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USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Panjsher Valley mineral district in Afghanistan: Chapter M in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Panjsher Valley mineral district, which has emerald and silver-iron deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2009, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Panjsher Valley) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the Panjsher Valley area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Panjsher Valley study area, two subareas were designated for detailed field investigations (that is, the Emerald and Silver-Iron subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.

Panjsher Valley Mineral District↗
USGS2012

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Khanneshin mineral district in Afghanistan: Chapter A in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Khanneshin mineral district, which has uranium, thorium, rare-earth-element, and apatite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (41 for Khanneshin) and the WGS84 datum. The final image mosaics were subdivided into nine overlapping tiles or quadrants because of the large size of the target area. The nine image tiles (or quadrants) for the Khanneshin area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Khanneshin study area, one subarea was designated for detailed field investigations (that is, the Khanneshin volcano subarea); this subarea was extracted from the area's image mosaic and is provided as separate embedded geotiff images.

Helm;Nimroz↗
USGS2014

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni2 mineral district, which has spectral reflectance anomalies indicative of gold, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Ghazni2) and the WGS84 datum. The images for the Ghazni2 area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Ghazni2 Mineral District↗
USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Bamyan mineral district in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the South Bamyan mineral district, which has areas with a spectral reflectance anomaly that require field investigation. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008),but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for South Bamyan) and the WGS84 datum. The final image mosaics for the South Bamyan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

South Bamyan Mineral District↗
USGS2014

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni1 mineral district, which has spectral reflectance anomalies indicative of clay, aluminum, gold, silver, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Ghazni1) and the WGS84 datum. The images for the Ghazni1 area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Ghazni1 Mineral District↗
USGS2014

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Farah mineral district, which has spectral reflectance anomalies indicative of copper, zinc, lead, silver, and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (41 for Farah) and the WGS84 datum. The final image mosaics were subdivided into four overlapping tiles or quadrants because of the large size of the target area. The four image tiles (or quadrants) for the Farah area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Farah study area, five subareas were designated for detailed field investigations (that is, the FarahA through FarahE subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.

Farah Mineral District↗
USGS2012

Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This DS consists of the locally enhanced ALOS image mosaics for each of the 24 mineral project areas (referred to herein as areas of interest), whose locality names, locations, and main mineral occurrences are shown on the index map of Afghanistan (fig. 1). ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency, but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. PRISM image orthorectification for one-half of the target areas was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using SPARKLE logic, which is described in Davis (2006). Each of the four-band images within each resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a specified radius that was usually 500 m. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (either 41 or 42) and the WGS84 datum. Most final image mosaics were subdivided into overlapping tiles or quadrants because of the large size of the target areas. The image tiles (or quadrants) for each area of interest are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Approximately one-half of the study areas have at least one subarea designated for detailed field investigations; the subareas were extracted from the area's image mosaic and are provided as separate embedded geotiff images.

Data Series↗
USGS2010

The principal rare earth elements deposits of the United States: A summary of domestic deposits and a global perspective

The rare earth elements (REE) are fifteen elements with atomic numbers 57 through 71, from lanthanum to lutetium ('lanthanides'), plus yttrium (39), which is chemically similar to the lanthanide elements and thus typically included with the rare earth elements. Although industrial demand for these elements is relatively small in tonnage terms, they are essential for a diverse and expanding array of high-technology applications. REE-containing magnets, metal alloys for batteries and light-weight structures, and phosphors are essential for many current and emerging alternative energy technologies, such as electric vehicles, energy-efficient lighting, and wind power. REE are also critical for a number of key defense systems and other advanced materials. Section 843 of the National Defense Authorization Act for Fiscal Year 2010, Public Law 111-84, directs the Comptroller General to complete a report on REE materials in the defense supply chain. The Office of Industrial Policy, in collaboration with other U.S. Government agencies, has initiated (in addition to this report) a detailed study of REE. This latter study will assess the Department of Defense's use of REE, as well as the status and security of domestic and global supply chains. That study will also address vulnerabilities in the supply chain and recommend ways to mitigate any potential risks of supply disruption. To help conduct this study, the Office of Industrial Policy asked the U.S. Geological Survey (USGS) to report on domestic REE reserves and resources in a global context. To this end, the enclosed report is the initial USGS contribution to assessing and summarizing the domestic REE resources in a global perspective. In 2009, the Mineral Resources Program of the USGS organized a new project under the title Minerals at Risk and For Emerging Technologies in order to evaluate mineral resource and supply issues of rare metals that are of increasing importance to the national economy. Leaders and members of this project, with the assistance of the USGS National Minerals Information Center, prepared the enclosed USGS report on domestic REE resources. The USGS Mineral Resources Program has investigated domestic and selected foreign REE resources for many decades, and this report summarizes what has been learned from this research. The USGS National Minerals Information Center (formerly Minerals Information Team) has monitored global production, trade, and resources for an equally long period and is the principal source of statistics used in this report. The objective of this study is to provide a nontechnical overview of domestic reserves and resources of REE and possibilities for utilizing those resources. At the present time, the United States obtains its REE raw materials from foreign sources, almost exclusively from China. Import dependence upon a single country raises serious issues of supply security. In a global context, domestic REE resources are modest and of uncertain value; hence, available resources in traditional trading partners (such as Canada and Australia) are of great interest for diversifying sources of supply. This report restates basic geologic facts about REE relevant to assessing security of supply, followed by a review of current United States consumption and imports of REE, current knowledge of domestic resources, and possibilities for future domestic production. Further detail follows in a deposit-by-deposit review of the most significant domestic REE deposits (see index map). Necessary steps to develop domestic resources are discussed in a separate section, leading into a review of current domestic exploration and a discussion of the value of a future national mineral resource assessment of REE. The report also includes an overview of known global REE resources and discusses the reliability of alternative foreign sources of REE.

