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USGS2018

Land-cover changes associated with oil and natural-gas production and concentrations of selected constituents in surface-water and streambed-sediment samples collected upstream from and within an area of oil and natural-gas production, south Texas, 2008–17

The extensive development of oil and natural-gas resources in south Texas during the past 10 years has led to questions regarding possible environmental effects of processes associated with oil and natural-gas production, in particular the process of hydraulic fracturing, on water and other natural resources. Part of the lower San Antonio River watershed intersects an area of oil and natural-gas production from the sedimentary rocks that compose the Eagle Ford Group. The rapid expansion of infrastructure associated with oil and natural-gas production increases potential pathways for inorganic and organic contaminants to enter surface-water systems. The U.S. Geological Survey, in cooperation with the San Antonio River Authority, analyzed geospatial data from different years (2008 and 2015) to evaluate changes in land cover associated with oil and natural-gas production activities in the lower San Antonio River watershed. Impervious surface in this study is defined as land cover consisting of well pads, oil- and gas-related features, or roads. The areal coverage associated with impervious surface increased from 201 acres to 5,390 acres (net increase of 5,189 acres) between 2008 and 2015. The total percentage of the study area accounted for by impervious surface resulting from oil and natural-gas production activities increased from 0.034 percent to 0.912 percent, which is an increase of approximately 27-fold. Collectively, 0.878 percent of the study area was converted to new impervious surface between 2008 and 2015. If the area associated with new storage ponds (0.066 percent) is added to the estimate of total land-cover changes as a result of oil and natural-gas production, then 0.944 percent of the study area was altered. During 2015–17, surface-water samples collected from 5 sites and streambed-sediment samples collected from 17 sites in the lower San Antonio River watershed were analyzed for a broad range of constituents that might be associated with oil and natural-gas production. All major elements, trace elements, semivolatile organic compounds (SVOCs), and volatile organic compounds (VOCs) measured in surface-water samples were detected at concentrations less than any of the U.S. Environmental Protection Agency’s water-quality standards. In general, the greatest SVOC and VOC concentrations were observed in samples collected from sites upstream from the area of active oil and natural-gas production and just downstream from urban areas. The lack of benzene, toluene, ethylbenzene, and all isomers of xylene (hereinafter referred to as BTEX) for most sites within the area of active oil and natural-gas production indicates that little, if any, local runoff associated with the area of active oil and natural-gas production has contaminated the surface water with BTEX compounds. Glycols, which are commonly used in hydraulic fracturing fluids as scale inhibitors, were detected in one surface-water sample from Ecleto Creek within the area of oil and natural-gas production; however, the presence of glycols does not necessarily indicate contamination from hydraulic fracturing fluid. The glycols detected also have other potential sources including the use of diethylene and ethylene glycols in antifreeze used in vehicles and the use of triethylene glycol in antibacterial air sanitizers. The concentrations of select constituents in the streambed-sediment samples were compared to sediment quality guidelines (SQGs). The SQGs evaluate the potential toxicity of bed sediments to sediment-dwelling organisms. Two SQG concentration levels are used: (1) a lower level, called the threshold effect concentration (TEC), below which harmful effects to benthic biota are not expected, and (2) a higher level, the probable effect concentration (PEC), above which harmful effects are expected to occur frequently. The PEC for arsenic was exceeded in a sample collected from one site on Ecleto Creek. The origin of the elevated arsenic concentration is unknown; the contamination likely is not related to oil and natural-gas production because the site of the sample collection is located upstream from the area of active oil and natural-gas production. Streambed-sediment samples were analyzed for selected polycyclic aromatic hydrocarbons (PAHs) because PAHs can be used as indicators of petroleum hydrocarbons associated with produced waters. Each streambed-sediment sample was analyzed for two size fractions of PAHs: less than (<) 63 micrometers (μm) and < 2 millimeters (mm). Total PAH concentrations in all samples, regardless of size fraction, were less than the TEC for total PAHs of 1,610 micrograms per kilogram. Total PAH concentrations generally were greater in the <63-μm size-fraction samples than in the <2-mm size-fraction samples, indicating that PAHs could potentially sorb more readily to the exclusively silt- and clay-sized particles that compose <63-μm size-fraction samples than to the mixture of silt and clay and larger sized particles that compose the <2-mm size-fraction samples. Total PAH concentrations typically were greater in the samples collected from the sites upstream from the area of active oil and natural-gas production compared to those collected from sites within the area in both the <2-mm and <63-μm size-fraction samples. The smaller PAH concentrations measured in samples collected from within the area of active oil and natural-gas production in comparison to the upstream urbanized areas indicate relatively minor additional local contributions of PAHs of uncertain origin to the watershed.

