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Central Mineral and Environmental Resources Science Center

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Overview

Landsat 7-based material mapping of the U.S. with inset showing one Landsat scene

Maps of exposed surface mineral groups derived from automated spectral analysis of Landsat 7 ETM+ and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data are being generated for areas of the U.S. and its territories having potential for 1) undiscovered mineral deposits and (or) 2) environmental effects associated with mining and (or) unmined, hydrothermally-altered rocks. The mapping is being continually updated over the conterminous United States, and currently covers the western states with results 1,630 ASTER scenes and all of the lower 48 states with results from 447 Landsat 7 scenes.

More detailed and accurate mineral and vegetation maps generated from spectroscopic analysis of ASTER and "hyperspectral" data acquired by airborne imaging systems such as the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), HyMap, and SpecTIR are also provided for comparison with the automated analysis products. Most of these detailed maps are available over important active or abandoned mining districts.

The maps are available online for interactive viewing in a web browser. The underlying map services can be accessed using ArcMap for integration with other geospatial data. References for the maps available in the online services are listed below.

An algorithm for the automated analysis of Landsat 8 Operational Land Imager (OLI) data has been developed, and preliminary results covering the western, conterminous United States are available for viewing and analysis as an internal USGS web service. The results will be posted to the public web application after supporting documentation has been published. The new "coastal aerosol" band present in OLI data provides important new capabilities for mineral mapping which will have particular impact on geoenvironmental site assessment and monitoring.

Support for this ongoing effort has been provided by the Updated National Mineral Resource Assessment and other projects of the USGS Mineral Resources Program.

Online Map Resources

  • View comprehensive JavaScript-based web application (ideal for mobile devices): Online viewer (data updated August 10, 2017; viewer updated continually)
    • New The web application has been updated with various new features, including an "Add Data" widget Legend icon. This widget allows users to add geospatial data from their own organizations, ArcGIS Online, or elsewhere on the web to the application for integration with the currently available data. Supported data types include ArcGIS services, WMS OGC web services, shapefiles, and KML, GeoRSS, and CSV files.
    • Viewing tips:
      • If you haven't viewed the application in several weeks or longer, and (or) some features are not displaying correctly, clear your browser cache and cookies as the application may have been updated.
      • Use your mouse wheel to quickly zoom in and out.
      • To view explanations of the maps currently displayed in the viewer, click the Legend button WAB Legend icon in the top toolbar. Map explanations are also available within the Layer List WAB Layers icon.
      • To zoom to a data layer or regional study area, click the small "down arrow" icons on the right-hand edge of the Layer List WAB Layers icon, or use the bookmarks accessible from the Bookmark Tool WAB Bookmark tool icon.
      • Refreshing (F5) the application in your browser will reset the Layer List to default configuration.
      • Use the Identify and Query Tool WAB ID tool icon to query the thematic maps and determine the material(s) identified in a pixel. Start the tool, and then click on a map element (colored pixel, polygon, line, or point feature). The attributes associated with most vector-based features (points, lines, and polygons) can also be viewed simply by clicking on the features without starting the Identify Tool, and by accessing the Attribute Table via the small white tab at bottom center of the viewer. A maximum of 1,000 query results will be returned at a time. To see complete results, scroll down to the bottom of the Query or Identify widget panels.
  • View ArcGIS services in ArcMap:
    • In ArcCatalog, add a new ArcGIS Server and select "Use GIS services."
    • Add "https://www.sciencebase.gov/arcgis/services" as server URL.
    • Navigate to "usminmap" server directory.
    • Drag and Drop services into ArcMap window.
    • Integrate maps with your data.
  • View Landsat- and ASTER-derived automated products in Google Earth: KMZ file (updated January 19, 2017)

Usage Guide for Large-Area Material Maps

The large-area material maps presented here were designed to aid in the identification of mineral groups in exposed rocks, soils, mine waste rock, and mill tailings on the Earth’s surface. Many man-made materials have spectral absorption features in the shortwave infrared region of the electromagnetic spectrum that can appear similar to those of various mineral groups at the spectral and spatial resolutions of Landsat and ASTER satellite data. For example, many plastics, asphalt, and other organic materials show deep absorption between 2.30 and 2.40 micrometers caused by a C-H combination band (Clark, 1999). This absorption can mimic those of the clay-sulfate-mica-marble mineral group detectable using Landsat Thematic Mapper (Rockwell, 2013a) and Operational Land Imager data, and the carbonate-propylitic mineral group detectable using the employed ASTER data analysis methodology (Rockwell, 2012). Some construction materials, including fine aggregates used in some asphalt shingles, have absorptions near 2.2 micrometers (Clark and others, 2007) that will be identified as the sericite-smectite mineral group in the ASTER-derived results. Therefore, mineral groups are often erroneously detected in built-up areas such as cities, towns, and along roadways. Reflections between man-made objects can also result in spurious spectral responses in such areas.