Scientific Investigations Report↗
USGS1970

Study and interpretation of the chemical characteristics of natural water

The chemical composition of natural water is derived from many different sources of solutes, including gases and aerosols from the atmosphere, weathering and erosion of rocks and soil, solution or precipitation reactions occurring below the land surface, and cultural effects resulting from activities of man. Some of the processes of solution or precipitation of minerals can be closely evaluated by means of principles of chemical equilibrium including the law of mass action and the Nernst equation. Other processes are irreversible and require consideration of reaction mechanisms and rates. The chemical composition of the crustal rocks of the earth and the composition of the ocean and the atmosphere are significant in evaluating sources of solutes in natural fresh water. The ways in which solutes are taken up or precipitated and the amounts present in solution are influenced by many environmental factors, especially climate, structure and position: of rock strata, and biochemical effects associated with life cycles of plants and animals, both microscopic and macroscopic. Taken all together and in application with the further influence of the general circulation of all water in the hydrologic cycle, the chemical principles and environmental factors form a basis for the developing science of natural-water chemistry. Fundamental data used in the determination of water quality are obtained by the chemical analysis of water samples in the laboratory or onsite sensing of chemical properties in the field. Sampling is complicated by changes in composition of moving water and the effects of particulate suspended material. Most of the constituents determined are reported in gravimetric units, usually milligrams per liter or milliequivalents per liter. More than 60 constituents and properties are included in water analyses frequently enough to provide a basis for consideration of the sources from which each is generally derived, most probable forms of elements and ions in solution, solubility controls, expected concentration ranges and other chemical factors. Concentrations of elements that are commonly present in amounts less than a few tens of micrograms per liter cannot always be easily explained, but present information suggests many are controlled by solubility of hydroxide or carbonate or by sorption on solid particles. Chemical analyses may be grouped and statistically evaluated by averages, frequency distributions, or ion correlations to summarize large volumes of data. Graphing of analyses or of groups of analyses aids in showing chemical relationships among waters, probable sources of solutes, areal water-quality regimen, and water-resources evaluation. Graphs may show water type based on chemical composition, relationships among ions, or groups of ions in individual waters or many waters considered simultaneously. The relationships of water quality to hydrologic parameters, such as stream discharge rate or ground-water flow patterns, can be shown by mathematical equations, graphs, and maps. About 75 water analyses selected from the literature are tabulated to illustrate the relationships described, and some of these, along with many others that are not tabulated, are also utilized in demonstrating graphing and mapping techniques. Relationships of water composition to source rock type are illustrated by graphs of some of the tabulated analyses. Activities of man may modify water composition extensively through direct effects of pollution and indirect results of water development, such as intrusion of sea water in ground-water aquifiers. Water-quality standards for domestic, agricultural, and industrial use have been published by various agencies. Irrigation project requirements for water quality are particularly intricate. Fundamental knowledge of processes that control natural water composition is required for rational management of water quality.

Water Supply Paper↗
USGS1959

Study and interpretation of the chemical characteristics of natural water

The chemical composition of natural water is derived from many different sources of solutes, including gases and aerosols from the atmosphere, weathering and erosion of rocks and soil, solution or precipitation reactions occurring below the land surface, and cultural effects resulting from activities of man. Some of the processes of solution or precipitation of minerals can be closely evaluated by means of principles of chemical equilibrium including the law of mass action and the Nernst equation. Other processes are irreversible and require consideration of reaction mechanisms and rates. The chemical composition of the crustal rocks of the earth and the composition of the ocean and the atmosphere are significant in evaluating sources of solutes in natural fresh water. The ways in which solutes are taken up or precipitated and the amounts present in solution are influenced by many environmental factors, especially climate, structure and position: of rock strata, and biochemical effects associated with life cycles of plants and animals, both microscopic and macroscopic. Taken all together and in application with the further influence of the general circulation of all water in the hydrologic cycle, the chemical principles and environmental factors form a basis for the developing science of natural-water chemistry. Fundamental data used in the determination of water quality are obtained by the chemical analysis of water samples in the laboratory or onsite sensing of chemical properties in the field. Sampling is complicated by changes in composition of moving water and the effects of particulate suspended material. Most of the constituents determined are reported in gravimetric units, usually milligrams per liter or milliequivalents per liter. More than 60 constituents and properties are included in water analyses frequently enough to provide a basis for consideration of the sources from which each is generally derived, most probable forms of elements and ions in solution, solubility controls, expected concentration ranges and other chemical factors. Concentrations of elements that are commonly present in amounts less than a few tens of micrograms per liter cannot always be easily explained, but present information suggests many are controlled by solubility of hydroxide or carbonate or by sorption on solid particles. Chemical analyses may be grouped and statistically evaluated by averages, frequency distributions, or ion correlations to summarize large volumes of data. Graphing of analyses or of groups of analyses aids in showing chemical relationships among waters, probable sources of solutes, areal water-quality regimen, and water-resources evaluation. Graphs may show water type based on chemical composition, relationships among ions, or groups of ions in individual waters or many waters considered simultaneously. The relationships of water quality to hydrologic parameters, such as stream discharge rate or ground-water flow patterns, can be shown by mathematical equations, graphs, and maps. About 75 water analyses selected from the literature are tabulated to illustrate the relationships described, and some of these, along with many others that are not tabulated, are also utilized in demonstrating graphing and mapping techniques. Relationships of water composition to source rock type are illustrated by graphs of some of the tabulated analyses. Activities of man may modify water composition extensively through direct effects of pollution and indirect results of water development, such as intrusion of sea water in ground-water aquifiers. Water-quality standards for domestic, agricultural, and industrial use have been published by various agencies. Irrigation project requirements for water quality are particularly intricate. Fundamental knowledge of processes that control natural water composition is required for rational management of water quality.

