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332 records · Page 19Linked to original sources
USGS2012

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dusar-Shaida mineral district in Afghanistan: Chapter I 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 Dusar-Shaida mineral district, which has copper and tin 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), 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’ 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’ local zone (41 for Dusar-Shaida) 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 Dusar-Shaida 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 Dusar-Shaida study area, three subareas were designated for detailed field investigations (that is, the Dahana-Misgaran, Kaftar VMS, and Shaida subareas); these subareas were extracted from the area’ image mosaic and are provided as separate embedded geotiff images.

Farah;Herat↗
USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghunday-Achin mineral district in Afghanistan, in Davis, P.A, compiler, 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 Ghunday-Achin mineral district, which has magnesite and talc 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. 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 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 Ghunday-Achin) and the WGS84 datum. The final image mosaics were subdivided into six overlapping tiles or quadrants because of the large size of the target area. The six image tiles (or quadrants) for the Ghunday-Achin 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 Ghunday-Achin study area, two subareas were designated for detailed field investigations (that is, the Achin-Magnesite and Ghunday-Mamahel subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.

Data Series↗
USGS2012

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kharnak-Kanjar mineral district in Afghanistan: Chapter K 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 Kharnak-Kanjar mineral district, which has mercury 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. 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 Kharnak-Kanjar) 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 Kharnak-Kanjar 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 Kharnak-Kanjar study area, three subareas were designated for detailed field investigations (that is, the Koh-e-Katif Passaband, Panjshah-Mullayan, and Sahebdad-Khanjar subareas); these subareas were extracted from the area's image mosaic and are provided as separate embedded geotiff images.

Farah;Ghor;Daykundi↗
USGS2012

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Haji-Gak mineral district in Afghanistan: Chapter C 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 Haji-Gak mineral district, which has iron ore 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,2006,2007), 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 co-registered 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 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 Haji-Gak) and the WGS84 datum. The final image mosaics were subdivided into three overlapping tiles or quadrants because of the large size of the target area. The three image tiles (or quadrants) for the Haji-Gak 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 Haji-Gak study area, three subareas were designated for detailed field investigations (that is, the Haji-Gak Prospect, Farenjal, and NE Haji-Gak subareas); these subareas were extracted from the area's image mosaic and are provided as separate embedded geotiff images.

Bamyan;Parwan;Wardak↗
USGS2013

Lithofacies, age, depositional setting, and geochemistry of the Otuk Formation in the Red Dog District, northwestern Alaska