Texas↗

USGS2023

Bringing the Nature Futures Framework to life: Creating a set of illustrative narratives of nature futures

To halt further destruction of the biosphere, most people and societies around the globe need to transform their relationships with nature. The internationally agreed vision under the Convention of Biological Diversity—Living in harmony with nature—is that “By 2050, biodiversity is valued, conserved, restored and wisely used, maintaining ecosystem services, sustaining a healthy planet and delivering benefits essential for all people”. In this context, there are a variety of debates between alternative perspectives on how to achieve this vision. Yet, scenarios and models that are able to explore these debates in the context of “living in harmony with nature” have not been widely developed. To address this gap, the Nature Futures Framework has been developed to catalyse the development of new scenarios and models that embrace a plurality of perspectives on desirable futures for nature and people. In this paper, members of the IPBES task force on scenarios and models provide an example of how the Nature Futures Framework can be implemented for the development of illustrative narratives representing a diversity of desirable nature futures: information that can be used to assess and develop scenarios and models whilst acknowledging the underpinning value perspectives on nature. Here, the term illustrative reflects the multiple ways in which desired nature futures can be captured by these narratives. In addition, to explore the interdependence between narratives, and therefore their potential to be translated into scenarios and models, the six narratives developed here were assessed around three areas of the transformative change debate, specifically, (1) land sparing vs. land sharing, (2) Half Earth vs. Whole Earth conservation, and (3) green growth vs. post-growth economic development. The paper concludes with an assessment of how the Nature Futures Framework could be used to assist in developing and articulating transformative pathways towards desirable nature futures.

Sustainability Science↗

USGS2024

Leveraging natural capital accounting to support businesses with nature-related risk assessments and disclosures

Nature loss threatens businesses, the global economy and financial stability. Understanding and addressing these risks for business will require credible measurement approaches and data. This paper explores how natural capital accounting (NCA) can support business data and information needs related to nature, including disclosures aligned with the Taskforce on Nature-related Financial Disclosures recommendations. As businesses seek to measure, manage and disclose their nature-related risks and opportunities, they will need well-organized, consistent and high-quality information regarding their dependencies and impacts on nature, which few businesses currently collect or track in-house. NCA may be useful for these purposes but has not been widely used or applied by businesses. National NCA guided by the U.N. System of Environmental-Economic Accounting may provide: (i) a useful framework for businesses in conceptualizing, organizing and managing nature-related data and statistics; and (ii) data and information that can directly support business disclosures, corporate NCA and other business applications. This paper explores these opportunities as well as synergies between national and corporate natural capital accounts. In addition, the paper discusses key barriers to advancing the wider use and benefits of NCA for business, including: awareness of NCA, data access, business capabilities related to NCA, spatial and temporal scales of data, audit and assurance considerations, potential risks, and costs and incentives.

Philosophical Transactions of the Royal Society B:↗

USGS2015

Markov decision processes in natural resources management: observability and uncertainty

The breadth and complexity of stochastic decision processes in natural resources presents a challenge to analysts who need to understand and use these approaches. The objective of this paper is to describe a class of decision processes that are germane to natural resources conservation and management, namely Markov decision processes, and to discuss applications and computing algorithms under different conditions of observability and uncertainty. A number of important similarities are developed in the framing and evaluation of different decision processes, which can be useful in their applications in natural resources management. The challenges attendant to partial observability are highlighted, and possible approaches for dealing with it are discussed.