Water Supply Paper↗
USGS1985

Study and interpretation of the chemical characteristics of natural water

The chemical composition of natural water is derived from many different sources of solutes, including gases and aerosols from the atmosphere, weathering and erosion of rocks and soil, solution or precipitation reactions occurring below the land surface, and cultural effects resulting from human activities. Broad interrelationships among these processes and their effects can be discerned by application of principles of chemical thermodynamics. Some of the processes of solution or precipitation of minerals can be closely evaluated by means of principles of chemical equilibrium, including the law of mass action and the Nernst equation. Other processes are irreversible and require consideration of reaction mechanisms and rates. The chemical composition of the crustal rocks of the Earth and the composition of the ocean and the atmosphere are significant in evaluating sources of solutes in natural freshwater. The ways in which solutes are taken up or precipitated and the amounts present in solution are influenced by many environmental factors, especially climate, structure and position of rock strata, and biochemical effects associated with life cycles of plants and animals, both microscopic and macroscopic. Taken together and in application with the further influence of the general circulation of all water in the hydrologic cycle, the chemical principles and environmental factors form a basis for the developing science of natural-water chemistry. Fundamental data used in the determination of water quality are obtained by the chemical analysis of water samples in the laboratory or onsite sensing of chemical properties in the field. Sampling is complicated by changes in the composition of moving water and by the effects of particulate suspended material. Some constituents are unstable and require onsite determination or sample preservation. Most of the constituents determined are reported in gravimetric units, usually milligrams per liter or milliequivalents per liter. More than 60 constituents and properties are included in water analyses frequently enough to provide a basis for consideration of the sources from which each is generally derived, the most probable forms of elements and ions in solution, solubilitycontrols, expected concentration ranges, and other chemical factors. Mechanisms that control concentrations of elements commonly present in amounts less than a few tens of micrograms per liter cannot always be easily ascertained, but present information suggests that many are controlled by solubility of their hydroxides or carbonates or by sorption on solid particles. Many dissolved organic compounds can now be specifically determined. Chemical analyses may be grouped and statistically evaluated by means, medians, frequency distributions, or ion correlations to summarize large volumes of data. Graphing of analyses or of groups of analyses aids in showing chemical relationships among water, probable sources of solutes, areal water-quality regimen, temporal and spatial variation, and water-resources evaluation. Graphs may show water type based on chemical composition, relationships among ions, or groups of ions in individual waters or many waters considered simultaneously. The relationships of water quality to hydrogeologic characteristics, such as stream discharge rate or ground-water flow patterns, can be shown by mathematical equations, graphs, and maps. About 80 water analyses selected from the literature are tabulated to illustrate the relationships described, and some of these, along with many others that are not tabulated, are also used in demonstrating graphing and mapping techniques. Relationships of water composition to source rock type are illustrated by graphs of some of the tabulated analyses. Human activities may modify water composition extensively through direct effects of pollution and indirect results of water development, such as intrusion of seawater in groundwater aquifers. Water-quality standards for domestic, agricultural, and industrial use have been published by various agencies. Irrigation project requirements for water quality are particularly intricate. Fundamental knowledge of processes that control natural-water composition is required for rational management of water quality.

Water Supply Paper↗
USGS1994

Circum-North Pacific tectonostratigraphic terrane map

The companion tectonostratigraphic terrane and overlap assemblage of map the Circum-North Pacific presents a modern description of the major geologic and tectonic units of the region. The map illustrates both the onshore terranes and overlap volcanic assemblages of the region, and the major offshore geologic features. The map is the first collaborative compilation of the geology of the region at a scale of 1:5,000,000 by geologists of the Russian Far East, Japanese, Alaskan, Canadian, and U.S.A. Pacific Northwest. The map is designed to be a source of geologic information for all scientists interested in the region, and is designed to be used for several purposes, including regional tectonic analyses, mineral resource and metallogenic analyses (Nokleberg and others, 1993, 1994a), petroleum analyses, neotectonic analyses, and analyses of seismic hazards and volcanic hazards. This text contains an introduction, tectonic definitions, acknowledgments, descriptions of postaccretion stratified rock units, descriptions and stratigraphic columns for tectonostratigraphic terranes in onshore areas, and references for the companion map (Sheets 1 to 5). This map is the result of extensive geologic mapping and associated tectonic studies in the Russian Far East, Hokkaido Island of Japan, Alaska, the Canadian Cordillera, and the U.S.A. Pacific Northwest in the last few decades. Geologic mapping suggests that most of this region can be interpreted as a collage of fault-bounded tectonostratigraphic terranes that were accreted onto continental margins around the Circum- . orth Pacific mainly during the Mesozoic and Cenozoic (Fujita and ewberry, 1983; 1987; Parfenov, 1984, 1991; Howell, 1985; Watson and Fujita, 1985; Parfenov and Natal'in, 1984; Jones and others. 1987; Monger and Berg, 1987, Fujita and Cook. 1990; Zonenshain and others. 1990; Natal'in, 1991, 1993; Moore and others, 1992; Silberling and others, 1992; Nokleberg and others. 1992, 1993, 1994a; Parfenov and others. 1993; Plaflcer and Berg, 1994; Tabor, 1994). This map is the result of extensive geologic mapping and associated tectonic studies in the Russian Far East, Hokkaido Island of Japan, Alaska, the Canadian Cordillera, and the U.S.A. Pacific Northwest in the last few decades. Geologic mapping suggests that most of this region can be interpreted as a collage of fault-bounded tectonostratigraphic terranes that were accreted onto continental margins around the Circum- . orth Pacific mainly during the Mesozoic and Cenozoic (Fujita and ewberry, 1983; 1987; Parfenov, 1984, 1991; Howell, 1985; Watson and Fujita, 1985; Parfenov and Natal'in, 1984; Jones and others. 1987; Monger and Berg, 1987, Fujita and Cook. 1990; Zonenshain and others. 1990; Natal'in, 1991, 1993; Moore and others, 1992; Silberling and others, 1992; Nokleberg and others. 1992, 1993, 1994a; Parfenov and others. 1993; Plaflcer and Berg, 1994; Tabor, 1994). On the companion map and in the descriptions bel?w· terranes are interpreted according to inferred tectonic environments. These environments are (I) cratonai; (2) passive continental margin; (3) metamorphosed continental margin; (4) continental-margin arc; (5) island arc; (6) oceanic crust, seamount, and ophiolite; (7) accretionary wedge and subduction zone: (8) turbidite basin; and (9) metamorphic for terranes that are too highly-deformed and metamorphosed to de~ermine the original tectonic environment. For terranes with complex geologic histories, the chosen color indicates the tectonic environment most prevalent during this history of the terrane. The tectonic environments inf~rred for igneous rocks are both temporal and genetic. The temporal environments are preaccretion and postaccretion. The genetic environments are subduction-related, rift-related, and collisional (anatectic)- related. In addition to terranes, the map also depicts postaccretion units that include: (I) Cenozoic and Mesozoic overlap assemblages of sedimentary and volcanic rocks that are deposited across two or more terranes that formed generally after accretion of most terranes in the region; (2) Cenozoic and Mesozoic basinal deposits that occur within a terrane or on the craton; (3) plutonic rocks. The postaccretion igneous units are identified by age-lithologic abbreviations and by name. These overlap assemblages and basinal deposits formed mainly during sedimentation and magmatism that occurred after accretion of terranes to each other or to a continental margin. Overlap assemblages provide minimum ages on the timing of accretion of terranes. Some Cenozoic and Mesozoic overlap assemblages and basinal deposits, as well as fragments of terranes, are extensively offset by movement along postaccretion faults. In addition, in onshore areas, the map depicts major preaccretion plutonic rocks that are limited to individual terranes. and in offshore areas. the map depicts major oceanic plates,-ocean floor magnetic lineations. oceanic spreading ridges, and seamounts. The map consists of five sheets. Sheets I and 2 depict, at a scale of I :5.000.000. the tectonostratigraphic terranes. preaccretion plutonic rocks, and postaccretion Cenozoic and Mesozoic overlap sedimentary, volcanic. and plutonic assemblages, and basinal deposits for the Circum- orth Pacific including the Russian Far East, northern Hokkaido Island of Japan, Alaska. the Canadian Cordillera, part of the U.S.A. Pacific Northwest. and adjacent offshore areas. Sheet 3 provides the list of map units for Sheets I and 2. Sheet 4 is a index map showing generalized onshore terranes and overlap assemblages for onshore parts of the Circum-North Pacific at a scale of I: I 0,000,000. Sheet 4 is a guide to the more complicated onshore features depicted on Sheets I and 2. Sheet 5 is an index map showing the major geographic regions for the Circum-North Pacific. Significant differences exist between the representation of onshore and offshore geology on Sheets I and 2. These are: (I) compared to the onshore part of the map, the offshore part is depicted in a more schematic fashion because of more limited data and because the offshore terranes and early Cenozoic and older overlap assemblages generally are obscured by extensive late Cenozoic sedimentary cover that is not shown unless thicker than two kilometers; (2) marginal contacts of offshore Cenozoic and Cretaceous sedimentary basins do not match contacts of onshore Cenozoic and Cretaceous sedimentary units because offshore basins are limited to those regions with sediment thicknesses greater than two kilometers; (3) stratigraphic columns, included at the end of this explanation. are provided only for onshore terranes because the geology of offshore terranes is generally less well-known; and (4) for simplicity, the major onshore Cenozoic sedimentary basins are generally not defined and described separately because the onshore part of the map is designed to emphasize terranes and overlap volcanic assemblages that are crucial for both for tectonic and metallogenic analyses published elsewhere (Nokleberg and others, 1993, 1994a). Several key geologic sources were used in the compilation of the map. For Alaska. the basic outcrop pattern for the map is from Beikman (1980), Gehrels and Berg (1992, 1994). Barker and others ( 1994). Brew (1994), and Moli-Stalcup and others ( 1994b). The distribution of terranes is from Jones and others (1987) and Monger and Berg (1987), with modification by Grantz and other (1991 ). Worall (199 1 ), okleberg and others (1993, 1994a), the cited references, and the Alaskan co-authors of this report. For the Canadian Cordillera. the basic outcrop pattern is from Monger and Berg ( 1987), Wheeler and other (1988). and Wheeler and McFeeley ( 1991) with modifications by the Canadian authors. For the northern part of the Russian Far East. the basic outcrop pattern is from So unov (1985) with modifications by the Russian authors. For the outhern part of the Russian Far East, the basic outcrop pattern is from Krasny (1991) and Bazhanov and Oleinik ( 1986) with modification by the Russian authors. The Russian Far East part of the map is the first attempt to define and delineate terranes in that region. In their compilation. the Russian authors utilized the methodology of U.S.A. and Canadian geologists. Because this map is the first attempt to display the terranes. Cenozoic and Mesozoic overlap assemblages. basinal deposit , and plutonic belts of the Russian Far East. the Russian author will appreciate constructive sugge tions for improving the map.

