Geology Reports⌕ Search

SEARCH · Geology Reports

Results for “Data”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,261 records · Page 70Linked to original sources
USGS2005

Application of flowmeter and depth-dependent water quality data for improved production well construction

Ground water production wells commonly are designed to maximize well yield and, therefore, may be screened over several water-bearing zones. These water-bearing zones usually are identified, and their hydrogeologic characteristics and water quality are inferred, on the basis of indirect data such as geologic and geophysical logs. Production well designs based on these data may result in wells that are drilled deeper than necessary and are screened through zones having low permeability or poor-quality ground water. In this study, we examined the application of flowmeter logging and depth-dependent water quality samples for the improved design of production wells in a complex hydrogeologic setting. As a demonstration of these techniques, a flowmeter log and depth-dependent water quality data were collected from a long-screened production well within a multilayered coastal aquifer system in the Santa Clara-Calleguas Basin, Ventura County, California. Results showed that the well yields most of its water from four zones that constitute 58% of the screened interval. The importance of these zones to well yield was not readily discernible from indirect geologic or geophysical data. The flowmeter logs and downhole water quality data also show that small quantities of poor-quality water could degrade the overall quality of water from the well. The data obtained from one well can be applied to other proposed wells in the same hydrologic basin. The application of flowmeter and depth-dependent water quality data to well design can reduce installation costs and improve the quantity and quality of water produced from wells in complex multiple-aquifer systems.

Ground Water↗
USGS2014

Past, present, and future of water data delivery from the U.S. Geological Survey

We present an overview of national water databases managed by the U.S. Geological Survey, including surface-water, groundwater, water-quality, and water-use data. These are readily accessible to users through web interfaces and data services. Multiple perspectives of data are provided, including search and retrieval of real-time data and historical data, on-demand current conditions and alert services, data compilations, spatial representations, analytical products, and availability of data across multiple agencies.

Journal of Contemporary Water Research and Educati↗
USGS2012

Likelihood analysis of species occurrence probability from presence-only data for modelling species distributions

1. Understanding the factors affecting species occurrence is a pre-eminent focus of applied ecological research. However, direct information about species occurrence is lacking for many species. Instead, researchers sometimes have to rely on so-called presence-only data (i.e. when no direct information about absences is available), which often results from opportunistic, unstructured sampling. MAXENT is a widely used software program designed to model and map species distribution using presence-only data. 2. We provide a critical review of MAXENT as applied to species distribution modelling and discuss how it can lead to inferential errors. A chief concern is that MAXENT produces a number of poorly defined indices that are not directly related to the actual parameter of interest – the probability of occurrence ( ψ ). This focus on an index was motivated by the belief that it is not possible to estimate ψ from presence-only data; however, we demonstrate that ψ is identifiable using conventional likelihood methods under the assumptions of random sampling and constant probability of species detection. 3. The model is implemented in a convenient r package which we use to apply the model to simulated data and data from the North American Breeding Bird Survey. We demonstrate that MAXENT produces extreme under-predictions when compared to estimates produced by logistic regression which uses the full (presence/absence) data set. We note that MAXENT predictions are extremely sensitive to specification of the background prevalence, which is not objectively estimated using the MAXENT method. 4. As with MAXENT, formal model-based inference requires a random sample of presence locations. Many presence-only data sets, such as those based on museum records and herbarium collections, may not satisfy this assumption. However, when sampling is random, we believe that inference should be based on formal methods that facilitate inference about interpretable ecological quantities instead of vaguely defined indices.