Complete penetration of the Otuk Formation in a continuous drill core (diamond-drill hole, DDH 927) from the Red Dog District illuminates the facies, age, depositional environment, source rock potential, and isotope stratigraphy of this unit in northwestern Alaska. The section, in the Wolverine Creek plate of the Endicott Mountains Allochthon (EMA), is ~82 meters (m) thick and appears structurally uncomplicated. Bedding dips are generally low and thicknesses recorded are close to true thicknesses. Preliminary synthesis of sedimentologic, paleontologic, and isotopic data suggests that the Otuk succession in DDH 927 is a largely complete, albeit condensed, marine Triassic section in conformable contact with marine Permian and Jurassic strata. The Otuk Formation in DDH 927 gradationally overlies gray siliceous mudstone of the Siksikpuk Formation (Permian, based on regional correlations) and underlies black organic-rich mudstone of the Kingak(?) Shale (Jurassic?, based on regional correlations). The informal shale, chert, and limestone members of the Otuk are recognized in DDH 927, but the Jurassic Blankenship Member is absent. The lower (shale) member consists of 28 m of black to light gray, silty shale with as much as 6.9 weight percent total organic carbon (TOC). Thin limy layers near the base of this member contain bivalve fragments (Claraia sp.?) consistent with an Early Triassic (Griesbachian-early Smithian) age. Gray radiolarian chert dominates the middle member (25 m thick) and yields radiolarians of Middle Triassic (Anisian and Ladinian) and Late Triassic (Carnian-late middle Norian) ages. Black to light gray silty shale, like that in the lower member, forms interbeds that range from a few millimeters to 7 centimeters in thickness through much of the middle member. A distinctive, 2.4-m-thick interval of black shale and calcareous radiolarite ~17 m above the base of the member has as much as 9.8 weight percent TOC, and a 1.9-m-thick interval of limy to cherty mudstone immediately above this contains radiolarians, foraminifers, conodonts, and halobiid bivalve fragments. The upper (limestone) member (29 m thick) is lime mudstone with monotid bivalves and late Norian radiolarians, overlain by gray chert that contains Rhaetian (latest Triassic) radiolarians; Rhaetian strata have not previously been documented in the Otuk. Rare gray to black shale interbeds in the upper member have as much as 3.4 weight percent TOC. At least 35 m of black mudstone overlies the limestone member; these strata lack interbeds of oil shale and chert that are characteristic of the Blankenship, and instead they resemble the Kingak Shale. Vitrinite reflectance values (2.45 and 2.47 percent Ro) from two samples of black shale in the chert member indicate that these rocks reached a high level of thermal maturity within the dry gas window. Regional correlations indicate that lithofacies in the Otuk Formation vary with both structural and geographic position. For example, the shale member of the Otuk in the Wolverine Creek plate includes more limy layers and less barite (as blades, nodules, and lenses) than equivalent strata in the structurally higher Red Dog plate of the EMA, but it has fewer limy layers than the shale member in the EMA ~450 kilometers (km) to the east at Tiglukpuk Creek. The limestone member of the Otuk is thicker in the Wolverine Creek plate than in the Red Dog plate and differs from this member in EMA sections to the east in containing an upper cherty interval that lacks monotids; a similar interval is seen at the top of the Otuk Formation ~125 km to the west (Lisburne Peninsula). Our observations are consistent with the interpretations of previous researchers that Otuk facies become more distal in higher structural positions and that within a given structural level more distal facies occur to the west. Recent paleogeographic reconstructions indicate that the Otuk accumulated at a relatively high paleolatitude with a bivalve fauna typical of the Boreal realm. A suite of δ 13 C org (carbon isotopic composition of carbon) data (n=38) from the upper Siksikpuk Formation through the Otuk Formation and into the Kingak(?) Shale in DDH 927 shows a pattern of positive and negative excursions similar to those reported elsewhere in Triassic strata. In particular, a distinct negative excursion at the base of the Otuk (from ‒23.8 to ‒31.3‰ (permil, or parts per thousand)) likely correlates with a pronounced excursion that marks the Permian-Triassic boundary at many localities worldwide. Another feature of the Otuk δ 13 C org record that may correlate globally is a series of negative and positive excursions in the lower member. At the top of the Otuk in DDH 927, the δ 13 C org values are extremely low and may correlate with a negative excursion that is widely observed at the Triassic-Jurassic boundary.

Alaska↗
USGS1996

Geomorphology of the lower Copper River, Alaska

The Copper River, located in southcentral Alaska, drains an area of more than 24,000 square miles. About 30 miles above its mouth, this large river enters Miles Lake, a proglacial lake formed by the retreat of Miles Glacier. Downstream from the outlet of Miles Lake, the Copper River flows past the face of Childs Glacier before it enters a large, broad, alluvial flood plain. The Copper River Highway traverses this flood plain and in 1996, 11 bridges were located along this section of the highway. These bridges cross parts or all of the Copper River and in recent years, some of these bridges have sustained serious damage due to the changing course of the Copper River. Although the annual mean discharge of the lower Copper River is 57,400 cubic feet per second, most of the flow occurs during the summer months from snowmelt, rainfall, and glacial melt. Approximately every six years, an outburst flood from Van Cleve Lake, a glacier-dammed lake formed by Miles Glacier, releases approximately 1 million acre-feet of water into the Copper River. At the peak outflow rate from Van Cleve Lake, the flow of the Copper River will increase an additional 140,000 and 190,000 cubic feet per second. Bedload sampling and continuous seismic reflection were used to show that Miles Lake traps virtually all the bedload being transported by the Copper River as it enters the lake from the north. The reservoir-like effect of Miles Lake results in the armoring of the channel of the Copper River downstream from Miles Lakes, past Childs Glacier, until it reaches the alluvial flood plain. At this point, bedload transport begins again. The lower Copper River transports 69 million tons per year of suspended sediment, approximately the same quantity as the Yukon River, which drains an area of more than 300,000 square miles. By correlating concurrent flows from a long-term streamflow- gaging station on the Copper River with a short-term streamflow-gaging station at the outlet of Miles Lake, long-term flow characteristics of the lower Copper River were synthesized. Historical discharge and cross-section data indicate that as late as 1970, most of the flow of the lower Copper River was through the first three bridges of the Copper River Highway as it begins to traverse the alluvial flood plain. In the mid 1980's, a percentage of the flow had shifted away from these three bridges and in 1995, only 51 percent of the flow of the Copper River passed through them. Eight different years of aerial photography of the lower Copper River were analyzed using Geographical Information System techniques. This analysis indicated that no major channel changes were caused by the 1964 earthquake. A flood in 1981 that had a recurrence interval of more than 100 years caused significant channel changes in the lower Copper River. A probability analysis of the lower Copper River indicated stable areas and the long-term locations of channels. By knowing the number of times a particular area has been occupied by water and the last year an area was occupied by water, areas of instability can be located. A Markov analysis of the lower Copper River indicated that the tendency of the flood plain is to remain in its current state. Large floods of the magnitude of the 1981 event are believed to be the cause of major changes in the lower Copper River.

Open-File Report↗
USGS1997

Geomorphology of the lower Copper River, Alaska

The Copper River, located in southcentral Alaska, drains an area of more than 24,000 square miles. About 30 miles above its mouth, this large river enters Miles Lake, a proglacial lake formed by the retreat of Miles Glacier. Downstream from the outlet of Miles Lake, the Copper River flows past the face of Childs Glacier before it enters a large, broad, alluvial flood plain. The Copper River Highway traverses this flood plain and in 1995, 11 bridges were located along this section of the highway. These bridges cross parts of the Copper River and in recent years, some of these bridges have sustained serious damage due to the changing course of the Copper River. Although the annual mean discharge of the lower Copper River is 57,400 cubic feet per second, most of the flow occurs during the summer months from snowmelt, rainfall, and glacial melt. Approximately every six years, an outburst flood from Van Cleve Lake, a glacier-dammed lake formed by Miles Glacier, releases approximately 1 million acre-feet of water into the Copper River. When the outflow rate from Van Cleve Lake reaches it peak, the flow of the Copper River will increase between 150,000 to 190,000 cubic feet per second. Data collected by bedload sampling and continuous seismic reflection indicated that Miles Lake traps virtually all the bedload being transported by the Copper River as it enters the lake from the north. The reservoir-like effect of Miles Lake results in the armoring of the channel of the Copper River downstream from Miles Lake, past Childs Glacier, until it reaches the alluvial flood plain. At this point, bedload transport begins again. The lower Copper River transports 69 million tons per year of suspended sediment, approximately the same quantity as the Yukon River, which drains an area of more than 300,000 square miles. By correlating concurrent flows from a long-term streamflow-gaging station on the Copper River with a short-term streamflow-gaging station at the outlet of Miles Lake, long-term flow characteristics of the lower Copper River were synthesized. Historical discharge and cross-section data indicate that as late as 1970, most of the flow of the lower Copper River was through the first three bridges of the Copper River Highway as it begins to traverse the alluvial flood plain. In the mid 1980's, a percentage of the flow had shifted away from these three bridges and in 1995, only 51 percent of the flow of the Copper River passed through them. Eight different years of aerial photography of the lower Copper River were analyzed using Geographical Information System techniques. This analysis indicated that no major channel changes were caused by the 1964 earthquake. However, a flood in 1981 that had a recurrence interval of more than 100 years caused significant channel changes in the lower Copper River. A probability analysis of the lower Copper River indicated stable areas and the long-term locations of channels. By knowing the number of times a particular area has been occupied by water and the last year an area was occupied by water, areas of instability can be located. A Markov analysis of the lower Copper River indicated that the tendency of the flood plain is to remain in its current state. Large floods of the magnitude of the 1981 event are believed to be the cause of major changes in the lower Copper River.