Open-File Report↗
USGS1994

Hydrogeology of the Chickasaw National Recreation Area, Murray County, Oklahoma

The Travertine District (Park) of the Chickasaw National Recreation Area, operated and maintained by the National Park Service, is near the City of Sulphur in south-central Oklahoma. The Park was established in 1902 because of its unique hydrologic setting, which includes Rock Creek, Travertine Creek, numerous mineralized and freshwater springs, and a dense cover of riparian vegetation. Since the turn of the century several flowing artesian wells have been drilled within and adjacent to the Park. Discharge from many of these springs and the numbers of flowing wells have declined substantially during the past 86 years. To determine the cause of these declines, a better understanding of the hydrologic system must be obtained. The U.S. Geological Survey, in cooperation with the National Park Service, has appraised hydrologic information obtained for the Park from several studies conducted during 1902-87. The principal geologic units referred to in this report are the Arbuckle Group and the overlying Simpson Group. These rocks are of Upper Cambrian to Middle Ordovician age and are composed of dolomitic limestone, with some sandstones and shales in the Simpson Group. Surface geologic maps give a general understanding of the regional subsurface geology, but information about the subsurface geology within the Park is poor. The Simpson and Arbuckle aquifers are the principal aquifers in the study area. The two aquifers are not differentiated readily in some parts of the study area because of the similarity of the Simpson and Arbuckle rocks; thus, both water-bearing units are referred to frequently as the Arbuckle-Simpson aquifer. The aquifers are confined under the Park, but are unconfined east and south of the Park. Precipitation on the outcrop area of the Arbuckle aquifer northeast and east of the Park recharges the freshwater springs (Antelope and Buffalo Springs) near the east boundary of the Park. The source of water from mineralized springs located in the central part of the Park, and flowing wells within and north of the Park, is believed to be a mix of waters from rocks of the Arbuckle and Simpson Groups. The source of water from two highly mineralized springs, Bromide and Medicine, that ceased to flow in the early 1970’s is believed to be from the Simpson Group. Water-quality characteristics reflect the sources of ground water in the study area. The highly mineralized springs near the western end of the Park are a sodium chloride type with dissolved solids greater than 4,500 mg/L. The freshwater springs near the eastern end of the Park are a calcium bicarbonate type with total dissolved solids of less than 400 mg/L. Flow from the artesian wells has declined substantially during the past 86 years and the wells are estimated to currently discharge only about 10 percent of the total flow reported in 1939. The depletion is believed to be caused by a gradual lowering of the hydraulic head within the aquifer. The influence on the hydrologic system of local municipal and industrial pumping from the Arbuckle-Simpson aquifer is difficult to discern because the system is much more sensitive to precipitation than to pumpage. Ground-water levels and spring flows in this region respond rapidly to precipitation. The effects of withdrawals from the City of Sulphur and Oklahoma Gas and Electric Company power-plant water-well fields are not discernible at wells and springs. The hydrologic system may be influenced by pumping, particularly during extended dry periods of several years, but the impact of pumping on the system cannot be determined without further investigation.

Oklahoma↗
USGS2007

Geology and Mineral Resources of the East Mojave National Scenic Area, San Bernardino County, California

From our evaluations that largely used model-based criteria, we conclude that much of the East Mojave National Scenic Area (EMNSA) contains significant indications of epigenetic mineralization of various types. Economically significant concentrations of many metals may possibly remain to be discovered in many parts of the EMNSA (see also Wetzel and others, 1992). We have discussed specific types of metallic deposits that are known to be present in the EMNSA. Some mountain ranges that have widespread occurrences are the Providence Mountains, Clark Mountain Range, Ivanpah Mountains, and New York Mountains; the area of Hackberry Mountain is included in a tract that is judged to be favorable for the discovery of epithermal, volcanic-hosted gold deposits (pl. 2). These ranges make up a broad, roughly north-south-trending region in the central part of the EMNSA. Much less endowed with known occurrences of all of the various types of deposits considered above are the Granite Mountains, the central parts of the Piute Range, the Fenner Valley area, the general area of Cima Dome, the Cima volcanic field, and areas west to Soda Lake. We have attempted to make some judgments concerning the gravel-covered areas in the EMNSA (pl. 3), including the areal extent of bedrock apparently covered only by thin veneers of gravel. But few data are available to us for the overwhelming bulk of the covered areas. The presence of any mineralization, the type of mineralization, and the extent and intensity of mineralization in the covered areas is essentially unknown. The likelihood is high, however, that those areas in the EMNSA covered only by a thin cap of gravels could host mineralization similar to that known in the adjoining mountain ranges. Most buried epigenetic-mineral deposits do not respond to standard geophysical methods, particularly at the coarse spacing of the data-collection points available for our evaluation. Restricting judgments concerning the presence of undiscovered metal resources in the EMNSA only to currently known types of deposits and to regionally representative tonnages for such deposits would undoubtedly yield small estimates for volumes of many metals that might be exploited. Metals from most newly discovered, base- and ferrous-metal deposits of the types presently known in the EMNSA probably would be insignificant from the standpoint of national needs. For example, copper from a newly discovered skarn deposit in the EMNSA would have roughly a 25 percent chance of being in excess of approximately 10,000 tonnes contained Cu, if the grade-and-tonnage distribution curves of Jones and Menzie (1986b) for copper skarns are applicable to copper skarn in the EMNSA. Most copper in the United States is produced in the Southwest from much larger open-pit operations than those associated with the typical copper skarn; the former operations exploit large-tonnage porphyry-type systems. Historically, the EMNSA has been the site of minor production of many metals from a large number of sites. Since 1985, however, a small number of sites in the EMNSA whose gold production and reserves are much greater than that of the preceding discoveries have been developed (see U.S. Bureau of Mines, 1990a). Nonetheless, widespread distribution of numerous types of deposits (including copper skarn, lead-zinc skarn, tin-tungsten skarn, polymetallic vein, gold-silver quartz-pyrite vein, low-fluorine porphyry molybdenum, gold breccia pipe, and volcanic-hosted gold) that are petrogenetically associated with igneous rock in many parts of the EMNSA is indicative of a metallogenic environment that may be the site of future discoveries of mineral-deposit types that are not now recognized by the exploration community. The science, art, and, yes, even luck of exploration procedures continually evolve, and this evolution is one of the most important aspects of currently employed methods of exploration (Bailly, 1981; Hutchinson and Grauch, 1991).

Miscellaneous Field Studies Map↗
USGS2014

Geophysical investigations of the geologic and hydrothermal framework of the Pilgrim Springs Geothermal Area, Alaska

Pilgrim Hot Springs, located on the Seward Peninsula in west-central Alaska, is characterized by hot springs, surrounding thawed regions, and elevated lake temperatures. The area is of interest because of its potential for providing renewable energy for Nome and nearby rural communities. We performed ground and airborne geophysical investigations of the Pilgrim Springs geothermal area to identify areas indicative of high heat flow and saline geothermal fluids, and to map key structures controlling hydrothermal fluid flow. Studies included ground gravity and magnetic measurements, as well as an airborne magnetic and frequency-domain electromagnetic (EM) survey. The structural and conceptual framework developed from this study provides critical information for future development of this resource and is relevant more generally to our understanding of geothermal systems in active extensional basins. Potential field data reveal the Pilgrim area displays a complex geophysical fabric reflecting a network of intersecting fault and fracture sets ranging from inherited basement structures to Tertiary faults. Resistivity models derived from the airborne EM data reveal resistivity anomalies in the upper 100 m of the subsurface that suggest elevated temperatures and the presence of saline fluids. A northwest trending fabric across the northeastern portion of the survey area parallels structures to the east that may be related to accommodation between the two major mountain ranges south (Kigluaik) and east (Bendeleben) of Pilgrim Springs. The area from the springs southward to the range front, however, is characterized by east-west trending, range-front-parallel anomalies likely caused by late Cenozoic structures associated with north-south extension that formed the basin. The area around the springs (~10 km2 ) is coincident with a circular magnetic high punctuated by several east-west trending magnetic lows, the most prominent occurring directly over the springs. These features possibly result from hydrothermal alteration imposed by fluids migrating along intra-basin faults related to recent north-south extension. The Pilgrim River valley is characterized by a NE-elongate gravity low that reveals a basin extending to depths of ~300 m beneath Pilgrim Springs and deepening to ~800 m to the southwest. The margins of the gravity low are sharply defined by northeasttrending gradients that probably reflect the edges of fault-bounded structural blocks. The southeastern edge of the low, which lies very close to the springs, also corresponds with prominent NE-striking anomalies seen in magnetic and resistivity models. Together, these features define a structure we refer to as the Northeast Fault. The location of the hot springs appears to be related to the intersection of the Northeast Fault with a N-oriented structure marked by the abrupt western edge of a resistivity low surrounding the hot springs. While the hot springs represent the primary outflow of geothermal fluids, additional outflow extends from the springs northeast along the Northeast fault to another thaw zone that we interpret to be a secondary region of concentrated upflow of geothermal fluids. The Northeast Fault apparently controls shallow geothermal fluid flow, and may also provide an important pathway conveying deep fluids to the shallow subsurface. We suggest that geothermal fluids may derive from a reservoir residing beneath the sediment basin southwest of the springs. If so, the shape of the basin, which narrows and shallows towards the springs, may funnel fluids beneath the springs where they intersect the Northeast Fault allowing them to reach the surface. An alternative pathway for reservoir fluids to reach intermediate to shallow depths may be afforded by the main Kigluaik range front fault that coincides with a resistivity anomaly possibly resulting from fluid flow and associated hydrothermal mineralization occurring within the fault zone.