Methods in Ecology and Evolution↗
USGS2011

Mapping rice areas of South Asia using MODIS multitemporal data

Our goal is to map the rice areas of six South Asian countries using moderate-resolution imaging spectroradiometer (MODIS) time-series data for the time period 2000 to 2001. South Asia accounts for almost 40% of the world's harvested rice area and is also home to 74% of the population that lives on less than $2.00 a day. The population of the region is growing faster than its ability to produce rice. Thus, accurate and timely assessment of where and how rice is cultivated is important to craft food security and poverty alleviation strategies. We used a time series of eight-day, 500-m spatial resolution composite images from the MODIS sensor to produce rice maps and rice characteristics (e.g., intensity of cropping, cropping calendar) taking data for the years 2000 to 2001 and by adopting a suite of methods that include spectral matching techniques, decision trees, and ideal temporal profile data banks to rapidly identify and classify rice areas over large spatial extents. These methods are used in conjunction with ancillary spatial data sets (e.g., elevation, precipitation), national statistics, and maps, and a large volume of field-plot data. The resulting rice maps and statistics are compared against a subset of independent field-plot points and the best available subnational statistics on rice areas for the main crop growing season (kharif season). A fuzzy classification accuracy assessment for the 2000 to 2001 rice-map product, based on field-plot data, demonstrated accuracies from 67% to 100% for individual rice classes, with an overall accuracy of 80% for all classes. Most of the mixing was within rice classes. The derived physical rice area was highly correlated with the subnational statistics with R 2 values of 97% at the district level and 99% at the state level for 2000 to 2001. These results suggest that the methods, approaches, algorithms, and data sets we used are ideal for rapid, accurate, and large-scale mapping of paddy rice as well as for generating their statistics over large areas.

South Asia↗
USGS2002

Archiving, processing, and disseminating ASTER products at the USGS EROS Data Center

The U.S. Geological Survey EROS Data Center archives, processes, and disseminates Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data products. The ASTER instrument is one of five sensors onboard the Earth Observing System's Terra satellite launched December 18, 1999. ASTER collects broad spectral coverage with high spatial resolution at near infrared, shortwave infrared, and thermal infrared wavelengths with ground resolutions of 15, 30, and 90 meters, respectively. The ASTER data are used in many ways to understand local and regional earth-surface processes. Applications include land-surface climatology, volcanology, hazards monitoring, geology, agronomy, land cover change, and hydrology. The ASTER data are available for purchase from the ASTER Ground Data System in Japan and from the Land Processes Distributed Active Archive Center in the United States, which receives level 1A and level 1B data from Japan on a routine basis. These products are archived and made available to the public within 48 hours of receipt. The level 1A and level 1B data are used to generate higher level products that include routine and on-demand decorrelation stretch, brightness temperature at the sensor, emissivity, surface reflectance, surface kinetic temperature, surface radiance, polar surface and cloud classification, and digital elevation models. This paper describes the processes and procedures used to archive, process, and disseminate standard and on-demand higher level ASTER products at the Land Processes Distributed Active Archive Center.

Conference Paper↗
USGS2005

Sharpening advanced land imager multispectral data using a sensor model

The Advanced Land Imager (ALI) instrument on NASA's Earth Observing One (EO-1) satellite provides for nine spectral bands at 30m ground sample distance (GSD) and a 10m GSD panchromatic band. This report describes an image sharpening technique where the higher spatial resolution information of the panchromatic band is used to increase the spatial resolution of ALI multispectral (MS) data. To preserve the spectral characteristics, this technique combines reported deconvolution deblurring methods for the MS data with highpass filter-based fusion methods for the Pan data. The deblurring process uses the point spread function (PSF) model of the ALI sensor. Information includes calculation of the PSF from pre-launch calibration data. Performance was evaluated using simulated ALI MS data generated by degrading the spatial resolution of high resolution IKONOS satellite MS data. A quantitative measure of performance was the error between sharpened MS data and high resolution reference. This report also compares performance with that of a reported method that includes PSF information. Preliminary results indicate improved sharpening with the method reported here.