Scenes of Landsat and ASTER satellite data were selected based on several criteria, the most important of which are that the presence of clouds, smoke, haze, and snow is minimized, and that the scenes be acquired as close as possible to the northern hemisphere summer solstice in mid-June to insure maximal solar irradiance (solar elevation angle) and minimal terrain shadow. The number of scene acquisition dates was minimized by selecting as many high-quality scenes from a single satellite overpass (path, or swath) as possible (optimal scenes from a single swath acquired on the same day). Given these criteria, there may be substantial differences in scene acquisition date between scenes in a given swath and between those of adjacent swaths. The varying scene acquisition dates may result in seams of identified surface materials between scenes of the same and adjacent swaths, as the automated analysis methodologies utilize statistics generated from the data being processed, which are most often individual scenes. Most Landsat and ASTER scenes are analyzed individually and the resultant maps are then mosaicked into a single map. In rare cases, several scenes are mosaicked together prior to analysis. Variations in soil moisture and vegetation growth stage between scenes are another possible cause of seams in analysis results.

ASTER visible to near-infrared (VNIR) and short-wave infrared (SWIR) data are each collected by a unique telescope and detector array. In rare cases, the data in an ASTER scene collected by these two sensor systems are geometrically mis-registered to each other, resulting in corrupted pixel spectra. The VNIR data of one pixel will be combined with the SWIR data of another pixel located 30-100 meters away. For such scenes, the automated analysis methodology will result in an overabundance of pixels identified as “advanced argillic +/- ferric iron” (assigned a color of red in the maps) in areas where clay, sulfate, and mica minerals are abundant. Examples of scenes with such erroneous results are in the Independence Range in northern Nevada, and the area surrounding the Tintic mining district in the East Tintic Mountains near Eureka, Utah.

Suggested Citation

Rockwell, B.W., Bonham, L.C., and Giles, S.A., 2015, USGS National Map of Surficial Mineralogy: U.S. Geological Survey Online Map Resource. Available at https://minerals.cr.usgs.gov/cmerwebmap/usminmap.html.

Additional Information

DMT poster thumbnail

A poster describing the National Map of Surficial Mineralogy was presented at the Digital Mapping Techniques (DMT) 2013 conference.

