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Minerals & deposits

Find USGS publications on mineral resources and deposits. Search commodities and geographic names, then check source reports for geology and assessment methods.

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At least 217 records · Page 12Linked to original sources

USGS1978

Summary of references to mineral occurrences (other than mineral fuels and construction materials) in the Bradfield Canal Quadrangle, Alaska

These summaries of references are designed to aid in library research on metallic and nonmetallic (other than mineral fuels and construction materials) mineral occurrences in the Bradfield Canal quadrangle, Alaska. All references to reports of the Geological Survey and to most reports of the U.S. Bureau of Mines, and to most reports of the State of Alaska Division of Geological and Geophysical Surveys and its predecessor State and Territorial agencies released before July 1, 1978, are summarized. Certain, mainly statistical, reports such as the annual Minerals Yearbook of the U.S. Bureau of Mines and most biennial and annual reports of the State of Alaska Division of Geological and Geophysical Surveys and its predecessor State and Territorial agencies are not included. This report is divided into three parts: a section made up of summaries of references arranged alphabetically first by occurrence name; a section that lists synonyms for names in the first section, claim names, and the names of operators and owners of mines and prospects; and a section that lists, by author, all references summarized in the first section.

Alaska↗

USGS1978

Summary of references to mineral occurrences (other than mineral fuels and construction materials) in the Nome Quadrangle, Alaska

These summaries of references are designed to aid in library research on metallic and nonmetallic (other than mineral fuels and construction materials) mineral occurrences in the Nome quadrangle, Alaska. All references to reports of the Geological Survey, to most reports of the U.S. Bureau of Mines, and to most reports of the State of Alaska Division of Geological and Geophysical Surveys and its predecessor State and Territorial agencies released before July 1, 1977, are summarized. Certain, mainly statistical, reports such as the annual Minerals Yearbook of the U.S. Bureau of Mines and the biennial and annual reports of the State of Alaska Division of Geological and Geophysical Surveys and its predecessor State and Territorial agencies are not included. This report is divided into three parts: a section made up of summaries of references arranged alphabetically by occurrence name; a section that lists synonyms for names in the first section, claim names, and the names of operators and owners of mines and prospects; and a section that lists, by author, all references summarized in the first section.

Alaska↗

USGS1978

Summary of references to mineral occurrences (other than mineral fuels and construction materials) in the Beaver, Bettles, and Medfra quadrangles, Alaska

These summaries of references are designed to aid in library research on metallic and nonmetallic (other than mineral fuels and construction materials) mineral occurrences in the Beaver, Bettles, and Medfra quadrangles, Alaska. All references to reports of the Geological Survey, to most reports of the U.S. Bureau of Mines, and to most reports of the State of Alaska Division of Geological and Geophysical Surveys and its predecessor State and Territorial agencies released before July 1, 1977, are summarized. Certain, mainly statistical, reports such as the annual Minerals Yearbook of the U.S. Bureau of Mines and the biennial and annual reports of the State of Alaska Division of Geological and Geophysical Surveys and its predecessor State and Territorial agencies are not included. This report is divided into three parts: a section made up of summaries of references arranged alphabetically first by quadrangle and second by occurrence name; a section that lists synonyms for names in the first section, claim names, and the names of operators and owners of mines and prospects; and a section that lists, by author, all references summarized in the first section.

Alaska↗

USGS1979

Summary of references to mineral occurrences (other than mineral fuels and construction materials) in the Mount Hayes Quadrangle, Alaska

These summaries of references are designed to aid in library research on metallic and nonmetallic (other than mineral fuels and construction materials) mineral occurrences in the Mount Hayes quadrangle, Alaska. References to most reports of the Geological Survey, the U.S. Bureau of Mines, and the State of Alaska Division of Geological and Geophysical Surveys and its predecessor State and Territorial agencies released before September 1, 1978, are summarized. Certain, mainly statistical, reports such as the annual Minerals Yearbook of the U.S. Bureau of Mines and most biennial and annual reports of the State of Alaska Division of Geological and Geophysical Surveys and its predecessor State and Territorial agencies are not included.

Alaska↗

USGS2012

Economic filters for evaluating porphyry copper deposit resource assessments using grade-tonnage deposit models, with examples from the U.S. Geological Survey global mineral resource assessment: Chapter H in Global mineral resource assessment

An analysis of the amount and location of undiscovered mineral resources that are likely to be economically recoverable is important for assessing the long-term adequacy and availability of mineral supplies. This requires an economic evaluation of estimates of undiscovered resources generated by traditional resource assessments (Singer and Menzie, 2010). In this study, simplified engineering cost models were used to estimate the economic fraction of resources contained in undiscovered porphyry copper deposits, predicted in a global assessment of copper resources. The cost models of Camm (1991) were updated with a cost index to reflect increases in mining and milling costs since 1989. The updated cost models were used to perform an economic analysis of undiscovered resources estimated in porphyry copper deposits in six tracts located in North America. The assessment estimated undiscovered porphyry copper deposits within 1 kilometer of the land surface in three depth intervals. The results of the updated engineering cost model analysis for open-pit porphyry copper deposits are in agreement with the grade-tonnage boundary defining positive economic returns for copper deposits developed between 1989 and 2008. This correspondence demonstrates that the updated engineering cost equations are performing well and appear to be appropriate to evaluate the economic status of open-pit porphyry copper mines under current, and potentially future, economic conditions. Economic filters based on these simplified engineering cost models provide a method for estimating potential tonnages of undiscovered metals that may be economic in individual assessment areas. One implication of the economic filter results for undiscovered copper resources is that global copper supply will continue to be dominated by production from a small number of giant deposits. This domination of resource supply by a small number of producers may increase in the future, because an increasing proportion of new deposit discoveries are likely to occur in remote areas and be concealed deep beneath covering rock and sediments. Extensive mineral exploration activity will be required to meet future resource demand, because these deposits will be harder to find and more costly to mine than near-surface deposits located in more accessible areas. Relatively few of the new deposit discoveries in these high-cost settings will have sufficient tonnage and grade characteristics to assure positive economic returns on development and exploration costs.

Scientific Investigations Report↗

USGS2012

Assessment of the geoavailability of trace elements from minerals in mine wastes: analytical techniques and assessment of selected copper minerals

In this study, four randomly selected copper-bearing minerals were examined—azurite, malachite, bornite, and chalcopyrite. The objectives were to examine and enumerate the crystalline and chemical properties of each of the minerals, to determine which, if any, of the Cu-bearing minerals might adversely affect systems biota, and to provide a multi-procedure reference. Laboratory work included use of computational software for quantifying crystalline and amorphous material and optical and electron imaging instruments to model and project crystalline structures. Chemical weathering, human fluid, and enzyme simulation studies were also conducted. The analyses were conducted systematically: X-ray diffraction and microanalytical studies followed by a series of chemical, bio-leaching, and toxicity experiments.

Scientific Investigations Report↗

USGS2024

Near-infrared reflectance spectra of mixtures of kaolin-group minerals: Use in clay mineral studies

Near-infrared (NIR) reflectance spectra for mixtures of ordered kaolinite and ordered dickite have been found to simulate the spectral response of disordered kaolinite. The amount of octahedral vacancy disorder in nine disordered kaolinite samples was estimated by comparing the sample spectra to the spectra of reference mixtures. The resulting estimates are consistent with previously published estimates of vacancy disorder for similar kaolin minerals that were modeled from calculated X-ray diffraction patterns. The ordered kaolinite and dickite samples used in the reference mixtures were carefully selected to avoid undesirable particle size effects that could bias the spectral results. NIR spectra were also recorded for laboratory mixtures of ordered kaolinite and halloysite to assess whether the spectra could be potentially useful for determining mineral proportions in natural physical mixtures of these two clays. Although the kaolinite-halloysite proportions could only be roughly estimated from the mixture spectra, the halloysite component was evident even when halloysite was present in only minor amounts. A similar approach using NIR spectra for laboratory mixtures may have applications in other studies of natural clay mixtures.

Clays and Clay Minerals↗

USGS1988

Geology and mineral resources of the Port Moller region, western Alaska Peninsula, Aleutian arc: A section in USGS research on mineral resources - 1989: Program and abstracts

Geologic mapping of the Port Moller, Stepovak Bay, and Simeonof Island quadrangles was begun under the auspices of the Alaska Mineral Resource Assessment Program (AMRAP) in 1983 . Two important mineral deposits are located in the Port Moller quadrangle; the Pyramid prospect is the largest copper porphyry system in the Aleutian Arc, and the Apollo Mine is the only gold mine to reach production status in the Aleutian Arc.

Alaska↗

USGS1985

Processing of Landsat imagery to map surface mineral alteration on the Alaska Peninsula: A section in USGS research on mineral resources, 1985 program and abstracts

Landsat images were digitally processed to facilitate assessment of the mineral resources of the Port Moller, Stepovak Bay, and Simeonof Island 1:250,000 quadrangles. Field mapping and assessment of these quadrangles were begun in 1983 as part of the Alaska Mineral Resource Assessment Program (AMRAP). It was quickly realized that time and budget constraints would limit mapping coverage. Therefore, at the suggestion of Roger Ashley, we used existing Landsat multispectral scanner imagery to aid in locating surface alteration, which could be field checked or related to stream-sediment or hand-sample geochemical data.

Circular↗

USGS1976

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

The Tanacross quadrangle, consisting of 17,400 km 2 (6,700 mi 2) in east-central Alaska, was investigated by an interdisciplinary research team for the purpose of assessing the mineral resource potential of the quadrangle. This report provides the background information for a folio of maps on the geology, geophysics, reconnaissance geochemistry, Landsat imagery, and mineral resource evaluation of the quadrangle. Revisions to the previously published geologic map of the Tanacross quadrangle, 18 new potassium-argon ages, and a comprehensive bibliography are also included.

Alaska↗

USGS1983

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

The Ambler River quadrangle, consisting of 14,290 km2 (5,520 mi2) in northwest Alaska, was investigated by an interdisciplinary research team for the purpose of assessing the mineral resource potential of the quadrangle. This report provides background information for a folio of maps on the geology, reconnaissance geochemistry, aeromagnetics, Landsat imagery, and mineral resource evaluation of the quadrangle. A summary of the geologic history, radiometric dates, and fossil localities and a comprehensive bibliography are also included. The quadrangle contains jade reserves, now being mined, and potentially significant resources of copper, zinc, lead, and silver.

Alaska↗

USGS1981

The Conterminous United States Mineral Appraisal Program; background information to accompany folio of geologic, geochemical, geophysical, and mineral resource maps of the Choteau 1 degree x 2 degrees Quadrangle, Montana

The Choteau l? x 2? quadrangle in northwest Montana was studied by an interdisciplinary research team in order to appraise its mineral resource and hydrocarbon potential The appraisal is based on field and laboratory investigations of the geology, geochemistry, and geophysics. The results of the investigations are published as a folio of maps, figures, tables, and accompanying discussions. This circular provides background information on the investigations and integrates the published components of the resource appraisal. A comprehensive bibliography cites both specific and general references to the geology, geochemistry, geophysics, and mineral deposits of the Choteau l? x 2? quadrangle.

Circular↗

USGS1984

The Conterminous United States Mineral Appraisal Program; background information to accompany folio of geologic, geochemical, geophysical, and mineral resources maps of the Walker Lake 1 degree x 2 degrees Quadrangle, California and Nevada

The Walker Lake 1? by 2? quadrangle in eastern California and western Nevada was studied by an interdisciplinary research team to appraise its mineral resources. The appraisal is based on geological, geochemical, and geophysical field and laboratory investigations, the results of which are published as a folio of maps, figures, and tables, with accompanying discussions. This circular provides background information on the investigations and integrates the information presented in the folio. The selected bibliography lists selected references to the geology, geochemistry, geophysics, and mineral deposits of the Walker Lake 1? by 2? quadrangle.

Circular↗

USGS1986

The Conterminous United States Mineral Appraisal Program; background information to accompany folio of geologic, geochemical, geophysical, and mineral resources maps of the Medford 1 degree x 2 degrees Quadrangle, Oregon and California

The Medford 1 ? by 2 ? quadrangle in southern Oregon and northern California was studied by an interdisciplinary research team to appraise its mineral resources. The appraisal is based on geological, geochemical, and geophysical field and laboratory investigations, the results of which are published as a folio of maps, figures, and tables, with accompanying discussions. This circular provides background information on the investigations and integrates the information presented in the folio. The bibliography lists selected references to the geology, geochemistry, geophysics, and mineral deposits of the Medford 1 ? by 2 ? quadrangle.

Circular↗

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↗

USGS2012

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Balkhab mineral district in Afghanistan: Chapter B 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 Balkhab mineral district, which has copper 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), 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 Balkhab) 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 Balkhab 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 Balkhab study area, one subarea was designated for detailed field investigations (that is, the Balkhab Prospect subarea); this subarea was extracted from the area's image mosaic and is provided as separate embedded geotiff images.

Balkh;Samangan;Sari-Pul↗

USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Herat mineral district in Afghanistan: Chapter T 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 Herat mineral district, which has barium and limestone 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,2007,2008,2009), 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. For this particular area, PRISM image orthorectification 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). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was 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 1,000-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 Herat) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the Herat 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 Herat study area, one subarea was designated for detailed field investigations (that is, the Barium-Limestone subarea); this subarea was extracted from the area's image mosaic and is provided as separate embedded geotiff images.

Herat↗

USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Uruzgan mineral district in Afghanistan: Chapter V 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 Uruzgan mineral district, which has tin and tungsten 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, 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 Uruzgan) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the Uruzgan 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.

Data Series↗