Conference Paper↗
USGS2020

Three-dimensional shape and structure of the Susitna basin, south-central Alaska, from geophysical data

We use gravity, magnetic, seismic reflection, well, and outcrop data to determine the three-dimensional shape and structural features of south-central Alaska’s Susitna basin. This basin is located within the Aleutian-Alaskan convergent margin region and is expected to show effects of regional subduction zone processes. Aeromagnetic data, when filtered to highlight anomalies associated with sources within the upper few kilometers, show numerous linear northeast-trending highs and some linear north-trending highs. Comparisons to seismic reflection and well data show that these highs correspond to areas where late Paleocene to early Eocene volcanic layers have been locally uplifted due to folding and/or faulting. The combined magnetic and seismic reflection data suggest that the linear highs represent northeast-trending folds and north-striking faults. Several lines of evidence suggest that the northeast-trending folds formed during the middle Eocene to early Miocene and may have continued to be active in the Pliocene. The north-striking faults, which in some areas appear to cut the northeast-trending folds, show evidence of Neogene and probable modern movement. Gravity data facilitate estimates of the shape and depth of the basin. This was accomplished by separating the observed gravity anomaly into two components—one representing low-density sedimentary fill within the basin and one representing density heterogeneities within the underlying crystalline basement. We then used the basin anomaly, seismic reflection data, and well data to estimate the depth of the basin. Together, the magnetic, gravity, and reflection seismic analyses reveal an asymmetric basin comprising sedimentary rock over 4 km thick with steep, fault-bounded sides to the southwest, west, and north and a mostly gentle rise toward the east. Relations to the broader tectonic regime are suggested by fold axis orientations within the Susitna basin and neighboring Cook Inlet basin, which are roughly parallel to the easternmost part of the Alaska-Aleutian trench and associated Wadati-Benioff zone as it trends from northeast to north-northeast to northeast. An alignment between forearc basin folds and the subduction zone trench has been observed at other convergent margins, attributed to strain partitioning generated by regional rheologic variations that are associated with the subducting plate and arc magmatism. The asymmetric shape of the basin, especially its gentle rise to the east, may reflect uplift associated with flat-slab subduction of the Yakutat microplate, consistent with previous work that suggested Yakutat influence on the nearby Talkeetna Mountains and western Alaska Range. Yakutat subduction may also have contributed to Neogene and later reverse slip along north-striking faults within the Susitna basin.

Alaska↗
USGS2001

Assessing large-scale surveyor variability in the historic forest data of the original U.S. Public Land Survey

The U.S. General Land Office Public Land Survey (PLS) records are a valuable resource for studying pre-European settlement vegetation. However, these data were taken for legal, not ecological, purposes. In turn, the instructions the surveyors followed affected the data collected. For this reason, it has been suggested that the PLS data may not truly represent the surveyed landscapes. This study examined the PLS data of northern Wisconsin, U.S.A., to determine the extent of variability among surveyors. We statistically tested for differences among surveyors in recorded tree species, size, location, and distance from the survey point. While we cannot rule out effects from other influences (e.g., environmental factors), we found evidence suggesting some level of surveyor bias for four of five variables, including tree species and size. The PLS data remain one of the best records of pre-European settlement vegetation available. However, based on our findings, we recommend that projects using PLS records examine these data carefully. This assessment should include not only the choice of variables to be studied but also the spatial extent at which the data will be examined.

Canadian Journal of Forest Research↗
USGS1993

The use of NOAA AVHRR data for assessment of the urban heat sland effect

A vegetation index and a radiative surface temperature were derived from satellite data acquired at approximately 1330 LST for each of 37 cities and for their respective nearby rural regions from 28 June through 8 August 1991. Urban–rural differences for the vegetation index and the surface temperatures were computed and then compared to observed urban–rural differences in minimum air temperatures. The purpose of these comparisons was to evaluate the use of satellite data to assess the influence of the urban environment on observed minimum air temperatures (the urban heat island effect). The temporal consistency of the data, from daily data to weekly, biweekly, and monthly intervals, was also evaluated. The satellite-derived normalized difference (ND) vegetation-index data, sampled over urban and rural regions composed of a variety of land surface environments, were linearly related to the difference in observed urban and rural minimum temperatures. The relationship between the ND index and observed differences in minimum temperature was improved when analyses were restricted by elevation differences between the sample locations and when biweekly or monthly intervals were utilized. The difference in the ND index between urban and rural regions appears to be an indicator of the difference in surface properties (evaporation and heat storage capacity) between the two environments that are responsible for differences in urban and rural minimum temperatures. The urban and rural differences in the ND index explain a greater amount of the variation observed in minimum temperature differences than past analyses that utilized urban population data. The use of satellite data may contribute to a globally consistent method for analysis of urban heat island bias.