References

  • Ashley, R.P., 1975, Preliminary geologic map of the Goldfield mining district, Nevada: U.S. Geological Survey Miscellaneous Field Studies Map MF-681, 1:24,000 scale.
  • Clark, R.N., 1999, Spectroscopy of rocks and minerals, and principles of spectroscopy, in Rencz, A.N., ed., Remote sensing for the earth sciences, in Ryerson, R.A., ed., Manual of remote sensing, Volume 3: New York, John Wiley, p. 3-58. Available at https://speclab.cr.usgs.gov/PAPERS.refl-mrs/refl4.html.
  • Clark, R.N., Swayze, G.A., Wise, R., Livo, K.E., Hoefen, T.M., Kokaly, R.F., and Sutley, S.J., 2007, USGS Digital Spectral Library splib06a, U.S. Geological Survey Digital Data Series 231. Available at https://speclab.cr.usgs.gov/spectral.lib06/ds231/index.html.
  • Cunningham, C.G., Rye, R.O., Rockwell, B.W., Kunk, M.J., and Councell, T.B., 2005, Supergene destruction of a hydrothermal replacement alunite deposit at Big Rock Candy Mountain, Utah: mineralogy, spectroscopic remote sensing, stable isotope and argon age evidences: Chemical Geology, vol. 215, issues 1-4, pp. 317-337. Available at https://dx.doi.org/10.1016/j.chemgeo.2004.06.055.
  • Dalton, J.B., Bove, D.J., and Mladinich, C.S., 2005, Remote sensing characterization of the Animas River watershed, southwestern Colorado, by AVIRIS imaging spectroscopy: U.S. Geological Survey Scientific Investigations Report 2004-5203, 49 p. Available at https://pubs.usgs.gov/sir/2004/5203/.
  • Dalton, J.B., Bove, D.J., Mladinich, C.S., and Rockwell, B.W., 2007, Imaging spectroscopy applied to the Animas River watershed and Silverton caldera, in Church, S.E., von Guerard, P., and Finger, S.E., eds., Integrated investigations of environmental effects of historical mining in the Animas River watershed, San Juan County, Colorado: U.S. Geological Survey Professional Paper 1651, pp. 143-159. Available at https://pubs.usgs.gov/pp/1651/downloads/Vol1_combinedChapters/vol1_chapE2.pdf. [pdf file, 10 MB]
  • Fernette, G. and Rockwell, B.W., 2014, Compilation of mineral deposit footprints in the central and northern Carlin trend, Nevada: U.S. Geological Survey Digital Data Series, in preparation. Download list of references. [pdf file, 63 KB]
  • Horton, J.D., 2017, The State Geologic Map Compilation (SGMC) geodatabase of the conterminous United States (ver. 1.1, August 2017): U.S. Geological Survey data release, https://doi.org/10.5066/F7WH2N65. Download list of references (from USGS DS1052). [pdf file, 67.5 KB]
  • Horton, J.D., San Juan, C.A., and Stoeser, D.B, 2017, The State Geologic Map Compilation (SGMC) geodatabase of the conterminous United States (ver. 1.1, August 2017): U.S. Geological Survey Data Series 1052, 46 p. Available at https://doi.org/10.3133/ds1052.
  • John, D.A., Rockwell, B.W., Henry, C.D., and Colgan, J.P., 2010, Hydrothermal alteration of the late Eocene Caetano ash-flow caldera, north-central Nevada: a field and ASTER remote sensing study, in 2010 Symposium Volume: Geological Society of Nevada, Reno, Nevada, May 14-22, 2010, pp. 1055-1083.
  • Logicon Geodynamics, 1997, Multispectral imagery reference guide: Fairfax, Virginia, pp. 6-5.
  • Long, K.R., DeYoung, J.H., Jr., and Ludington, S.D., 1998, Database of significant deposits of gold, silver, copper, lead, and zinc in the United States: U. S. Geological Survey Open-File Report 98-206 A,B, 33 pp. Available at https://pubs.usgs.gov/of/1998/0206a-b/.
  • Rockwell, B.W., 2009, Comparison of ASTER- and AVIRIS-derived mineral and vegetation maps of the White Horse replacement alunite deposit and surrounding area, Marysvale volcanic field, Utah: U.S. Geological Survey Scientific Investigations Report 2009-5117, 31 p. Available at https://pubs.usgs.gov/sir/2009/5117/.
  • Rockwell, B.W., 2010a, Mineral and vegetation maps of the Bodie Hills, Sweetwater Mountains, and Wassuk Range, California/Nevada, generated from ASTER satellite data: U.S. Geological Survey Scientific Investigations Map 3104, scale 1:62,000, 4 plates, pamphlet, 5 p. Available at https://pubs.usgs.gov/sim/3104/.
  • Rockwell, B.W., 2010b, Evaluation of detailed and automated methodologies for hydrothermal alteration mapping from space: application to geoenvironmental and mineral resource assessments at the scale of watersheds and permissive tracts (abstract and multimedia PowerPoint presentation): Geological Society of America Annual Meeting, October 31-November 3, 2010, Denver, Colorado. Available at https://gsa.confex.com/gsa/2010AM/finalprogram/abstract_179892.htm.
