Keith E. Livo

Evaluating Minerals of Environmental Concern Using Spectroscopy

Imaging spectroscopy has been successfully used to aid researchers in characterizing potential environmental impacts posed by acid-rock drainage, ore-processing dust on mangroves, and asbestos in serpentine mineral deposits and urban dust. Many of these applications synergistically combine field spectroscopy with remote sensing data, thus allowing more-precise data calibration, spectral analysis of the data, and verification of mapping. The increased accuracy makes these environmental evaluation tools efficient because they can be used to focus field work on those areas most critical to the research effort. The use of spectroscopy to evaluate minerals of environmental concern pushes current imaging spectrometer technology to its limits; we present laboratory results that indicate the direction for future designs of imaging spectrometers.

Ultraviolet to near-infrared spectroscopy of REE-bearing materials

Increasing worldwide demand for many of our natural resources requires that we reassess our geologic models and expand our search for rare earth element (REE) resources in the United States. Currently, there is a lack of sufficient spectroscopic investigations characterizing surface materials associated with many of the potential REE-bearing deposit types. Understanding the spectral properties of these deposits using ultraviolet (UV) to near-infrared (NIR) spectroscopic methods will add significant information about how we assess such deposits in the future using laboratory spectrometers, core scanning systems, and imaging spectrometers. Spectra of lanthanide-bearing materials show fine structure in the UV to NIR wavelengths of the electromagnetic spectrum that are caused by 4/-4/ intraconfigurational electron transitions of lanthanide ions present in the material [1]. Lanthanide-bearing minerals produce sharp spectral absorptions that allow for accurate identification of these minerals when found in significant concentrations and can also be used to identify the type of lanthanides based on the position of their absorptions.

Hyperspectral surface materials map of quadrangles 3360 and 3460, Kawir-e Naizar (413), Kohe-Mahmudo-Esmailjan (414), Kol-e Namaksar (407), and Ghoriyan (408) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

HYPERSPECTRAL SURFACE MATERIALS MAP OF QUADRANGLES 3360 AND 3460, KAWIR-E NAIZAR (413), KOHE-MAHMUDO-ESMAILJAN (414), KOL-E NAMAKSAR (407), AND GHORIYAN (408) QUADRANGLES, AFGHANISTAN, SHOWING IRON-BEARING MINERALS AND OTHER MATERIALS By Trude V.V. King, Todd M. Hoefen, Raymond F. Kokaly, Keith E. Livo, Michaela R. Johnson, and Stuart A. Giles 2013 SCALE 1:250 000 5 5 0 10 15 20 25 30 35 40 KILOMETERS 10 5 0 5 15 20 MILES Cultural data from digital files from Afghanistan Information Management Service (http://www.aims.org.af) Projection: Universal Transverse Mercator, Zone 41, WGS 1984 Datum Figure 1.—Provinces and selected cities, towns, and villages in the map area. Topography is shown as shaded relief. EXPLANATION OF MATERIAL CLASSES USGS OPEN-FILE REPORT 2013–1203–B AGS OPEN-FILE REPORT (413/414/407/408) 2013–1203–B USGS Afghanistan Project Product No. 226 U.S. DEPARTMENT OF THE INTERIOR U.S. GEOLOGICAL SURVEY AFGHANISTAN MINISTRY OF MINES AFGHANISTAN GEOLOGICAL SURVEY Prepared in cooperation with the U.S. Geological Survey under the auspices of the U.S. Department of Defense Task Force for Business and Stability Operations

Hyperspectral surface materials map of quadrangles 3664 and 3764, Char Shengo (123), Shibirghan (124), Jalajin (117), and Kham-Ab (118) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

124 123 3664 118 117 3764 REFERENCES CITED Clark, R.N., Swayze, G.A., Wise, R.A, Livo, K.E., Hoefen, T.M., Kokaly, R.F., and Sutley, S.J., 2007, USGS digital spectral library splib06a: U.S. Geological Survey Data Series 231. King, T.V.V., Kokaly, R.F., Hoefen, T.M., Dudek, K.B., and Livo, K.E., 2011, Surface materials map of Afghanistan; iron-bearing minerals and other materials: U.S. Geological Survey Scientific Investigations Map 3152–B, one sheet, scale 1:1,100,000. Kokaly, R.F., King, T.V.V., and Hoefen, T.M., 2013, Surface mineral maps of Afghanistan derived from HyMapTM imaging spectrometer data, version 2: U.S. Geological Survey Data Series 787. Kokaly, R.F., King, T.V.V., and Livo, K.E., 2008, Airborne hyperspectral survey of Afghanistan 2007; flight line planning and HyMapTM data collection: U.S. Geological Survey Open-File Report 2008–1235, 14 p. DATA SUMMARY This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMapTM imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007 (Kokaly and others, 2008). This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan and is a subset of the version 2 map of the entire country showing iron-bearing minerals and other materials (Kokaly and others, 2013). This version 2 map improved mineral mapping from the previously published version (King and others, 2011) by refining the classification procedures, especially in areas having wet soils. The version 2 map more accurately represents the mineral distributions and contains an additional mineral classification (FeFe type 3). Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMapTM imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMapTM imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials (Clark and others, 2007). Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated. Minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra. Further information regarding the processing procedures is presented in King and others (2011) and Kokaly and others (2013). International boundary City, town, or village Peak; elevation in meters 3725

Hyperspectral surface materials map of quadrangles 3664 and 3764, Char Shengo (123), Shibirghan (124), Jalajin (117), and Kham-Ab (118) quadrangles, Afghanistan, showing carbonates, phyllosilicates, sulfates, altered minerals, and other materials

124 123 3664 118 117 3764 DATA SUMMARY This map shows the spatial distribution of selected carbonates, phyllosilicates, sulfates, altered minerals, and other materials derived from analysis of airborne HyMapTM imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007 (Kokaly and others, 2008). This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan and is a subset of the version 2 map of the entire country showing carbonates, phyllosilicates, sulfates, altered minerals, and other materials (Kokaly and others, 2013). This version 2 map improved mineral mapping from the previously published version (Kokaly and others, 2011) by refining the classification procedures, especially in areas having wet soils. The version 2 map more accurately represents the mineral distributions and contains modifications to the material class names, as well as an additional mineral classification (Carbonate and clay/muscovite). Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMapTM imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMapTM imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials (Clark and others, 2007). Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated. Minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Epidote or chlorite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra. Further information regarding the processing procedures is presented in Kokaly and others (2011, 2013).