Journal of Applied Meteorology and Climatology↗
USGS2014

An approach for filtering hyperbolically positioned underwater acoustic telemetry data with position precision estimates

Background Telemetry systems that estimate animal positions with hyperbolic positioning algorithms also provide a technology-specific estimate of position precision (e.g., horizontal position error (HPE) for the VEMCO positioning system). Position precision estimates (e.g., dilution of precision for a global positioning system (GPS)) have been used extensively to identify and remove positions with unacceptable measurement error in studies of terrestrial and surfacing aquatic animals such as turtles and seals. Few underwater acoustic telemetry studies report using position precision estimates to filter data in accordance with explicit data quality objectives because the relationship between the precision estimate and measurement error is not understood or not evaluated. A four-step filtering approach which incorporates data-filtering principles developed for GPS tracking of terrestrial animals is demonstrated. HPE was evaluated for its effectiveness to remove uncertain fish positions acquired from a new underwater fine-scale passive acoustic monitoring system. Results Four filtering objectives were identified based on the need for three sequential future analyses and four data quality criteria were developed for evaluating the performance of individual filters (step 1). The unfiltered, baseline position confidence from known-position test tags was considered to determine if filtering was necessary (step 2). An HPE filter cutoff of 8 was selected to meet the four criteria (step 3), and it was determined that one analysis may need to be adjusted for use with this dataset. The data quality objectives, criteria, and filter selection rationale were reported (step 4). Conclusions The use of position precision estimates that reflect the confidence in the positioning process should be considered prior to the use of biological filters that rely on a priori expectations of the subject’s movement capacities and tendencies. Position confidence goals should be determined based upon the needs of the research questions and analysis requirements versus arbitrary selection, in which filters of previous studies are adopted. Data filtering with this approach ensures that data quality is sufficient for the selected analyses and presents the opportunity to adjust or identify a different analysis in the event that the requisite precision was not attained. Ignoring these steps puts a practitioner at risk of reporting errant findings.

Animal Biotelemetry↗
USGS2013

Expression of terrain and surface geology in high-resolution helicopter-borne gravity gradient (AGG) data: examples from Great Sand Dunes National Park, Rio Grande Rift, Colorado

Airborne gravity gradient (AGG) data are rapidly becoming standard components of geophysical mapping programs, due to their advantages in cost, access, and resolution advantages over measurements of the gravity field on the ground. Unlike conventional techniques that measure the gravity field, AGG methods measure derivatives of the gravity field. This means that effects of terrain and near-surface geology are amplified in AGG data, and that proper terrain corrections are critically important for AGG data processing. However, terrain corrections require reasonable estimates of density for the rocks and sediments that make up the terrain. A recommended philosophical approach is to use the terrain and surface geology, with their strong expression in AGG data, to the interpreter’s advantage. An example of such an approach is presented here for an area with very difficult ground access and little ground gravity data. Nettleton-style profiling is used with AGG data to estimate the densities of the sand dunefield and adjacent Precambrian rocks from the area of Great Sand Dunes National Park in southern Colorado. Processing of the AGG data using the density estimate for the dunefield allows buried structures, including a hypothesized buried basement bench, to be mapped beneath the sand dunes.

