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At least 1,441 records · Page 80Linked to original sources
USGS1991

Comparison of three different methods to merge multiresolution and multispectral data: Landsat TM and SPOT panchromatic

The merging of multisensor image data is becoming a widely used procedure because of the complementary nature of various data sets. Ideally, the method used to merge data sets with high-spatial and high-spectral resolution should not distort the spectral characteristics of the high-spectral resolution data. This paper compares the results of three different methods used to merge the information contents of the Landsat Thematic Mapper (TM) and Satellite Pour l'Observation de la Terre (SPOT) panchromatic data. The comparison is based on spectral characteristics and is made using statistical, visual, and graphical analyses of the results. The three methods used to merge the information contents of the Landsat TM and SPOT panchromatic data were the Hue-Intensity-Saturation (HIS), Principal Component Analysis (PCA), and High-Pass Filter (HPF) procedures. The HIS method distorted the spectral characteristics of the data the most. The HPF method distorted the spectral characteristics the least; the distortions were minimal and difficult to detect. -Authors

Photogrammetric Engineering and Remote Sensing↗
USGS1994

Real-time data collection of scour at bridges

The record flood on the Mississippi River during the summer of 1993 provided a rare opportunity to collect data on scour of the streambed at bridges and to test data collection equipment under extreme hydraulic conditions. Detailed bathymetric and hydraulic information were collected at two bridges crossing the Mississippi River during the rising limb, near the peak, and during the recession of the flood. Bathymetric data were collected using a digital echo sounder. Three-dimensional velocities were collected using Broadband Acoustic Doppler Current Profilers (BB-ADCP) operating at 300 kilohertz (kHz), 600 kHz, and 1,200 kHz. Positioning of the data collected was measured using a range-azimuth tracking system and two global positioning systems (GPS). Although differential GPS was able to provide accurate positions and tracking information during approach- and exit-reach data collection, it was unable to maintain lock on a sufficient number of satellites when the survey vessel was under the bridge or near the piers. The range-azimuth tracking system was used to collect position and tracking information for detailed data collection near the bridge piers. These detailed data indicated local scour ranging from 3 to 8 meters and will permit a field-based evaluation of the ability of various numerical models to compute the hydraulics, depth, geometry, and time-dependent development of local scour.

Conference Paper↗
USGS2001

Hierarchical programming for data storage and visualization

Graphics software is an essential tool for interpreting, analyzing, and presenting data from multidimensional hydrodynamic models used in estuarine and coastal ocean studies. The post-processing of time-varying three-dimensional model output presents unique requirements for data visualization because of the large volume of data that can be generated and the multitude of time scales that must be examined. Such data can relate to estuarine or coastal ocean environments and come from numerical models or field instruments. One useful software tool for the display, editing, visualization, and printing of graphical data is the Gr application, written by the first author for use in U.S. Geological Survey San Francisco Bay Program. The Gr application has been made available to the public via the Internet since the year 2000. The Gr application is written in the Java (Sun Microsystems, Nov. 29, 2001) programming language and uses the Extensible Markup Language standard for hierarchical data storage. Gr presents a hierarchy of objects to the user that can be edited using a common interface. Java's object-oriented capabilities allow Gr to treat data, graphics, and tools equally and to save them all to a single XML file.

Conference Paper↗
USGS2002

Comparability and accuracy of fluvial-sediment data - A view from the U.S. Geological Survey

The quality of historical fluvial-sediment data cannot be taken for granted, based on a review of upper Colorado River basin suspended-sediment discharges, and on an evaluation of the reliability of Total Suspended Solids (TSS) data. Additionally, the quality of future fluvial-sediment data are not assured. Sediment-surrogate technologies, including those that operate on acoustic, laser, bulk optic, digital optic, or pressure differential principles, are being used with increasing frequency to measure in-stream and (or) laboratory fluvial-sediment characteristics. Data from sediment-surrogate technologies may yield results that differ significantly from those obtained by traditional methods for the same sedimentary conditions. Development of national sediment data-quality criteria and rigorous comparisons of data derived from sediment-surrogate technologies to those obtained by traditional techniques will minimize the potential for future fluvial-sediment data-quality concerns.

Conference Paper↗
USGS1969

Hydrogeologic data for the southwestern coastal river basins, Connecticut

This report presents hydrologic and geologic data collected by the U.S. Geological Survey during an investigation of water resources in the southwestern coastal river basins of Connecticut in cooperation with the Connecticut Water Resources Commission. These basins occupy about 394 square miles in Connecticut and 46 square miles in New York, including the towns of Greenwich, Stamford, Darien, New Canaan, Norwalk, Wilton, Westport, Weston, Fairfield, Easton, and Bridgeport and parts of Danbury, Ridgefield, Redding, Bethel, Newtown, Trumbull, Monroe, Shelton, and Stratford. A companion interpretive report evaluating the water resources of the basins will be published as Connecticut Water Resources Bulletin No. 17. The data on the following pages serve to document and supplement that report and should be especially useful in planning the development of water resources at specific localities. Data were collected as part of this investigation during the period July 1963 through November 1966. Streamflow records from continuous-record gaging stations in the basins have been published annually along with data from other parts of the State in a series of U.S. Geological Survey reports entitled "Surface Water Records of Connecticut." Water-level measurements in wells throughout the State from 1960 through 1966, including most of those made as part of this investigation, are published in Connecticut Water Resources Bulletins No. 7 and No. 13. Most other data collected during this investigation are tabulated on the following pages. Included are some well records and chemical analyses of water samples collected prior to July 1963 and not previously published. The locations of sites at which data were collected are shown on plate A in the pocket at the back of the report. Data presented, unless otherwise noted, were collected by U.S. Geological Survey personnel.

Connecticut↗
USGS1970

Hydrogeologic data for the lower Housatonic River basin, Connecticut

This report contains hydrologic and geologic data collected for an investigation of the lower Housatonic River basin by the U.S. Geological Survey in financial cooperation with the Connecticut Water Resources Commission. The report also summarizes data that are available in other publications. The towns within the 557 square mile area of the basin in western Connecticut include all of Beacon Falls, Middlebury, Naugatuck, Oxford, Seymour, Thomaston, Waterbury, Watertown, and Woodbury; and parts of Ansonia, Bethany, Bethlehem, Bristol, Burlington, Cheshire, Derby, Easton, Goshen, Narwinton, Litchfield, Milford, Monroe, Morris, New Hartford, Newtown, Norfolk, Orange, Plymouth, Prospect, Roxbury, Shelton, Southbury, Stratford, Torrington, