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At least 1,135 records · Page 63Linked to original sources
USGS2011

Digital surfaces and hydrogeologic data for the Floridan aquifer system in Florida and in parts of Georgia, Alabama, and South Carolina

A digital dataset for the Floridan aquifer system in Florida and in parts of Georgia, Alabama, and South Carolina was developed from selected reports published as part of the Regional Aquifer-System Analysis (RASA) Program of the U.S. Geological Survey (USGS) in the 1980s. These reports contain maps and data depicting the extent and elevation of both time-stratigraphic and hydrogeologic units of which the aquifer system is composed, as well as data on hydrology, meteorology, and aquifer properties. The three primary reports used for this dataset compilation were USGS Professional Paper 1403-B (Miller, 1986), Professional Paper 1403-C (Bush and Johnston, 1988), and USGS Open-File Report 88-86 (Miller, 1988). Paper maps from Professional Papers 1403-B and 1403-C were scanned and georeferenced to the North American Datum of 1927 (NAD27) using the Lambert Conformal Conic projection (standard parallels 33 and 45 degrees, central longitude -96 degrees, central latitude 39 degrees). Once georeferenced, tracing of pertinent line features contained in each image (for example, contours and faults) was facilitated by specialized software using algorithms that automated much of the process. Resulting digital line features were then processed using standard geographic information system (GIS) software to remove artifacts from the digitization process and to verify and update attribute tables. The digitization process for polygonal features (for example, outcrop areas and unit extents) was completed by hand using GIS software.

Alabama, Florida, Georgia, South Carolina↗
USGS2009

Modelling predation by transient leopard seals for an ecosystem-based management of Southern Ocean fisheries

Correctly quantifying the impacts of rare apex marine predators is essential to ecosystem-based approaches to fisheries management, where harvesting must be sustainable for targeted species and their dependent predators. This requires modelling the uncertainty in such processes as predator life history, seasonal abundance and movement, size-based predation, energetic requirements, and prey vulnerability. We combined these uncertainties to evaluate the predatory impact of transient leopard seals on a community of mesopredators (seals and penguins) and their prey at South Georgia, and assess the implications for an ecosystem-based management. The mesopredators are highly dependent on Antarctic krill and icefish, which are targeted by regional fisheries. We used a state-space formulation to combine (1) a mark-recapture open-population model and individual identification data to assess seasonally variable leopard seal arrival and departure dates, numbers, and residency times; (2) a size-based bioenergetic model; and (3) a size-based prey choice model from a diet analysis. Our models indicated that prey choice and consumption reflected seasonal changes in leopard seal population size and structure, size-selective predation and prey vulnerability. A population of 104 (90-125) leopard seals, of which 64% were juveniles, consumed less than 2% of the Antarctic fur seal pup production of the area (50% of total ingested energy, IE), but ca. 12-16% of the local gentoo penguin population (20% IE). Antarctic krill (28% IE) were the only observed food of leopard seal pups and supplemented the diet of older individuals. Direct impacts on krill and fish were negligible, but the "escapement" due to leopard seal predation on fur seal pups and penguins could be significant for the mackerel icefish fishery at South Georgia. These results suggest that: (1) rare apex predators like leopard seals may control, and may depend on, populations of mesopredators dependent on prey species targeted by fisheries; and (2) predatory impacts and community control may vary throughout the predator's geographic range, and differ across ecosystems and management areas, depending on the seasonal abundance of the prey and the predator's dispersal movements. This understanding is important to integrate the predator needs as natural mortality of its prey in models to set prey catch limits for fisheries. Reliable estimates of the variability of these needs are essential for a precautionary interpretation in the context of an ecosystem-based management. ?? 2009 Elsevier B.V.

Ecological Modelling↗
USGS1994

Sources of trends in water-quality data for selected streams in Texas, 1975-89 water years

Sources of trends in water-quality data for selected streams in Texas for the 1975-89 water years were investigated in this study. The investigation of sources was confined to distinct geographic patterns in the trend indicators for one constituent or for a group of related constituents. The probable source of trend patterns in nutrients and measures of oxygen in the Trinity River Basin was changes in the wastewater treatment facilities in the Dallas-Fort Worth metropolitan area. A pattern of increased concentrations of inorganic constituents in the upper Colorado River Basin resulted from emergency releases of water from the Natural Darn Lake, a salinity control structure. Trend patterns in inorganic constituents in the Rio Grande Basin were a result of increasing concentrations in the Pecos River and, to a lesser extent, the Rio Grande above the Amistad Reservoir, combined with the effects of reservoir regulation. A pattern of increasing concentrations of organic plus ammonia nitrogen and ammonia nitrogen was detected for the 1975-86 water years for stations with low concentrations (generally less than 5 milligrams per liter) of these nitrogen species. The trends were no longer evident when the period of trend analysis was extended to the 1989 water year. A positive bias in the data caused by the addition of mercuric chloride tablets to preserve nutrient samples during 1980-86 was the probable source of this trend pattern. A pattern of increasing concentrations in dissolved sulfate in the eastern part of the State was a result of a positive bias in the analytical results of a turbidimetric method of sulfate analysis. The source of a statewide pattern of increased pH in streams could not be identified.

Texas↗
USGS2008

A simulation model for projecting changes in salinity concentrations and species dominance in the coastal margin habitats of the Everglades

Sharp boundaries typically separate the salinity tolerant mangroves from the salinity intolerant hardwood hammock species, which occupy the similar geographical areas of southern Florida. Evidence of strong feedback between tree community-type and the salinity of the unsaturated (vadose) zone of the soil suggests that a severe disturbance that significantly tilts the salinity in the vadose zone might cause a shift from one vegetation type to the other. In this study, a model based upon the feedback dynamics between vegetation and salinity of the vadose zone of the soil was used to take account of storm surge events to investigate the mechanisms that by which this large-scale disturbance could affect the spatial pattern of hardwood hammocks and mangroves. Model simulation results indicated that a heavy storm surge that completely saturated the vadose zone at 30 ppt for 1 day could lead to a regime shift in which there is domination by mangroves of areas previously dominated by hardwood hammocks. Lighter storm surges that saturated the vadose zone at less than 7 ppt did not cause vegetation shifts. Investigations of model sensitivity analysis indicated that the thickness of the vadose zone, coupled with precipitation, influenced the residence time of high salinity in the vadose zone and therefore determined the rate of mangrove domination. The model was developed for a southern Florida coastal ecosystem, but its applicability may be much broader. ?? 2008 Elsevier B.V. All rights reserved.

Ecological Modelling↗
USGS2010

Flood-frequency estimates for streams on Kauai, Oahu, Molokai, Maui, and Hawaii, State of Hawaii

This study provides an updated analysis of the magnitude and frequency of peak stream discharges in Hawai`i. Annual peak-discharge data collected by the U.S. Geological Survey during and before water year 2008 (ending September 30, 2008) at stream-gaging stations were analyzed. The existing generalized-skew value for the State of Hawai`i was retained, although three methods were used to evaluate whether an update was needed. Regional regression equations were developed for peak discharges with 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals for unregulated streams (those for which peak discharges are not affected to a large extent by upstream reservoirs, dams, diversions, or other structures) in areas with less than 20 percent combined medium- and high-intensity development on Kaua`i, O`ahu, Moloka`i, Maui, and Hawai`i. The generalized-least-squares (GLS) regression equations relate peak stream discharge to quantified basin characteristics (for example, drainage-basin area and mean annual rainfall) that were determined using geographic information system (GIS) methods. Each of the islands of Kaua`i,O`ahu, Moloka`i, Maui, and Hawai`i was divided into two regions, generally corresponding to a wet region and a dry region. Unique peak-discharge regression equations were developed for each region. The regression equations developed for this study have standard errors of prediction ranging from 16 to 620 percent. Standard errors of prediction are greatest for regression equations developed for leeward Moloka`i and southern Hawai`i. In general, estimated 100-year peak discharges from this study are lower than those from previous studies, which may reflect the longer periods of record used in this study. Each regression equation is valid within the range of values of the explanatory variables used to develop the equation. The regression equations were developed using peak-discharge data from streams that are mainly unregulated, and they should not be used to estimate peak discharges in regulated streams. Use of a regression equation beyond its limits will produce peak-discharge estimates with unknown error and should therefore be avoided. Improved estimates of the magnitude and frequency of peak discharges in Hawai`i will require continued operation of existing stream-gaging stations and operation of additional gaging stations for areas such as Moloka`i and Hawai`i, where limited stream-gaging data are available.

Hawaii↗
USGS2013

Using landscape epidemiological models to understand the distribution of chronic wasting disease in the Midwestern USA

Animal movement across the landscape plays a critical role in the ecology of infectious wildlife diseases. Dispersing animals can spread pathogens between infected areas and naïve populations. While tracking free-ranging animals over the geographic scales relevant to landscape-level disease management is challenging, landscape features that influence gene flow among wildlife populations may also influence the contact rates and disease spread between populations. We used spatial diffusion and barriers to white-tailed deer gene flow, identified through landscape genetics, to model the distribution of chronic wasting disease (CWD) in the infected region of southern Wisconsin and northern Illinois, USA. Our generalized linear model showed that risk of CWD infection declined exponentially with distance from current outbreaks, and inclusion of gene flow barriers dramatically improved fit and predictive power of the model. Our results indicate that CWD is spreading across the Midwestern landscape from these two endemic foci, but spread is strongly influenced by highways and rivers that also reduce deer gene flow. We used our model to plot a risk map, providing important information for CWD management by identifying likely routes of disease spread and providing a tool for prioritizing disease monitoring and containment efforts. The current analysis may serve as a framework for modeling future disease risk drawing on genetic information to investigate barriers to spread and extending management and monitoring beyond currently affected regions.

Landscape Ecology↗
USGS1997

Activities of the National Water-Quality Assessment Program in the upper Snake River Basin, Idaho and western Wyoming, 1991-2001

In 1991, the U.S. Geological Survey (USGS) began a full-scale National Water-Quality Assessment (NAWQA) Program. The long-term goals of the NAWQA Program are to describe the status and trends in the water quality of a large part of the Nation's rivers and aquifers and to improve understanding of the primary natural and human factors that affect water-quality conditions. In meeting these goals, the program will produce water-quality, ecological, and geographic information that will be useful to policy makers and managers at the national, State, and local levels. A major component of the program is study-unit investigations, upon which national-level assessment activities are based. The program's 60 study-unit investigations are associated with principal river basins and aquifer systems throughout the Nation. Study units encompass areas from 1,200 to more than 65,000 mi2 (square miles) and incorporate about 60 to 70 percent of the Nation's water use and population served by public water supply. In 1991, the upper Snake River Basin was among the first 20 NAWQA study units selected for implementation. From 1991 to 1995, a high-intensity data-collection phase of the upper Snake River Basin study unit (fig. 1) was implemented and completed. Components of this phase are described in a report by Gilliom and others (1995). In 1997, a low-intensity phase of data collection began, and work continued on data analysis, report writing, and data documentation and archiving activities that began in 1996. Principal data-collection activities during the low-intensity phase will include monitoring of surface-water and ground-water quality, assessment of aquatic biological conditions, and continued compilation of environmental setting information.

Wyoming↗
USGS2024

The addition of 144Nd atomic mass to routine ICP-MS analysis as a Quick Screening Tool for Approximating Rare Earth Elements (Q-STAR) in natural waters

Rare earth elements (REEs) are a class of critical minerals, all of which can have supply chain vulnerability that impacts economic security. These elements are widely measured in environmental matrices via inductively coupled plasma mass spectrometry (ICP-MS); however, successful quantification can require time-consuming, sample-specific optimization. While a sample-by-sample approach is appropriate for targeted quantification studies, this approach is not suitable for mineral exploration efforts where rapidly screening thousands of samples for the presence of REEs is desired. Here, we demonstrated the use of a Quick Screening Tool for Approximating REEs (Q-STAR) to detect REEs in surface water and groundwater matrices, collected as part of existing environmental studies. A mass-to-charge ratio of 144 ( m / z = 144) was added to an ICP-MS method to screen for REEs in filtered water samples submitted for metals analyses to the U.S. Geological Survey (USGS) National Water Quality Laboratory. We detected the presence of REEs above a reference threshold of 1200 counts per second in 18 % of pre-selected 6626 samples. Using this screened dataset, we mapped estimated dissolved REE concentrations across the United States in relation to ecoregions and underlying geology. Data are constrained to where sample collection took place but nevertheless show estimated aqueous dissolved REE concentrations on a geographic scale that has not yet been studied. To validate Q-STAR, REEs were measured in a USGS standard reference sample, a subset of 88 archived filtered water samples, and in fresh filtered surface water samples. Our targeted analyses demonstrated a strong linear relationship between Q-STAR predicted and measured values in all archived samples for Nd (r 2 = 0.94), and light REEs (LREEs) such as lanthanum (La) (r 2 = 0.93), praseodymium (Pr) (r 2 = 0.94) and samarium (Sm) (r 2 = 0.94). Using Q-STAR screen values, nine field sites were identified and surface water samples recollected to confirm the continued presence of Nd and LREEs. Q-STAR can be used to screen an unlimited number of water samples for the presence of REEs prior to time-intensive and costly quantitative analyses and to generate large REE datasets for further investigation.

Journal of Geochemical Exploration↗
USGS1999

Use of historical and geospatial data to guide the restoration of a Lake Erie coastal marsh

Historical and geospatial data were used to identify the relationships between water levels, wetland vegetation, littoral drift of sediments, and the condition of a protective barrier beach at Metzger Marsh, a coastal wetland in western Lake Erie, to enhance and guide a joint federal and state wetland restoration project. Eleven sets of large-scale aerial photographs dating from 1940 through 1994 were interpreted to delineate major vegetation types and boundaries of the barrier beach. A geographic information system (GIS) was then used to digitize the data and calculate the vegetated area and length of barrier beach. Supplemented by paleoecological and sedimentological analyses, aerial photographic interpretation revealed that Metzger Marsh was once a drowned-river-mouth wetland dominated by sedges and protected by a sand barrier beach. Extremely high water levels, storm events, and reduction of sediments in the littoral drift contributed to the complete destruction of the barrier beach in 1973 and prevented its recovery. The extent of wetland vegetation, correlated to water levels and condition of the barrier beach, decreased from a high of 108 ha in 1940 to a low of 33 ha in 1994. The lack of an adequate sediment supply and low probability of a period of extremely low lake levels in the near future made natural reestablishment of the barrier beach and wetland vegetation unlikely. Therefore, the federal and state managers chose to construct a dike to replace the protective barrier beach. Recommendations stemming from this historical analysis, however, resulted in the incorporation of a water-control structure in the dike that will retain a hydrologic connection between wetland and lake. Management of the wetland will seek to mimic processes natural to the wetland type identified by this analysis.

Wetlands↗
USGS1995

Synthesis of nutrient and sediment data for watersheds within the Chesapeake Bay drainage basin

Nutrient and sediment data collected by Federal and state agencies from 1972 through 1992 at 1,058 surface-water sites in nontidal parts of the Chesapeake Bay Basin were compiled into a large database. Adequate nutrient, sediment, and streamflow data were not available to compute annual loads for all sites because water-quality monitoring at many of the sites was either short term or noncontinuous or because stream-flow was not measured. Annual nutrient and sediment loads were calculated at a total of 127 sites. Annual loads of dissolved nitrate were calculated for 108 sites, but total nitrogen loads could be calculated for only 48 of these sites because ammonia plus organic nitrogen data were not available for many of these 108 sites. Annual loads of total phosphorus were calculated for 99 sites, and annual loads of suspended sediment were calculated for 33 sites. Loads could be calculated for only a very few sites in the Juniata River Basin (a tributary to the Susquehanna River), the York River Basin, the middle and lower reaches of the James River, and the nontidal parts of the eastern shore of the Bay. Geographic Information System (GIS) spatial data sets of land use, physiographic province, rock type, and watershed delineation were compiled for the entire Chesapeake Bay Basin (approximately 64,000 square miles). The nutrient- and sediment-yield were evaluated with respect to land use, physiographic province, rock type, and hydrologic characteristics. During years that the mean streamflow was about equal to the long-term mean streamflow, the Susquehanna River contributed about 50 percent of the freshwater, 66 percent of the total nitrogen, and 40 percent of the total phosphorus transported by tributaries to the Bay. Nutrient and sediment data were available for less than 18 percent of the predominantly agricultural areas underlain by siliciclastic rock and for less than 35 percent of the predominantly agricultural areas underlain by either carbonate rock or unconsolidated rock. Nutrient and sediment data were available for about 91 percent of the predominantly forested areas underlain by siliciclastic rock. Spatial and temporal gaps in the water-quality data and GIs data sets limited some data analysis. Correlations of annual yields or nutrients and sediment with respect to land use, physiographic province, and rock type indicated (1) basins with larger percentages of agricultural land had larger nutrient and sediment yields, (2) basins with larger percentages of forest land had smaller nutrient and sediment loads, (3) the largest total nitrogen yields were from agricultural basins underlain by carbonate rock, (4) yields or nutrients from urban basins were substantially less than yields from agricultural basins, and (5) basins with small amounts of agricultural and urban land had relatively small nutrient and sediment yields.