Professional Paper↗
USGS2003

Sea otter studies in Glacier Bay National Park and Preserve: annual report 2002

Since 1995, the number of sea otters in Glacier Bay proper has increased from around 5 to more than 1200. Sea otter distribution is mostly limited to the Lower Bay, south of Sandy Cove, and is not continuous within that area. Concentrations occur in the vicinity of Sita Reef and Boulder Island and between Pt. Carolus and Rush Pt. on the west side of the Bay, although there have been occasional sightings north of Sandy Cove (Figure 1). Large portions of the Bay remain unoccupied by sea otters, but recolonization is occurring rapidly. Most prey recovered by sea otters in Glacier Bay are ecologically, commercially, or socially important species. In 2002 sea otter diet consisted of 35% clam, 26% mussel, 3% crab, 3.0% snail, 2% starfish, 11% urchins, 2% other, and 20% unidentified. Dominant clam species include the butter clam, Saxidomus gigantea , the Greenland cockle, Serripes groenlandicus , and the littleneck clam, Protothaca staminea . Urchins are primarily green urchins, Strongylocentrotus droebachiensis , and the mussel is Modiolus modiolus . Crabs observed in 2002 include the Dungeness, Cancer magister , the kelp crab Pugettia gracilis , and the helmet crab, Telmessus cherigonus . Although we characterize diet at broad geographic scales, we have previously found diet to vary between sites separated by as little as several hundred meters. Dietary variation among and within sites can reflect differences in prey availability as well as individual specialization. We estimated species composition, density, biomass, and sizes of subtidal clams, urchins, and mussels at 13 sites in Glacier Bay and 5 sites in nearby Port Althorp, where sea otters have been present for at least 20 years. All sites were selected based on the presence of abundant clam siphons and the absence of sea otters (Glacier Bay) or abundant shell litter and the presence of sea otters (Port Althorp). Glacier Bay sites were selected to achieve a broad geographic sample of dense subtidal clam beds within Glacier Bay prior to occupation and foraging by sea otters. Port Althorp sites were chosen to achieve a representative sample of subtidal clam beds already under prolonged foraging pressure by sea otters. There was no direct evidence of otter foraging at any of our Glacier Bay sampling sites. In Glacier Bay, we sampled 15,338 bivalves (average of 1,180/site) representing 14 species of clam, 2 species of mussel, and a single scallop and we sampled 6,917 urchins (average of 513/site). In Port Althorp, we sampled 1,034 bivalves (average of 207/site) representing 14 species of clam. We found only 5 urchins, all S. droebachiensis . Mean densities and biomass of all subtidal clams were significantly greater in Glacier Bay (59.2 and 99/0.25m 2 compared to Port Althorp (10.3 and 5.8/0.25m 2 (p<0.002 for both). Our contrasts of subtidal clam populations between Glacier Bay and Port Althorp suggest that clam densities will likely decline by about a factor of six and that clam biomass estimates will decline by more than a factor of ten. Numerically dominant species of clams, P. staminea , S. gigantea , Macoma sp. and Mya sp. were all significantly greater in density and biomass in Glacier Bay, while C. nutalli density was low but significantly higher in Port Althorp. Subtidal clam species diversity was significantly greater in Port Althorp compared to Glacier Bay, although this may simply reflect habitat differences. Sea urchin densities were high in Glacier Bay, while in Port Althorp urchins were virtually absent. Sea otters are now well established in limited areas of the lower portions of Glacier Bay. It is likely that distribution and numbers of sea otters will continue to increase in Glacier Bay in the near future. Glacier Bay supports large and diverse populations of clams that are largely unexploited by sea otters at present. It is predictable that the density and sizes of clam populations will decline in response to otter predation. This will result in fewer opportunities for human harvest, but will also trigger ecosystem level changes, as prey for other predators, such as octopus, sea stars, fishes, birds and mammals are modified. Sea otters will also modify benthic habitats through excavation of sediments required to extract burrowing infauna such as clams. Effects of sediment disturbance by foraging sea otters are not understood. Glacier Bay also supports large populations of other preferred sea otter prey, such as king ( Paralithodes sp. ), tanner ( Chionoecetes sp. ) and dungeness ( Cancer magister ) crabs and green sea urchins ( S. droebachiensis ). As the colonization of Park waters by sea otters continues, it is also likely that dramatic changes will occur in the species composition, abundance, and size class distribution of many components of the nearshore marine ecosystem. Many of the changes will occur as a direct result of predation by sea otters. Others will result from indirect or cascading effects of sea otter foraging, such as increased kelp production and modified prey availability for other nearshore predators. Without recognizing and quantifying the extent of change initiated by the colonization of Glacier Bay by sea otters, management of nearshore resources will be severely constrained for many decades.

Alaska↗