Conference Paper↗
USGS1981

Availability and Quality of Water from Underground Coal Mines in Johnson and Martin Counties, Kentucky

This report provides water users with detailed information on the location, quantity, and quality of water available from underground coal mines in the Breathitt Formation of Pennsylvanian age in part of eastern Kentucky. The principal coal seams mined are the Van Lear in Johnson County and the Alma in Martin County. Coal mines that contained water were located by field inventory and coal-mine maps. The principal factors that affect the occurrence of water in coal mines are the size of the recharge area overlying the mine, the intensity and duration of precipitation, and the altitude of the mine relative to that of the nearest perennial stream. Ten above-drainage mines (that is, mines at higher elevations than that of the nearest perennial stream) are considered potential sources of water. Discharge from these mines ranged from 12 to 1,700 gallons per minute. The highest sustained discharge from a mine ranged from 750 to 1,200 gallons per minute. The water in coal mines is part of the hydrologic system and varies seasonally with precipitation. Annual discharge from most above-drainage mines ranged from 3 to 10 percent of annual precipitation on the 1and-surface area above the mine. Eight below-drainage mines are considered potential sources of water. Two were test-pumped at rates of 560 to 620 gallons per minute for as long as 6 hours. After test pumping the Warfield Mining No. 1 mine during September 1977 and March 1978, the recovery (or recharge) rates were significantly different. In September, the recharge rate was about 1,150 gallons per minute, but in March the recharge rate was 103,500 gallons per minute. This difference reflects the seasonal variations in the amount of water available to the ground-water system. Estimates of water stored in below-drainage mines ranged from 22 to 1,462 million gallons. This storage represents a safety factor sufficient to provide water through periods of limited recharge to the mine. Most mine water is of the calcium magnesium sulfate type. In general, water from below-drainage mines had lower concentrations of dissolved constituents and higher pH than water from mines above drainage. The hardness of water ranged from soft to very hard and pH ranged -from 3.1 to 8.0 units. Dissolved iron ranged from 0.01 to 64 milligrams per liter. Phenol concentrations in water from eight coal mines ranged from 0 to 5 micrograms per liter. There seems to be a significant difference in the chemical quality of water from above- and below-drainage mines. The concentration of most constituents was lower in water from below-drainage mines than it was from above-drainage mines. The better quality water from below-drainage mines may reflect (1) lower mineralization resulting from less atmospheric oxygen available to react with pyrite or, (2) the result of sampling only the upper zones of water in below-drainage mines where the water has been diluted by less mineralized surface water or inflow or recharge.

Water-Resources Investigations Report↗
USGS1987

The Alaska Mineral Resource Assessment Program: Background information to accompany folio of geologic and mineral resource maps of the Circle quadrangle, Alaska

The geology, geochemistry, geophysics, and Landsat imagery of the Circle quadrangle were investigated by an interdisciplinary research team for the purpose of assessing the mineral potential of the area. The quadrangle covers approximately 15,765 km 2 in east-central Alaska; most of it is included in the mountainous Yukon-Tanana Upland physiographic division, but the northernmost part is in the low-lying Yukon Flats section. The Circle mining district, in the east-central part of the quadrangle, has been a major producing area of placer gold since its discovery in 1893. For descriptive purposes, the Circle quadrangle is divided into three areas: the northwest Circle quadrangle, the area north of the Tintina fault zone, and the area south of the Tintina fault zone. The Tintina fault zone extends northwesterly through the northern part of the quadrangle. The northwest Circle quadrangle contains mostly folded and faulted, slightly metamorphosed sedimentary rocks that are intruded by Tertiary granitic plutons. In the northern part of the area north of the Tintina fault zone (Little Crazy Mountains and northern east Crazy Mountains), the rocks consist primarily of the gabbro and basalt of the Circle Volcanics and minor associated chert, graywacke, and limestone. Elsewhere in this area (south of the Circle Volcanics and in the western Crazy Mountains), the rocks are mostly slightly metamorphosed Paleozoic sedimentary rocks that have been folded and faulted. Rocks in the largest part of the quadrangle, the area south of the Tintina fault zone, consist largely of pelitic rocks that are regionally metamorphosed to greenschist and amphibolite facies. Felsic plutons, mostly Tertiary in age, occur throughout the area. The metamorphic rocks are separated from sedimentary rocks on the northwest by thrust faulting. The aeromagnetic and gravity data show clear differences between the areas north and south of the Tintina fault zone. The metamorphic terrane to the south has low overall gravity and local gravity lows over exposed granitic plutons. It is hypothesized that magnetic chlorite schist infolded with nonmagnetic quartzite and schist account for east-northeast-trending magnetic highs that approximately parallel the regional strike of the most prominent foliation in the metamorphic rocks. North of the Tintina fault zone, the Circle Volcanics are characterized by high gravity and east-west-trending magnetic highs. The Tintina fault zone has an intense magnetic high near the western margin of the Circle quadrangle overlying the magnetic granodiorite of the Victoria Mountain pluton. A magnetic high near Circle Hot Springs is less intense, but broader, and could reflect a buried magnetic pluton similar to that of the Victoria Mountain pluton. Computer-enhanced Landsat images of the Circle quadrangle show trends and patterns of concentrations of linear features. Features trending northeast-southwest predominate throughout the quadrangle; northwest-southeast-trending linear features are found mostly south of the Tintina fault zone. High concentrations of linear features were not found to correspond to areas of known mineralization in any consistent or significant way that could presently be used in locating areas of mineralization. Geochemical and mineralogical studies of stream sediment and heavy-mineral concentrates from the Circle quadrangle identify areas of anomalous concentrations of metallic elements, including gold, silver, tin, tungsten, lead, antimony, zinc, thorium, uranium, and beryllium. The data delineate areas of known mineral occurrences and areas that may contain undiscovered mineral resources. To date, placer gold has been the only significant metallic mineral resource from the Circle quadrangle, but the general geologic setting, especially the presence of post-orogenic plutons, is similar to that of regions that contain tin greisen deposits, tungsten skarn deposits, lode gold deposits in metasedimentary rocks, and uranium vein deposits. Six areas or tracts were identified in which such deposits might occur, and two more tracts were delineated as possible for the occurrence of shale-hosted Lead-zinc deposits. The discovery of two diamonds in the gravels of Cooked Creek point to the slight possibility of finding placer or lode diamond deposits. Although most of the past and present gold mining has taken place in four areas in the quadrangle, a sedimentary basin near the town of Central was identified as possibly containing buried placer gold deposits or sedimentary uranium deposits.