Colorado↗
USGS2018

Combining multiple sources of data to inform conservation of Lesser Prairie-Chicken populations

Conservation of small populations is often based on limited data from spatially and temporally restricted studies, resulting in management actions based on an incomplete assessment of the population drivers. If fluctuations in abundance are related to changes in weather, proper management is especially important, because extreme weather events could disproportionately affect population abundance. Conservation assessments, especially for vulnerable populations, are aided by a knowledge of how extreme events influence population status and trends. Although important for conservation efforts, data may be limited for small or vulnerable populations. Integrated population models maximize information from various sources of data to yield population estimates that fully incorporate uncertainty from multiple data sources while allowing for the explicit incorporation of environmental covariates of interest. Our goal was to assess the relative influence of population drivers for the Lesser Prairie-Chicken ( Tympanuchus pallidicinctus ) in the core of its range, western and southern Kansas, USA. We used data from roadside lek count surveys, nest monitoring surveys, and survival data from telemetry monitoring combined with climate (Palmer drought severity index) data in an integrated population model. Our results indicate that variability in population growth rate was most influenced by variability in juvenile survival. The Palmer drought severity index had no measurable direct effects on adult survival or mean number of offspring per female; however, there were declines in population growth rate following severe drought. Because declines in population growth rate occurred at a broad spatial scale, declines in response to drought were likely due to decreases in chick and juvenile survival rather than emigration outside of the study area. Overall, our model highlights the importance of accounting for environmental and demographic sources of variability, and provides a thorough method for simultaneously evaluating population demography in response to long-term climate effects.

The Auk↗
USGS2018

Mapping wildfire burn severity in the Arctic Tundra from downsampled MODIS data

Wildfires are historically infrequent in the arctic tundra, but are projected to increase with climate warming. Fire effects on tundra ecosystems are poorly understood and difficult to quantify in a remote region where a short growing season severely limits ground data collection. Remote sensing has been widely utilized to characterize wildfire regimes, but primarily from the Landsat sensor, which has limited data acquisition in the Arctic. Here, coarse-resolution remotely sensed data are assessed as a means to quantify wildfire burn severity of the 2007 Anaktuvuk River Fire in Alaska, the largest tundra wildfire ever recorded on Alaska's North Slope. Data from Landsat Thematic Mapper (TM) and downsampled Moderate-resolution Imaging Spectroradiometer (MODIS) were processed to spectral indices and correlated to observed metrics of surface, subsurface, and comprehensive burn severity. Spectral indices were strongly correlated to surface severity (maximum R2 = 0.88) and slightly less strongly correlated to substrate severity. Downsampled MODIS data showed a decrease in severity one year post-fire, corroborating rapid vegetation regeneration observed on the burned site. These results indicate that widely-used spectral indices and downsampled coarse-resolution data provide a reasonable supplement to often-limited ground data collection for analysis and long-term monitoring of wildfire effects in arctic ecosystems.

Alaska↗
USGS2013

Rupture history of the 2008 M w 7.9 Wenchuan, China, earthquake: Evaluation of separate and joint inversions of geodetic, teleseismic, and strong-motion data

An extensive data set of teleseismic and strong-motion waveforms and geodetic offsets is used to study the rupture history of the 2008 Wenchuan, China, earthquake. A linear multiple-time-window approach is used to parameterize the rupture. Because of the complexity of the Wenchuan faulting, three separate planes are used to represent the rupturing surfaces. This earthquake clearly demonstrates the strengths and limitations of geodetic, teleseismic, and strong-motion data sets. Geodetic data (static offsets) are valuable for determining the distribution of shallower slip but are insensitive to deeper faulting and reveal nothing about the timing of slip. Teleseismic data in the distance range 30°–90° generally involve no modeling difficulties because of simple ray paths and can distinguish shallow from deep slip. Teleseismic data, however, cannot distinguish between different slip scenarios when multiple fault planes are involved because steep takeoff angles lead to ambiguity in timing. Local strong-motion data, on the other hand, are ideal for determining the direction of rupture from directivity but can easily be over modeled with inaccurate Green’s functions, leading to misinterpretation of the slip distribution. We show that all three data sets are required to give an accurate description of the Wenchuan rupture. The moment is estimated to be approximately 1.0 × 10 21 N · m with the slip characterized by multiple large patches with slips up to 10 m. Rupture initiates on the southern end of the Pengguan fault and proceeds unilaterally to the northeast. Upon reaching the cross-cutting Xiaoyudong fault, rupture of the adjacent Beichuan fault starts at this juncture and proceeds bilaterally to the northeast and southwest.

