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At least 1,711 records · Page 95Linked to original sources
USGS2004

Seismic history of the Middle America subduction zone along El Salvador, Guatemala, and Chiapas, Mexico: 1526–2000

We present a catalog of subduction zone earthquakes along the Pacific coast from central El Salvador to eastern Chiapas, Mexico, from 1526 to 2000. We estimate that the catalog is complete since 1690 for M S ≥7.4 thrust events and M ≥ 7.4 normal-faulting events within the upper 60 km of the down-going slab. New intensity maps were constructed for the 27 earthquakes since 1690, using mostly primary data sources. By calibrating with recent events we find that the long axis of the (MM) VII intensity contour for such large earthquakes well approximates the length and location of rupture along the subduction zone and can thus be used to estimate the locations and magnitudes of older events. The section from western El Salvador to Chiapas appears to have ruptured completely in a series of four to five earthquakes during each of the periods 1902–1915, 1743–1776, and possibly 1565–1577. Earthquakes of M W 7.75 ± 0.3 have caused major damage along the 200 km long section from San Salvador to Guatemala City every 71 ± 17 yr, apparently since at least 1575. Although the January 2001 El Salvador earthquake caused damage within part of this zone, no major thrust earthquake has occurred there since at least 1915. We find that much of this section has been relatively quiescent for moderate earthquakes shallower that 50 km since at least 1963. The conditional probability that an earthquake of M W 7.75 ± 0.3 will occur at this location in the next 20 yr is estimated at 50% (±30%).

Chiapas↗
USGS1965

Ordovician, Silurian, and Devonian biostratigraphy of east-central Alaska

A predominantly shale and chert sequence has been mapped from the Canadian border at Latitude 65°00′ N. to the Nation River about 25 miles northwest. It has Ordovician and Silurian graptolites in the lower half, and Middle Devonian corals and Upper Devonian spores in the upper half. The lower half of the sequence consists of about 400 to 900 feet of predominantly dark gray graptolitic shale with lesser amounts of grayish black laminated chert. This unit has been traced by Green and Roddick from the international border southeastward into the Dawson area of the Yukon Territory and northeastward into the Ogilvie and Richardson Mountains where it has been mapped by Jackson & Lenz, Norris, and others as the Road River Formation. In the Tatonduk-Nation Rivers area the Road River Formation rests disconformably on a sequence of Middle and Upper Cambrian limestone that locally may include Lower Ordovician (Tremadoc) beds at its top. The sequence of graptolite faunas from the Road River Formation in Alaska is essentially the same as the graptolite zones established by Elles and Wood in Great Britain. All the standard series of the Ordovician and Silurian are probably represented in the formation with the exception of the Tremadoc and possibly the Arenig and Wenlock. Overlying the Road River Formation is a formation, 200 to 800 feet thick, consisting predominantly of thinly bedded and laminated light gray to black chert and siliceous shale that is here named the McCann Hill Chert. This new formation disconformably overlies the Road River Formation, and its lower boundary is at the base of a distinctive limestone and shale member. The basal limestone and shale member of the McCann Hill Chert contains a remarkably varied fauna including corals, brachiopods, trilobites, conodonts, ostracods, and fish of Eifelian (early Middle Devonian) age. Spores from the upper part of the formation resemble those from the overlying Nation River Formation and indicate a Late Devonian age. The McCann Hill Chert is conformably overlain by the Nation River Formation—a thick succession of inter-bedded graywacke, chert conglomerate, and silty shale of Late Devonian age. In the vicinity of Jones Ridge, only 7 miles north of exposures of the Road River Formation, Upper Cambrian limestone is overlain by a pure limestone section containing Ordovician, Middle Devonian, and perhaps Silurian shelly faunas contemporaneous with the Road River Formation and the thinner basal limestone and shale member of the McCann Hill Chert. The rapid change from graptolitic shale to limestone probably reflects changes in conditions of sedimentation, but could be a result of thrust faulting. The Tatonduk-Nation Rivers area seems to lie in a transitional zone between an early Paleozoic eugeosynclinal belt south of the Yukon River and a contemporaneous miogeosynclinal belt along the Porcupine River. One puzzling feature of the lower Paleozoic sequence in the Tatonduk-Nation Rivers area is its thinness in contrast to the much thicker volcanic and detrital sequence on the south and the considerably thicker carbonate sequence on the north.