Chesapeake Bay drainage basin↗
USGS2009

Geospatial data to support analysis of water-quality conditions in basin-fill aquifers in the southwestern United States

The Southwest Principal Aquifers study area consists of most of California and Nevada and parts of Utah, Arizona, New Mexico, and Colorado; it is about 409,000 square miles. The Basin-fill aquifers extend through about 201,000 square miles of the study area and are the primary source of water for cities and agricultural communities in basins in the arid and semiarid southwestern United States (Southwest). The demand on limited ground-water resources in areas in the southwestern United States has increased significantly. This increased demand underscores the importance of understanding factors that affect the water quality in basin-fill aquifers in the region, which are being studied through the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) program. As a part of this study, spatial datasets of natural and anthropogenic factors that may affect ground-water quality of the basin-fill aquifers in the southwestern United States were developed. These data include physical characteristics of the region, such as geology, elevation, and precipitation, as well as anthropogenic factors, including population, land use, and water use. Spatial statistics for the alluvial basins in the Southwest have been calculated using the datasets. This information provides a foundation for the development of conceptual and statistical models that relate natural and anthropogenic factors to ground-water quality across the Southwest. A geographic information system (GIS) was used to determine and illustrate the spatial distribution of these basin-fill variables across the region. One hundred-meter resolution raster data layers that represent the spatial characteristics of the basins' boundaries, drainage areas, population densities, land use, and water use were developed for the entire Southwest.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2023

User’s Guide to planetary image analysis and geologic mapping in ArcGIS Pro

Geologic maps are valuable tools in planetary science. Though planetary geologic maps are similar to terrestrial (Earthbased) geologic maps, the nature of planetary exploration introduces unique challenges for geologic mappers. Terrestrial geologic mappers prepare products from field-based observation, often comparing or refining those with aerial and (or) orbital images. Planetary geologic mapping relies almost exclusively on remote observations, which are made by orbiting spacecraft. Therefore, with a few exceptions for locations with rovers, landers, or crewed surface missions, planetary geologic mappers are not able to observe their map area in detail or at smaller scales. As a result, they must interpret and describe their map features differently than those used in terrestrial geologic maps. For example, terrestrial geologic mappers commonly divide units by lithology (rock type) or grain size. However, planetary geologic mappers often do not have detailed enough information to know what type of rock or grain size is present, and instead must divide the planet’s surface into geologic units using differences in tone, color, and surface texture (at multiple scales). Cross-cutting relationships, where apparent, can provide excellent—and often crucial—observations for identifying and subdividing geologic units using orbital datasets. The process of creating planetary maps has evolved over time, from original hand-drawn maps created during the early 1800s through the late 1900s, to the fully digital products created today. Modern-day planetary geologic mapping uses Geographic Information Systems (GIS) software and tools to visualize data, delineate units and landforms, and accurately convey spatial relationships to a map user using cartographic features represented by points, lines, and polygons. This tutorial was written to familiarize both new and experienced planetary geologic mappers with ArcGIS Pro, a commonly used GIS software package developed by Esri. This tutorial introduces new planetary geologic mappers to fundamental concepts and best practices in planetary geologic mapping. For mappers with experience using ArcMap (a previous version of ArcGIS), this tutorial will help to familiarize users with new changes in layout and functionality, so current projects may be migrated into the ArcGIS Pro environment. No prior knowledge is required, although a general familiarity with geology, GIS, and planetary science is recommended. This tutorial includes links to helpful glossaries of common GIS terms and other GIS and planetary science resources in appendix 1. For additional information on planetary geologic mapping, see the U.S Geological Survey (USGS) Astrogeology NASA Planetary Geologic Mapping Program website and the Planetary Mapping Guidelines. Numerous ArcGIS tutorials are also available from Esri’s Tutorials page, through the Esri Academy catalog, and Esri’s ArcGIS Pro Resources page.

Techniques and Methods↗
USGS2006

Variation in spring nearshore resident fish species composition and life histories in the lower San Joaquin watershed and delta

Providing freshwater to human populations while protecting or rehabilitating ecosystem health is a significant challenge to water resource managers and requires accurate knowledge of aquatic resources. Previous studies of fish assemblages in the San Francisco Estuary and watershed have focused on specific habitat types, water bodies, or geographic subregions. In this study, we use seining data from two monitoring programs to provide an integrated view of spring nearshore resident fish species composition and life history characteristics in five regions: the San Joaquin River, the upper Sacramento River, the lower Sacramento River, the northern Sacramento-San Joaquin Delta (North Delta), and the Interior Delta. Data for the period March-May from 1994 to 2002, showed that spring species composition of the San Joaquin River was very different from the other four regions. Total catch in the San Joaquin River was dominated by small, short-lived batch spawning alien species (93%), particularly red shiner Cyprinella lutrensis (>75% of total catch). The upper and lower Sacramento River were very similar in species composition and life history characteristics and less dominated by alien fish (<45% of total catch). Ordination of species percentage abundances by non–metric multidimensional scaling confirmed that the major gradient was from assemblages dominated by native species to assemblages dominated by alien species. Two-way analysis of variance of ordination scores indicated that spatial variability was more important than annual variability in explaining patterns in species composition. The potential benefits of San Joaquin River native fish restoration appear high because there is so much potential for improvement; however, it is unclear how to best manipulate the system to achieve such restoration. Addressing such uncertainties is necessary if society desires the reservation and restoration of native biodiversity as human demands on water resources increase.

California↗
USGS2011

Assessing forest vulnerability and the potential distribution of pine beetles under current and future climate scenarios in the Interior West of the US

The aim of our study was to estimate forest vulnerability and potential distribution of three bark beetles (Curculionidae: Scolytinae) under current and projected climate conditions for 2020 and 2050. Our study focused on the mountain pine beetle ( Dendroctonus ponderosae ), western pine beetle ( Dendroctonus brevicomis ), and pine engraver ( Ips pini) . This study was conducted across eight states in the Interior West of the US covering approximately 2.2 million km 2 and encompassing about 95% of the Rocky Mountains in the contiguous US. Our analyses relied on aerial surveys of bark beetle outbreaks that occurred between 1991 and 2008. Occurrence points for each species were generated within polygons created from the aerial surveys. Current and projected climate scenarios were acquired from the WorldClim database and represented by 19 bioclimatic variables. We used Maxent modeling technique fit with occurrence points and current climate data to model potential beetle distributions and forest vulnerability. Three available climate models, each having two emission scenarios, were modeled independently and results averaged to produce two predictions for 2020 and two predictions for 2050 for each analysis. Environmental parameters defined by current climate models were then used to predict conditions under future climate scenarios, and changes in different species’ ranges were calculated. Our results suggested that the potential distribution for bark beetles under current climate conditions is extensive, which coincides with infestation trends observed in the last decade. Our results predicted that suitable habitats for the mountain pine beetle and pine engraver beetle will stabilize or decrease under future climate conditions, while habitat for the western pine beetle will continue to increase over time. The greatest increase in habitat area was for the western pine beetle, where one climate model predicted a 27% increase by 2050. In contrast, the predicted habitat of the mountain pine beetle from another climate model suggested a decrease in habitat areas as great as 46% by 2050. Generally, 2020 and 2050 models that tested the three climate scenarios independently had similar trends, though one climate scenario for the western pine beetle produced contrasting results. Ranges for all three species of bark beetles shifted considerably geographically suggesting that some host species may become more vulnerable to beetle attack in the future, while others may have a reduced risk over time.

Arizona, Colorado, Idaho, Montana, New Mexico, Nev↗
USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Katawas mineral district in Afghanistan: Chapter N 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 Katawas mineral district, which has 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 (©AXA, 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 Katawas) and the WGS84 datum. The final image mosaics 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 Katawas study area, one subarea was designated for detailed field investigation (that is, the Gold subarea); this subarea was extracted from the area's image mosaic and is provided as a separate embedded geotiff image.

Katawas Mineral District↗
USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nuristan 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 Nuristan mineral district, which has gem, lithium, and cesium deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. All available panchromatic images for this area had significant cloud and snow cover that precluded their use for resolution enhancement of the multispectral image data. Each of the four-band images within the 10-m 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 Nuristan) and the WGS84 datum. The final image mosaics for the Nuristan 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↗
USGS2011

Forecasting carbon budget under climate change and CO2 fertilization for subtropical region in China using integrated biosphere simulator (IBIS) model

The regional carbon budget of the climatic transition zone may be very sensitive to climate change and increasing atmospheric CO2 concentrations. This study simulated the carbon cycles under these changes using process-based ecosystem models. The Integrated Biosphere Simulator (IBIS), a Dynamic Global Vegetation Model (DGVM), was used to evaluate the impacts of climate change and CO2 fertilization on net primary production (NPP), net ecosystem production (NEP), and the vegetation structure of terrestrial ecosystems in Zhejiang province (area 101,800 km2, mainly covered by subtropical evergreen forest and warm-temperate evergreen broadleaf forest) which is located in the subtropical climate area of China. Two general circulation models (HADCM3 and CGCM3) representing four IPCC climate change scenarios (HC3AA, HC3GG, CGCM-sresa2, and CGCM-sresb1) were used as climate inputs for IBIS. Results show that simulated historical biomass and NPP are consistent with field and other modelled data, which makes the analysis of future carbon budget reliable. The results indicate that NPP over the entire Zhejiang province was about 55 Mt C yr-1 during the last half of the 21st century. An NPP increase of about 24 Mt C by the end of the 21st century was estimated with the combined effects of increasing CO2 and climate change. A slight NPP increase of about 5 Mt C was estimated under the climate change alone scenario. Forests in Zhejiang are currently acting as a carbon sink with an average NEP of about 2.5 Mt C yr-1. NEP will increase to about 5 Mt C yr-1 by the end of the 21st century with the increasing atmospheric CO2 concentration and climate change. However, climate change alone will reduce the forest carbon sequestration of Zhejiang's forests. Future climate warming will substantially change the vegetation cover types; warm-temperate evergreen broadleaf forest will be gradually substituted by subtropical evergreen forest. An increasing CO2 concentration will have little contribution to vegetation changes. Simulated NPP shows geographic patterns consistent with temperature to a certain extent, and precipitation is not the limiting factor for forest NPP in the subtropical climate conditions. There is no close relationship between the spatial pattern of NEP and climate condition.

Polish Journal of Ecology↗
USGS2024

Applying mark-resight, count, and telemetry data to estimate effective sampling area and fish density with stationary underwater cameras

Accurate estimates of abundance and density for geographically open populations must account for the effective sampling area (ESA) of sampling gears. We describe a Marked N-Mixture model to estimate ESA and density (number of individuals/unit area) from repeated counts of unmarked and marked individuals, integrating mark-resight, camera counts, and telemetry data of red snapper ( Lutjanus campechanus ) at a 1.6 km 2 reef off North Carolina, USA. Cameras recorded observations of unmarked and marked individuals, whereas telemetry data indicated the number of tagged fish present on the reef. We estimated density (95 individuals/km 2 , 95%CI: 58–149), ESA (which was lower when current direction was towards the camera), detection probability (0.06, 95%CI: 0.03–0.09), and covariate relationships. Simulation studies under different scenarios of data quality and space use identified positive bias in density estimates from N-mixture models due to fish movement. In contrast, the Marked N-Mixture model returned unbiased estimates of density, ESA, and detection parameters, and appears to be a more robust method for modeling density given the data available for this analysis. This approach can be applied to other populations where count and telemetry data overlap in space and time.

North Carolina↗