Wenchuan↗
USGS2017

Considerations in comparing the U.S. Geological Survey one‐year induced‐seismicity hazard models with “Did You Feel It?” and instrumental data

The recent steep increase in seismicity rates in Oklahoma, southern Kansas, and other parts of the central United States led the U.S. Geological Survey (USGS) to develop, for the first time, a probabilistic seismic hazard forecast for one year (2016) that incorporates induced seismicity. In this study, we explore a process to ground‐truth the hazard model by comparing it with two databases of observations: modified Mercalli intensity (MMI) data from the “Did You Feel It?” (DYFI) system and peak ground acceleration (PGA) values from instrumental data. Because the 2016 hazard model was heavily based on earthquake catalogs from 2014 to 2015, this initial comparison utilized observations from these years. Annualized exceedance rates were calculated with the DYFI and instrumental data for direct comparison with the model. These comparisons required assessment of the options for converting hazard model results and instrumental data from PGA to MMI for comparison with the DYFI data. In addition, to account for known differences that affect the comparisons, the instrumental PGA and DYFI data were declustered, and the hazard model was adjusted for local site conditions. With these adjustments, examples at sites with the most data show reasonable agreement in the exceedance rates. However, the comparisons were complicated by the spatial and temporal completeness of the instrumental and DYFI observations. Furthermore, most of the DYFI responses are in the MMI II–IV range, whereas the hazard model is oriented toward forecasts at higher ground‐motion intensities, usually above about MMI IV. Nevertheless, the study demonstrates some of the issues that arise in making these comparisons, thereby informing future efforts to ground‐truth and improve hazard modeling for induced‐seismicity applications.

Kansas, Oklahoma↗
USGS1976

Availability of Earth resources data

The purpose of this booklet is to help the reader to become aware of the volume of Earth resources data that have been collected by agencies of the United States Government and to find out where and how these data may be obtained. Earth resources data as discussed here are those obtained by remote-sensing instruments, including aerial cameras, multispectral cameras, multispectral scanners, and radar. They are obtained by spacecraft and high-altitude aircraft. Also, various agencies have been acquiring vast quantities of conventional aerial mapping photography from low and medium altitudes for more than 50 years. There is also brief information to assist the reader in locating published references and identifying research projects relating to application of Earth resources data to a variety of purposes. In all cases, it is not the intent to say what data are needed or how the data are to be used, but to describe where an interested person can begin to locate Earth resources data.

General Information Product↗
USGS1982

Water-data program of the U.S. Geological Survey

The U.S. Geological Survey is the principal Federal agency responsible for the collection of hydrologic data needed for the planning, development, use, and management of the Nation 's water resources. These data are the foundation necessary for conducting analytical and interpretive appraisals describing the occurrence and availability of surface and ground waters, and their physical, chemical, and biological characteristics. The data are likewise required for basic and problem-oriented research in hydraulics, hydrology, and related fields. Hydrologic data collection by the Geological Survey began in 1894. Current operations include about 17,000 stations for collection of river, lake, and reservoir data; about 27,000 wells for collection of ground-water data; and almost 17,000 stations for collection of water-quality information. These activities are described as well as the means by which the data are made available, and how the program is coordinated with other agencies. (USGS)

Circular↗
USGS1995

1:2,000,000-scale digital line graph data on CD-ROM

Updated U.S. Geological Survey digital line graph (DLG) data collected at a scale of 1:2,000,000 are now available on two compact discs-read only memory (CD-ROM). Each CD-ROM contains digital cartographic data for 49 States and the District of Columbia. The U.S. Virgin Islands, Puerto Rico, and Alaska will be ready within the next year. These DLG data were originally collected from maps published in 1970. Extensive revisions have been made and no data source more than 5 years old was used in this update. In addition, text files containing information such as place names and population have been added for the first time. The records in these text files can be related to corresponding features in the DLG data files. Metadata that comply with the Federal Geographic Data Committee Content Standards for Digital Geospatial Metadata are included for each category of DLG data.

Fact Sheet↗