Alaska↗
USGS1983

Water-level changes in the high plains regional aquifer, northwestern Oklahoma, predevelopment to 1980

During 1978, the U.S. Geological Survey began a 5-year study of the High Plains regional aquifer system to provide hydrologic information for evaluation of the effects of long-term development of the aquifer and to develop computer models for prediction of aquifer response to alternative changes in ground-water management (Weeks, 1978). This report is one of a series presenting hydrologic information of the High Plains aquifer in Oklahoma. The predevelopment to 1980 water-level changes in the High Plains regional aquifer in Oklahoma are shown for Harper, Ellis, Woodward, Dewey, and Roger Mills Counties, on the east, and for the Oklahoma Panhandle, consist- ing of Cimarron, Texas, and Beaver Counties, on the west. About 1,470 water-level measurements in the Panhandle were used in compiling the predevelopment water-table map (Havens, 1982c). In the remaining area to the east about 150 water-level measurements from the 1950's to the 1970's are representative of predevelopment water levels. For the 1980 water-table map, about 330 measurements were made in the Panhandle and about 350 measurements in the eastern area by the Oklahoma Water Resources Board (Havens, 1982b).

Water-Resources Investigations Report↗
USGS1988

Water resources of Oley Township, Berks County, Pennsylvania

Oley Township covers an area of 24 square miles, about half of which is underlain by highly permeable carbonate rocks. Nondomestic wells in these rocks typically have yields of 200 gallons per minute, and some wells yield more than 1,000 gallons per minute. Ground-water yield for Oley Township is about 0.5 million gallons per day per square mile. Thus, about 12 million gallons per day could be pumped from wells on a sustained basis. However, pumping this amount would adversely affect streamflow. A series of discharge measurements on Manatawny Creek in January 1983 showed that the creek was gaining approximately 12 cubic feet per second where it crosses the more- permeable carbonate rocks. Thus, the streams are directly connected to these aquifers. The northern and western parts of the township are mostly underlain by shale, quartzite, granite, gneiss, and carbonate rocks of low permeability, and some wells do not yield enough water for domestic supplies. A water-table map shows that two active quarries in low-permeability rocks have had little effect on the hydrologic system. Specific yields are about 4.5 percent for the carbonate rocks; 5 percent for quartzite, granite, and gneiss; 1 percent for the noncarbonate sedimentary rocks; and 1.5 percent for the Jacksonburg Limestone, which consists of argillaceous limestone. In 1982--a year of average precipitation--the ground-water contribution to total streamflow ranged from 56 to 88 percent. Basins with the highest percentage of carbonate rock contribute the largest amount of ground water to streamflow. Evapotranspiration averaged about 26 inches in 1982. Water loss was 32 inches in the Limekiln Creek basin; this suggests that about 6 inches of precipitation bypassed the Limekiln Creek gaging station as ground-water underflow. The most serious water-quality problems are excessive nitrate concentrations and bacterial contamination. Water from 3 of 19 wells in carbonate rocks had nitrate concentrations in excess of the U.S. Environmental Protection Agency maximum contaminant level of 10 milligrams per liter. Water from 5 of the 19 wells had fecal streptococci counts of more than 20 colonies per 100 milliliters. Although most agencies concerned with the protection of public health have not set limits for fecal streptococci, they are pathogenic, and their presence in drinking water is undesirable.