Alaska↗
USGS1996

Geochemical and isotopic composition of ground water, with emphasis on sources of sulfate, in the upper Floridan aquifer and intermediate aquifer system in southwest Florida

In southwest Florida, sulfate concentrations in water from the Upper Floridan aquifer and overlying intermediate aquifer system are commonly above 250 milligrams per liter (the drinking water standard), particularly in coastal areas. Possible sources of sulfate include dissolution of gypsum from the deeper part of the Upper Floridan aquifer or the middle confining unit, saltwater in the aquifer, and saline waters from the middle confining unit and Lower Floridan aquifer. The sources of sulfate and geochemical processes controlling ground-water composition were evaluated for the Peace and Myakka River Basins and adjacent coastal areas of southwest Florida. Samples were collected from 63 wells and a saline spring, including wells finished at different depth intervals of the Upper Floridan aquifer and intermediate aquifer system at about 25 locations. Sampling focused along three ground-water flow paths (selected based on a predevelopment potentiometric-surface map). Ground water was analyzed for major ions, selected trace constituents, dissolved organic carbon, and stable isotopes (delta deuterium, oxygen-18, carbon-13 of inorganic carbon, and sulfur-34 of sulfate and sulfide); the ratio of strontium-87 to strontium-86 was analyzed for waters along one of the flow paths. Chemical and isotopic data indicate that dedolomitization reactions (gypsum and dolomite dissolution and calcite precipitation) control the chemical composition of water in the Upper Floridan aquifer in inland areas. This is confirmed by mass-balance modeling between wells in the shallowest interval in the aquifer along the flow paths. However, gypsum occurs deeper in the aquifer than these wells. Upwelling of sulfate-rich water that previously dissolved gypsum in deeper parts of the aquifer is a more likely source of sulfate than gypsum dissolution in shallow parts of the aquifer. This deep ground water moves to shallower zones in the aquifer discharge area. Saltwater from the Upper Floridan aquifer has not dissolved significant amounts of gypsum compared to fresher water in the aquifer. This is consistent with a shallow seawater source for the saltwater, rather than a deeper source from the underlying middle confining unit or Lower Floridan aquifer, which would have elevated sulfate concentrations. Ion exchange and dolomitization may be important reactions for saltwater in the aquifer. According to geochemical modeling, the freshwater end member for water in the saltwater mixing zone in the southwestern part of the study area is not upgradient water from the Upper Floridan aquifer that dissolved gypsum. Instead, this water appears to be isolated from the regional freshwater flow system and may be part of a more localized flow system. The chemical and isotopic composition of water in the intermediate aquifer system is controlled by differences in extent of reactions with aquifer minerals, upward leakage from the Upper Floridan aquifer, and saltwater mixing. In inland areas, water generally is characterized by relatively low sulfate concentrations (less than 250 milligrams per liter) and differences in extent of carbonate mineral dissolution. Some inland waters have elevated chloride concentrations, which may be related to evaporation prior to recharge. In coastal Sarasota County and in isolated inland areas, water from the intermediate aquifer system has high sulfate concentrations characteristic of dedolomitization waters from the Upper Floridan aquifer. The chemical and isotopic composition of these waters is controlled by upward leakage from the Upper Floridan aquifer, which naturally occurs in the discharge area but may be locally enhanced by pumping or interconnection of wells open to both aquifer systems. In western Charlotte County, the waters are dominated by sodium and chloride, and their compositions are consistent with mixing between saltwater and inland intermediate aquifer system water that has not been influenced by discharge from the

Florida↗