  • Rockwell, B.W., 2012, Description and validation of an automated methodology for mapping mineralogy, vegetation, and hydrothermal alteration type from ASTER satellite imagery with examples from the San Juan Mountains, Colorado: U.S. Geological Survey Scientific Investigations Map 3190, 35 p. pamphlet, 5 map sheets, scale 100,000. Available at https://pubs.usgs.gov/sim/3190/.
  • Rockwell, B.W., 2013a, Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado: U.S. Geological Survey Scientific Investigations Map 3252, 25 p. pamphlet, 1 map sheet, scale 1:325,000. Available at https://pubs.usgs.gov/sim/3252/.
  • Rockwell, B.W., 2013b, Comparative mineral mapping in the Colorado Mineral Belt using AVIRIS and ASTER remote sensing data: U.S. Geological Survey Scientific Investigations Map 3256, 8 p. pamphlet, 1 map sheet, scale 1:150,000. Available at https://pubs.usgs.gov/sim/3256/.
  • Rockwell, B.W. and Bonham, L.C., 2017, Digital maps of hydrothermal alteration type, key mineral groups, and green vegetation of the western United States derived from automated analysis of ASTER satellite data: U.S. Geological Survey data release, https://doi.org/10.5066/F7CR5RK7.
  • Rockwell, B.W., Clark, R.N., Livo, K.E., McDougal, R.R., Kokaly, R.F., and Vance, J.S., 1999, Preliminary materials mapping in the Park City region for the Utah USGS-EPA Imaging Spectroscopy Project using both high- and low-altitude AVIRIS data, in Green, R.O., ed., Summaries of the 8th Annual JPL Airborne Earth Science Workshop, NASA JPL Publication 99-17: NASA Jet Propulsion Laboratory, Pasadena, California, USA, pp. 365-375. Available at https://speclab.cr.usgs.gov/earth.studies/Utah-1/park_cityAV5.html.
  • Rockwell, B.W., Cunningham, C.G., Breit, G.N., and Rye, R.O., 2006, Spectroscopic mapping of the White Horse alunite deposit, Marysvale volcanic field, Utah: evidence of a magmatic component: Economic Geology, vol. 101, no. 7, pp. 1377-1395, doi: 10.2113/gsecongeo.101.7.1377. Available at https://econgeol.geoscienceworld.org/content/101/7/1377.
  • Rockwell, B.W. and Hofstra, A.H., 2008, Identification of quartz and carbonate minerals across northern Nevada using ASTER thermal infrared emissivity data-Implications for geologic mapping and mineral resource investigations in well-studied and frontier areas: Geosphere, vol. 4, no. 1, pp. 218-246, doi: 10.1130/GES00126.1. Available at https://geosphere.gsapubs.org/content/4/1/218.
  • Rockwell, B.W. and Hofstra, A.H., 2009, Remote detection of argillic alteration in quartzites and quartz arenites above and distal to porphyry Cu and Mo deposits: implications for assessments of concealed deposits, in Rocky Mountain Sectional Meeting Abstracts with Programs: Geological Society of America, Orem, Utah, May 11-13, 2009, vol. 41, no. 6, p. 6. Available at https://gsa.confex.com/gsa/2009RM/finalprogram/abstract_157797.htm.
  • Rockwell, B.W. and Hofstra, A.H., 2012, Mapping argillic and advanced argillic alteration in volcanic rocks, quartzites, and quartz arenites in the western Richfield 1° x 2° quadrangle, southwestern Utah, using ASTER satellite data: U.S. Geological Survey Open-File Report 2012-1105, 5 p., 1 plate, 2 geospatial PDF maps. Available at https://pubs.usgs.gov/of/2012/1105/.
  • Rockwell, B.W., McDougal, R.R., and Gent, C.A., 2005, Remote sensing for environmental site screening and watershed evaluation in Utah mine lands: East Tintic Mountains, Oquirrh Mountains, and Tushar Mountains: U.S. Geological Survey Scientific Investigations Report 2004-5241, 84 p. Available at https://pubs.usgs.gov/sir/2004/5241/. A full HTML-format version of the report is available at https://speclab.cr.usgs.gov/earth.studies/Utah-1/sir5241txto_bredit.html. View project overview.
  • Serna-Isaza, M.J., 1971, Geology and geochemistry of Calico Peak, Dolores County, Colorado: Colorado School of Mines M.S. Thesis T-1338, Golden, Colorado.
  • Smailbegovic, A., Rockwell, B.W., Taranik, J.V., and LaVeigne, J., 2003, A comparison of the new generation airborne and spaceborne hyperspectral imaging for mineral mapping in Cuprite, Nevada: ASTER, Hyperion, AVIRIS, HyMap, and HyperSpecTIR, in Proceedings: International Symposium on Spectral Sensing Research 2003 (ISSSR 2003), Santa Barbara, California, June 2-6, 2003.