Water-Resources Investigations Report↗
USGS2021

Detecting shrub recovery in sagebrush steppe: Comparing Landsat-derived maps with field data on historical wildfires

Background The need for basic information on spatial distribution and abundance of plant species for research and management in semiarid ecosystems is frequently unmet. This need is particularly acute in the large areas impacted by megafires in sagebrush steppe ecosystems, which require frequently updated information about increases in exotic annual invaders or recovery of desirable perennials. Remote sensing provides one avenue for obtaining this information. We considered how a vegetation model based on Landsat satellite imagery (30 m pixel resolution; annual images from 1985 to 2018) known as the National Land Cover Database (NLCD) “Back-in-Time” fractional component time-series, compared with field-based vegetation measurements. The comparisons focused on detection thresholds of post-fire emergence of fire-intolerant Artemisia L . species, primarily A. tridentata Nutt. (big sagebrush). Sagebrushes are scarce after fire and their paucity over vast burn areas creates challenges for detection by remote sensing. Measurements were made extensively across the Great Basin, USA, on eight burn scars encompassing ~500 000 ha with 80 plots sampled, and intensively on a single 113 000 ha burned area where we sampled 1454 plots. Results Estimates of sagebrush cover from the NLCD were, as a mean, 6.5% greater than field-based estimates, and variance around this mean was high. The contrast between sagebrush cover measurements in field data and NLCD data in burned landscapes was considerable given that maximum cover values of sagebrush were ~35% in the field. It took approximately four to six years after the fire for NLCD to detect consistent, reliable signs of sagebrush recovery, and sagebrush cover estimated by NLCD ranged from 3 to 13% (equating to 0 to 7% in field estimates) at these times. The stabilization of cover and presence four to six years after fire contrasted with previous field-based studies that observed fluctuations over longer time periods. Conclusions While results of this study indicated that further improvement of remote sensing applications would be necessary to assess initial sagebrush recovery patterns, they also showed that Landsat satellite imagery detects the influence of burns and that the NLCD data tend to show faster rates of recovery relative to field observations.

Oregon, Idaho, Nevada, Utah↗
USGS2012

EAARL coastal topography--Alligator Point, Louisiana, 2010

This project provides highly detailed and accurate datasets of a portion of Alligator Point, Louisiana, acquired on March 5 and 6, 2010. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the National Aeronautics and Space Administration (NASA) Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the "bare earth" under vegetation from a point cloud of last return elevations.

Louisiana↗
USGS2006

Chapter 4: The GIS Project for the Geologic Assessment of Undiscovered Oil and Gas in the Upper Cretaceous Navarro and Taylor Groups, Western Gulf Province, Texas

A geographic information system (GIS) focusing on the Upper Cretaceous Navarro and Taylor Groups in the Gulf Coast region was developed as a visual-analysis tool for the U.S. Geological Survey's 2003 assessment of undiscovered, technically recoverable oil and natural gas resources in the Western Gulf Province. The Central Energy Resources Team of the U.S. Geological Survey has also developed an Internet Map Service to deliver the GIS data to the general public. This mapping tool utilizes information from a database about the oil and natural gas endowment of the United States - including physical locations of geologic and geographic data - and converts the data into visual layers. Portrayal and analysis of geologic features on an interactive map provide an excellent tool for understanding domestic oil and gas resources for strategic planning, formulating economic and energy policies, evaluating lands under the purview of the Federal Government, and developing sound environmental policies. Assessment results can be viewed and analyzed or downloaded from the internet web site.

Data Series↗
USGS2014

Vegetation database for land-cover mapping, Clark and Lincoln Counties, Nevada

Floristic and other vegetation data were collected at 3,175 sample sites to support land-cover mapping projects in Clark and Lincoln Counties, Nevada, from 2007 to 2013. Data were collected at sample sites that were selected to fulfill mapping priorities by one of two different plot sampling approaches. Samples were described at the stand level and classified into the National Vegetation Classification hierarchy at the alliance level and above. The vegetation database is presented in geospatial and tabular formats.

Nevada↗
USGS2017

Remote measurement of river discharge using thermal particle image velocimetry (PIV) and various sources of bathymetric information

Although river discharge is a fundamental hydrologic quantity, conventional methods of streamgaging are impractical, expensive, and potentially dangerous in remote locations. This study evaluated the potential for measuring discharge via various forms of remote sensing, primarily thermal imaging of flow velocities but also spectrally-based depth retrieval from passive optical image data. We acquired thermal image time series from bridges spanning five streams in Alaska and observed strong agreement between velocities measured in situ and those inferred by Particle Image Velocimetry (PIV), which quantified advection of thermal features by the flow. The resulting surface velocities were converted to depth-averaged velocities by applying site-specific, calibrated velocity indices. Field spectra from three clear-flowing streams provided strong relationships between depth and reflectance, suggesting that, under favorable conditions, spectrally-based bathymetric mapping could complement thermal PIV in a hybrid approach to remote sensing of river discharge; this strategy would not be applicable to larger, more turbid rivers, however. A more flexible and efficient alternative might involve inferring depth from thermal data based on relationships between depth and integral length scales of turbulent fluctuations in temperature, captured as variations in image brightness. We observed moderately strong correlations for a site-aggregated data set that reduced station-to-station variability but encompassed a broad range of depths. Discharges calculated using thermal PIV-derived velocities were within 15% of in situ measurements when combined with depths measured directly in the field or estimated from field spectra and within 40% when the depth information also was derived from thermal images. The results of this initial, proof-of-concept investigation suggest that remote sensing techniques could facilitate measurement of river discharge.

Journal of Hydrology↗
USGS2008

TerraLook: GIS-Ready Time-Series of Satellite Imagery for Monitoring Change

TerraLook is a joint project of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL) with a goal of providing satellite images that anyone can use to see changes in the Earth's surface over time. Each TerraLook product is a user-specified collection of satellite images selected from imagery archived at the USGS Earth Resources Observation and Science (EROS) Center. Images are bundled with standards-compliant metadata, a world file, and an outline of each image's ground footprint, enabling their use in geographic information systems (GIS), image processing software, and Web mapping applications. TerraLook images are available through the USGS Global Visualization Viewer (http://glovis.usgs.gov).

Fact Sheet↗
USGS2020

Quantifying western U.S. rangelands as fractional components with multi-resolution remote sensing and in situ data

Quantifying western U.S. rangelands as a series of fractional components with remote sensing provides a new way to understand these changing ecosystems. Nine rangeland ecosystem components, including percent shrub, sagebrush ( Artemisia ), big sagebrush, herbaceous, annual herbaceous, litter, and bare ground cover, along with sagebrush and shrub heights, were quantified at 30 m resolution. Extensive ground measurements, two scales of remote sensing data from commercial high-resolution satellites and Landsat 8, and regression tree models were used to create component predictions. In the mapped area (2,993,655 km²), bare ground averaged 45.5%, shrub 15.2%, sagebrush 4.3%, big sagebrush 2.9%, herbaceous 23.0%, annual herbaceous 4.2%, and litter 15.8%. Component accuracies using independent validation across all components averaged R 2 values of 0.46 and an root mean squared error (RMSE) of 10.37, and cross-validation averaged R 2 values of 0.72 and an RMSE of 5.09. Component composition strongly varies by Environmental Protection Agency (EPA) level III ecoregions ( n = 32): 17 are bare ground dominant, 11 herbaceous dominant, and four shrub dominant. Sagebrush physically covers 90,950 km², or 4.3%, of our study area, but is present in 883,449 km², or 41.5%, of the mapped portion of our study area.

Arizona, California, Colorado, Idaho, Montana, Nev↗
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↗
USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ahankashan 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 Ahankashan mineral district, which has copper 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 (©JAXA,2007,2008, 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 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 Ahankashan) and the WGS84 datum. The final image mosaics were subdivided into five overlapping tiles or quadrants because of the large size of the target area. The five image tiles (or quadrants) for the Ahankashan 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.

Ahankashan Mineral District↗
USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Parwan mineral district in Afghanistan: Chapter CC 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 Parwan mineral district, which has gold and 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,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. 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 Parwan) 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 North 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.