Ecological Modelling↗

USGS2015

Natural or Induced: Identifying Natural and Induced Swarms from Pre-production and Co-production Microseismic Catalogs at the Coso Geothermal Field

Increased levels of seismicity coinciding with injection of reservoir fluids have prompted interest in methods to distinguish induced from natural seismicity. Discrimination between induced and natural seismicity is especially difficult in areas that have high levels of natural seismicity, such as the geothermal fields at the Salton Sea and Coso, both in California. Both areas show swarm-like sequences that could be related to natural, deep fluid migration as part of the natural hydrothermal system. Therefore, swarms often have spatio-temporal patterns that resemble fluid-induced seismicity, and might possibly share other characteristics. The Coso Geothermal Field and its surroundings is one of the most seismically active areas in California with a large proportion of its activity occurring as seismic swarms. Here we analyze clustered seismicity in and surrounding the currently produced reservoir comparatively for pre-production and co-production periods. We perform a cluster analysis, based on the inter-event distance in a space-time-energy domain to identify notable earthquake sequences. For each event j, the closest previous event i is identified and their relationship categorized. If this nearest neighbor’s distance is below a threshold based on the local minimum of the bimodal distribution of nearest neighbor distances, then the event j is included in the cluster as a child to this parent event i. If it is above the threshold, event j begins a new cluster. This process identifies subsets of events whose nearest neighbor distances and relative timing qualify as a cluster as well as a characterizing the parent-child relationships among events in the cluster. We apply this method to three different catalogs: (1) a two-year microseismic survey of the Coso geothermal area that was acquired before exploration drilling in the area began; (2) the HYS_catalog_2013 that contains 52,000 double-difference relocated events and covers the years 1981 to 2013; and (3) a catalog of 57,000 events with absolute locations from the local network recorded between 2002 and 2007. Using this method we identify 10 clusters of more than 20 events each in the pre-production survey and more than 200 distinct seismicity clusters that each contain at least 20 and up to more than 1000 earthquakes in the more extensive catalogs. The cluster identification method used yields a hierarchy of links between multiple generations of parent and offspring events. We analyze different topological parameters of this hierarchy to better characterize and thus differentiate natural swarms from induced clustered seismicity and also to identify aftershock sequences of notable mainshocks. We find that the branching characteristic given by the average number of child events per parent event is significantly different for clusters below than for clusters around the produced field.

Conference Paper↗

USGS2013

Sustainably connecting children with nature: an exploratory study of nature play area visitor impacts and their management

Parks are developing nature play areas to improve children's health and “connect” them with nature. However, these play areas are often located in protected natural areas where managers must balance recreation with associated environmental impacts. In this exploratory study, we sought to describe these impacts. We also investigated which ages, gender, and play group sizes most frequently caused impact and where impacts most frequently occur. We measured the lineal and aerial extent and severity of impacts at three play areas in the eastern United States. Methods included soil and vegetation loss calculations, qualitative searches and tree and shrub damage classifications. Additionally, we observed 12 h of play at five play areas. Results showed that measurable negative impacts were caused during 33% of the time children play. On average, 76% of groundcover vegetation was lost at recreation sites and 100% was lost at informal trails. In addition, approximately half of all trees and shrubs at sites were damaged. Meanwhile, soil exposure was 25% greater on sites and trails than at controls. Boys and small group sizes more frequently caused impact, and informal recreation sites were most commonly used for play. No statistically significant correlations were found between age or location and impact frequency. Managers interested in developing nature play areas should be aware of, but not deterred by these impacts. The societal benefits of unstructured play in nature may outweigh the environmental costs. Recommended management strategies include selecting impact-resistant sites, improving site resistance, promoting low impact practices, and managing adaptively.

Landscape and Urban Planning↗

USGS2021

Responses of vertebrate wildlife to oil and natural gas development: Patterns and frontiers

Purpose of Review Anthropogenic activities can lead to the loss, fragmentation, and alteration of wildlife habitats. I reviewed the recent literature (2014–2019) focused on the responses of avian, mammalian, and herpetofaunal species to oil and natural gas development, a widespread and still-expanding land use worldwide. My primary goals were to identify any generalities in species’ responses to development and summarize remaining gaps in knowledge. To do so, I evaluated the directionality of a wide variety of responses in relation to taxon, location, development type, development metric, habitat type, and spatiotemporal aspects. Recent Findings Studies ( n = 70) were restricted to the USA and Canada, and taxonomically biased towards birds and mammals. Longer studies, but not those incorporating multiple spatial scales, were more likely to detect significant responses. Negative responses of all types were present in relatively low frequencies across all taxa, locations, development types, and development metrics but were context-dependent. The directionality of responses by the same species often varied across studies or development metrics. Summary The state of knowledge about wildlife responses to oil and natural gas development has developed considerably, though many biases and gaps remain. Studies outside of North America and that focus on herpetofauna are lacking. Tests of mechanistic hypotheses for effects, long-term studies, assessment of response thresholds, and experimental designs that isolate the effects of different stimuli associated with development, remain critical. Moreover, tests of the efficacy of habitat mitigation efforts have been rare. Finally, investigations of the demographic effects of development across the full annual cycle were absent for non-game species and are critical for the estimation of population-level effects.

Current Landscape Ecology Reports↗

USGS2012

The Spar Lake strata-Bound Cu-Ag deposit formed across a mixing zone between trapped natural gas and metals-bearing brine

Ore formation at the Spar Lake red bed-associated strata-bound Cu deposit took place across a mixing and reaction zone between a hot oxidized metals-transporting brine and a reservoir of “sour” (H 2 S-bearing) natural gas trapped in the host sandstones. Fluid inclusion volatile analyses have very high CH 4 concentrations (≥1 mol % in most samples), and a sample from the fringe of the deposit has between 18 and 36 mol % CH 4 . The ratio of CH 4 /CO 2 in fluid inclusions appears to vary regularly across the deposit, with the lowest CH 4 /CO 2 ratios from high-grade chalcocite-bearing ore, and the highest from the chalcopyrite-bearing fringe. The helium R/R a isotope ratios (0.23–0.98) and concentrations define a mixture between crustal and atmospheric helium. The volatiles in fluid inclusions (CH 4 , CO 2 , H 2 S, SO 2 , H 2 , H 2 O, and other organic gases) and values of f O 2 and temperature calculated from the volatiles data all show gradations across the deposit that are completely consistent with such a mixing and reaction zone. Other volatiles from the fluid inclusions (HCl, HF, 3 He, Msup>4 He, N 2 , Ar) characterize the brine and give evidence for only shallow crustal fluids with no magmatic influences. The brine entered the gas reservoir from below and along the axis of the deposit and migrated out along bedding to the southwest, northeast, and northwest. Metals-transporting brines may have been fed into the host sandstones from the East Fault, but that remains uncertain. Abundant ore-stage Fe and Mn calcite cements from the reduced fringe have δ 13 C values as low as −18.4‰, and many values less than −10‰, which indicate that significant carbonate was generated by oxidation of organic carbon from the natural gas. The zone of calcite cements with very low δ 13 C values approximately envelopes chalcocite-bearing ore. Sulfur isotope data of Cu, Pb, and Fe sulfides and barite indicate derivation of roughly half of the orebody sulfide directly from sour gas H 2 S. That sour gas H 2 S had developed in steps known from other sedimentary basins, starting with (1) bacterial sulfate reduction (BSR) of seawater sulfate having δ 34 S of about 20‰ and sequestering of the sulfide in organic matter in source rocks stratigraphically below the deposit host rocks, followed by (2) maturation of the sulfide-bearing organic matter into liquid petroleum with relatively homogeneous sulfide having δ 34 S of 5 ± 5‰, then by (3) thermal cracking of the oil to CH 4 and H 2 S with relatively homogeneous sulfide having δ 34 S closely distributed, about 6‰. The CH 4 and H 2 S migrated and were trapped in sandstones of the upper member of the Revett Formation, where they were later met by the 200°C metals-transporting brine. There was additional contribution of sulfide to ore from later thermochemical sulfate reduction (TSR) operating on sulfate δ 34 S of 20 to 29‰ in both formation waters and metals-transporting solutions. A large range of δ 34 S in sulfides resulted as the 6‰ sour gas sulfide was supplemented with varying proportions of 20 to 29‰ sulfide from TSR.

