
      Planar coordinates are specified in kilometer
      The horizontal datum used is North American Datum of 1927.
      The ellipsoid used is Clarke 1866.
      The semi-major axis of the ellipsoid used is 6370997.
      The flattening of the ellipsoid used is 1/294.98.
  7. How does the data set describe geographic features?
    Following the gridding operation, the program GCLR written by R.W. Simpson of USGS in Menlo Park, California 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 were 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 image called Scalebar.tif. It shows the concentrations of each element corresponding to each color interval in the gridded elemental maps.
    Files Scalebar.tif and Atlashlp.doc within

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Jeffrey N. Grossman
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    Jeffrey N. Grossman
    U.S. Geological Survey
    12201 Sunrise Valley Dr.
    Reston, VA

    703 648-6184 (voice)

Why was the data set created?

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 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 (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 large part 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.

How was the data set created?

  1. From what previous works were the data drawn?
    DDS-18-A (source 1 of 3)
    Hoffman, James D., and Buttleman, Kim, 1994, National Geochemical Data Base: National Uranium Resource Evaluation Data for the Conterminous United States: U.S. Geological Survey Digital Data Series DDS-18-B.

    Type_of_Source_Media: CD-ROM
    Source_Contribution: chemical analyses
    DDS-18-B (source 2 of 3)
    Hoffman, James D., and Buttleman, Kim, 1996, National Geochemical Data Base: 1. National Uranium Resource Evaluation (NURE) Hydrogeochemical and Stream Sediment Reconnaissance (HSSR) data for Alaska, formatted for GSSEARCH data base software; 2. NURE HSSR Data formatted as dBASE files for Alaska and the conterminous United States; 3. NURE HSSR Data for Alaska and the conterminous United States as originally compiled by the Department of Energy: U.S. Geological Survey Digital Data Series DDS-18-B.

    Type_of_Source_Media: CD-ROM
    308 quadrangle files covering the continental US 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. Records covering these sample media were used to produce these images.
    DDS-47 (source 3 of 3)
    Baedecker, Phillip A., Grossman, Jeffrey N., and Buttleman, Kim P., 1998, National Geochemical Data Base: PLUTO geochemical data base for the United States: U.S. Geological Survey Digital Data Series DDS-47.

    Type_of_Source_Media: CD-ROM
    Source_Contribution: Information from the PLUTO database
  2. How were the data generated, processed, and modified?
    Date: 1998 (process 1 of 2)
    These images were made by examining 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.

    The starting point for the data processing that yielded these images 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. Records covering these sample media were used to produce these images.

    Initial data processing and clean-up

    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:

    1.1 Record selection

    Records were extracted from the quadrangle DBF files for the appropriate sample media using one or more of the following field codes. (See Hoffman and Buttleman, 1994, for explanation of codes.)

    Database field    Sediment codes   Soil codes
     SAMPLE           2.x or 2.xx      3.x
     SAMPMDC          4
     LTYPC            M
     SAMPTYP          11,12,13,14,15   58,59
    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.

    1.2 Field selection

    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).

    1.3 Data scaling

    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 weight percent for major elements (Al, Ca, Fe, K, Mg, and Na).

    1.4 Record consolidation

    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.

    Secondary data processing

    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 ( for example <10 ppm).

    2.1 Data surveying

    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. Systematic errors that were not found during primary data processing could 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 were handled through the data leveling procedure described next.

    2.2 Data leveling

    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 (that is, 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. 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 discarded and not used to produce these images.

    2.3 Data below detection limits

    A negative concentration of an element in the quadrangle DBF files indicates that the value is an upper limit (for example -10 means <10). These values present a special problem in creating map coverages of geochemical data. The philosophy adopted here is simple: steps were taken to ensure that all such upper limits fall within the lowest interval in the final map legend, and thus are known to be correctly categorized.

    First, two histograms were 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 fell in the first histogram, and markers were inserted into this plot showing the values of every 5th percentile (for reference). The second histogram was displayed below the first and compared visually. The strategy was 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 value, upper limits are deleted from the final dataset. The graphical result of deletions of this type are small holes in the map where grid cells could not be assigned real values.

    2.4 Data extraction

    Once the data were leveled, upper limit cutoffs were established, and areas of bad data were identified, the GRIDPLOT program was run again 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.

    Major errors corrected

    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.

    3.1 Miscoded samples

    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.

    3.2 Data in incorrect units

    In about 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.

    About 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.

    Data products

    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.

    Person who carried out this activity:
    Jeffrey N. Grossman
    U.S. Geological Survey
    12201 Sunrise Valley Dr.
    Reston, VA

    703-648-6184 (voice)
    Date: 15-Jan-2021 (process 2 of 2)
    Modified metadata to eliminate structural errors in the document. A few elements have been filled with arbitrary values because the precise values are not known: abscissa resolution, ordinate resolution, source contribution for Buttleman 1994. Contact information was updated, URLs were converted to https from http where applicable. Person who carried out this activity:
    Peter N Schweitzer
    USGS Geology, Energy, and Minerals Science Center
    Mail Stop 954
    12201 Sunrise Valley Dr
    Reston, VA

    703-648-6533 (voice)
    703-648-6252 (FAX)
  3. What similar or related data should the user be aware of?

How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?
    Issues relating to the analytical methods are best discussed in some of the source materials generated by the NURE program. In addition, a number of problems relating to the variability of the lower limit of detection were encountered during the processing of the data for these images. To some extent the categorization of element concentration into classes covered up some of these discrepancies.
  2. How accurate are the geographic locations?
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    Since the images are based on data from surveyed quadrangles, holes both large and small occur in the images. Large holes are typically the size and shape of groups of quadrangles, and the data were either unavailable in the source information or were discarded for reasons having to do with errors or inconsistencies found during processing. None of the maps shows continuous data for the entire area.
  5. How consistent are the relationships among the observations, including topology?
    A variety of data problems were identified during the processing that led to the production of these map images. Most of these have satisfactory solutions, but the user must review the processing steps to judge whether they are appropriate for new uses.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints: None
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.
  1. Who distributes the data set? (Distributor 1 of 1)
    Peter N Schweitzer
    USGS Geology, Energy, and Minerals Science Center
    12201 Sunrise Valley Drive
    Reston, VA

    703-648-6533 (voice)
    703-648-6252 (FAX)
  2. What's the catalog number I need to order this data set?
  3. What legal disclaimers am I supposed to read?
    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.
  4. How can I download or order the data?
    • Availability in digital form:
      Data format: Map images showing element concentration in format TIFF (version 6.0) Size: 8.5
      Network links:
    • Cost to order the data: none

Who wrote the metadata?

Last modified: 29-Dec-2020
Metadata author:
Peter N Schweitzer
USGS Geology, Energy, and Minerals Science Center
12201 Sunrise Valley Drive
Reston, VA

703-648-6533 (voice)
703-648-6252 (FAX)
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)

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