Parwan Mineral District↗
USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North 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 North Bamyan 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,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 North Bamyan) 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 North 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.

North Bamyan Mineral District↗
USGS2014

Evaluating CO2 and CH4 dynamics of Alaskan ecosystems during the Holocene Thermal Maximum

The Arctic has experienced much greater warming than the global average in recent decades due to polar amplification. Warming has induced ecological changes that have impacted climate carbon-cycle feedbacks, making it important to understand the climate and vegetation controls on carbon (C) dynamics. Here we used the Holocene Thermal Maximum (HTM, 11–9 ka BP, 1 ka BP = 1000 cal yr before present) in Alaska as a case study to examine how ecosystem Cdynamics responded to the past warming climate using an integrated approach of combining paleoecological reconstructions and ecosystem modeling. Our paleoecological synthesis showed expansion of deciduous broadleaf forest (dominated by Populus ) into tundra and the establishment of boreal evergreen needleleaf and mixed forest during the second half of the HTM under a warmer- and wetter-than-before climate, coincident with the occurrence of the highest net primary productivity, cumulative net ecosystem productivity, soil C accumulation and CH 4 emissions. These series of ecological and biogeochemical shifts mirrored the solar insolation and subsequent temperature and precipitation patterns during HTM, indicating the importance of climate controls on C dynamics. Our simulated regional estimate of CH 4 emission rates from Alaska during the HTM ranged from 3.5 to 6.4 Tg CH 4 yr −1 and highest annual NPP of 470 Tg C yr −1 , significantly higher than previously reported modern estimates. Our results show that the differences in static vegetation distribution maps used in simulations of different time slices have greater influence on modeled C dynamics than climatic fields within each time slice, highlighting the importance of incorporating vegetation community dynamics and their responses to climatic conditions in long-term biogeochemical modeling.

Alaska↗
USGS1994

Regional Aquifer-System Analysis Program of the U.S. Geological Survey, 1978-1992

The major ground-water systems of the United States have been investigated by the U.S. Geological Survey (USGS) through its Regional Aquifer-System Analysis (RASA) Program. During the first 15 years of the program (1978-92), 25 regional aquifer systems, including the most heavily pumped aquifers in the Nation, were intensively studied. As of mid-1992, 18 of the regional aquifer studies are completed or nearly so; 7 of the regional aquifer studies are ongoing, and compilation of a national ground-water atlas is in progress. This report summarizes the status of each RASA study and briefly describes the hydrology of the 25 regional aquifer systems. Important study results and examples of applications of study results are presented for some of the completed RASA investigations. The major contributions of the RASA Program are (1) assembly of data from numerous local studies and long-time data collections into systematic regional data bases; (2) comprehensive descriptions of the geologic, hydrologic, and geochemical characteristics of the regional aquifer systems; and (3) an understanding of how the regional ground-water-flow systems function under natural (predevelopment) and current (developed) conditions. To provide the comprehensive system descriptions, many of the RASA studies present, for the first time, maps depicting the hydrogeologic frameworks, water chemistry, potentiometric surfaces, and other aspects of entire regional aquifer systems. To provide an understanding of how the flow systems function, several of the completed RASA studies provide, for the first time, hydrologic budgets for both predevelopment and developed conditions. The results of the RASA Program are contained in nearly 900 reports published by the USGS, as well as various State and local agencies, and in articles published in scientific journals. A series of U.S. Geological Survey Professional Papers are being published to summarize and synthesize the results of each RASA study.

Circular↗
USGS2008

Arkansas and Louisiana aeromagnetic and gravity maps and data— A website for distribution of data

This report contains digital data, image files, and text files describing data formats for aeromagnetic and gravity data used to compile the State aeromagnetic and gravity maps of Arkansas and Louisiana. The digital files include grids, images, ArcInfo, and Geosoft compatible files. In some of the data folders, ASCII files with the extension 'txt' describe the format and contents of the data files. Read the 'txt' files before using the data files.

Arkansas, Louisiana↗