Economic Geology↗

USGS2015

Central Appalachian basin natural gas database: distribution, composition, and origin of natural gases

The U.S. Geological Survey (USGS) has compiled a database consisting of three worksheets of central Appalachian basin natural gas analyses and isotopic compositions from published and unpublished sources of 1,282 gas samples from Kentucky, Maryland, New York, Ohio, Pennsylvania, Tennessee, Virginia, and West Virginia. The database includes field and reservoir names, well and State identification number, selected geologic reservoir properties, and the composition of natural gases (methane; ethane; propane; butane, iso -butane [ i -butane]; normal butane [ n -butane]; iso -pentane [ i -pentane]; normal pentane [ n -pentane]; cyclohexane, and hexanes). In the first worksheet, location and American Petroleum Institute (API) numbers from public or published sources are provided for 1,231 of the 1,282 gas samples. A second worksheet of 186 gas samples was compiled from published sources and augmented with public location information and contains carbon, hydrogen, and nitrogen isotopic measurements of natural gas. The third worksheet is a key for all abbreviations in the database. The database can be used to better constrain the stratigraphic distribution, composition, and origin of natural gas in the central Appalachian basin.

Kentucky, Maryland, New York, Ohio, Pennsylvania, ↗

USGS2010

Transport of reacting solutes in porous media: Relation between mathematical nature of problem formulation and chemical nature of reactions

Examples involving six broad reaction classes show that the nature of transport-affecting chemistry may have a profound effect on the mathematical character of solute transport problem formulation. Substantive mathematical diversity among such formulations is brought about principally by reaction properties that determine whether (1) the reaction can be regarded as being controlled by local chemical equilibria or whether it must be considered as being controlled by kinetics, (2) the reaction is homogeneous or heterogeneous, (3) the reaction is a surface reaction (adsorption, ion exchange) or one of the reactions of classical chemistry (e.g., precipitation, dissolution, oxidation, reduction, complex formation). These properties, as well as the choice of means to describe them, stipulate, for instance, (1) the type of chemical entities for which a formulation's basic, mass-balance equations should be written; (2) the nature of mathematical transformations needed to change the problem's basic equations into operational ones. These and other influences determine such mathematical features of problem formulations as the nature of the operational transport-equation system (e.g., whether it involves algebraic, partial-differential, or integro-partial-differential simultaneous equations), the type of nonlinearities of such a system, and the character of the boundaries (e.g., whether they are stationary or moving). Exploration of the reasons for the dependence of transport mathematics on transport chemistry suggests that many results of this dependence stem from the basic properties of the reactions' chemical-relation (i.e., equilibrium or rate) equations.

Water Resources Research↗

USGS2011

Using a semi-natural stream to produce young sturgeons for conservation stocking: Maintaining natural selection during spawning and rearing

Young sturgeons used for conservation stocking are presently produced using the same methods used for commercial culture. To determine if young sturgeons could be produced without relaxing natural selection factors, we developed a semi‐natural stream where we annually studied mating of wild shortnose sturgeon ( Acipenser brevirostrum ) observed movement of gametes released freely during spawning, and estimated the number of larvae produced by various densities of spawned eggs. The stream had a bottom area of 18.8 m 2 , a rubble–gravel bottom, and a mean bottom current at 0.6 depth during spawning of 48 cm s −1 (range, 17–126 cm s −1 ). Wild adults successfully spawned in the stream each year for 7 years (2002–2008). Some females and males were more successful during spawning than others, suggesting an unequal fitness during spawning among wild individuals, which is different than the controlled spawning fitness of individuals in hatcheries. Male and female gametes spawned naturally must connect quickly in the fast current or fail, a selection factor absent in hatcheries. The number of larvae produced was inversely related to spawned egg density m −2 ( R 2 = 0.65) and the maximum number of larvae produced was 8000–16 000 (425–851 larvae m −2 of bottom). Artificial spawning streams have the potential to contribute to sturgeon restoration.

Journal of Applied Ichthyology↗

USGS2025

Performance evaluation of natural and nature-based features for coastal protection and co-benefits

Built infrastructure, such as seawalls and levees, has long been used to reduce shoreline erosion and protect coastal properties from flood impacts. In contrast, natural and nature-based features (NNBF), including marshes, mangroves, oyster reefs, coral reefs, and seagrasses, offer not only coastal protection but also a range of valuable ecosystem services. There is no clear understanding of the capacity of either natural habitats or NNBF integrated with traditional engineered infrastructure to withstand extreme events, nor are there well-defined breakpoints at which these habitats fail to provide coastal protection. Evaluating existing NNBF strategies using a standardized set of metrics can help to assess their effectiveness to better inform design criteria. This review identifies a selection of NNBF projects with long-term monitoring programs and synthesizes the monitoring data to provide a literature-based performance assessment. It also explores the integration of NNBF with existing gray infrastructure to enhance overall effectiveness.

Annual Review of Marine Science↗

USGS2011

40Ar∗ loss in experimentally deformed muscovite and biotite with implications for 40Ar/39Ar geochronology of naturally deformed rocks

The effects of deformation on radiogenic argon ( 40 Ar ∗ ) retentivity in mica are described from high pressure experiments performed on rock samples of peraluminous granite containing euhedral muscovite and biotite. Cylindrical cores, ∼15 mm in length and 6.25 mm in diameter, were drilled from granite collected from the South Armorican Massif in northwestern France, loaded into gold capsules, and weld-sealed in the presence of excess water. The samples were deformed at a pressure of 10 kb and a temperature of 600 °C over a period 29 of hours within a solid medium assembly in a Griggs-type triaxial hydraulic deformation apparatus. Overall shortening in the experiments was approximately 10%. Transmitted light and secondary and backscattered electron imaging of the deformed granite samples reveals evidence of induced defects and for significant physical grain size reduction by kinking, cracking, and grain segmentation of the micas. Infrared (IR) laser (CO 2 ) heating of individual 1.5–2.5 mm diameter grains of muscovite and biotite separated from the undeformed granite yield well-defined 40 Ar/ 39 Ar plateau ages of 311 ± 2 Ma (2σ). Identical experiments on single grains separated from the experimentally deformed granite yield results indicating 40 Ar ∗ loss of 0–35% in muscovite and 2–3% 40 Ar ∗ loss in biotite. Intragrain in situ ultraviolet (UV) laser ablation 40 Ar/ 39 Ar ages (±4–10%, 1σ) of deformed muscovites range from 309 ± 13 to 264 ± 7 Ma, consistent with 0–16% 40 Ar ∗ loss relative to the undeformed muscovite. The in situ UV laser ablation 40 Ar/ 39 Ar ages of deformed biotite vary from 301 to 217 Ma, consistent with up to 32% 40 Ar ∗ loss. No spatial correlation is observed between in situ 40 Ar/ 39 Ar age and position within individual grains. Using available argon diffusion data for muscovite the observed 40 Ar ∗ loss in the experimentally treated muscovite can be utilized to predict average 40 Ar ∗ diffusion dimensions. Maximum 40 Ar/ 39 Ar ages obtained by UV laser ablation overlap those of the undeformed muscovite, indicating argon loss of <1% and an average effective grain radius for 40 Ar ∗ diffusion ⩾700 μm. The UV laser ablation and IR laser incremental 40 Ar/ 39 Ar ages indicating 40 Ar ∗ loss of 16% and 35%, respectively, are consistent with an average diffusion radius ≪100 μm. These results support a hypothesis of grain-scale 40 Ar ∗ diffusion distances in undeformed mica and a heterogeneous mechanical reduction in the intragrain effective diffusion length scale for 40 Ar ∗ in deformed mica. Reduction in the effective diffusion length scale in naturally deformed samples occurs most probably through production of mesoscopic and submicroscopic defects such as, e.g., stacking faults. A network of interconnected defects, continuously forming and annealing during dynamic deformation likely plays an important role in controlling both 40 Ar ∗ retention and intragrain distribution in deformed mica. Intragrain 40 Ar/ 39 Ar ages, when combined with estimates of diffusion kinetics and distances, may provide a means of establishing thermochronological histories from individual micas.

Brittany↗

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↗

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↗

USGS2012

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Takhar mineral district in Afghanistan: Chapter D 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 North Takhar mineral district, which has placer 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,2006,2008), 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 North Takhar) 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 North Takhar 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 Takhar↗

USGS2012

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E 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 Aynak 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 ((c)JAXA,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 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 Aynak) and the WGS84 datum. The final image mosaics were subdivided into four overlapping tiles or quadrants because of the large size of the target area. The four image tiles (or quadrants) for the Aynak 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 Aynak study area, five subareas were designated for detailed field investigations (that is, the Bakhel-Charwaz, Kelaghey-Kakhay, Kharuti-Dawrankhel, Logar Valley, and Yagh-Darra/Gul-Darra subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.

Kabul;Logar;Paktya;Wardak↗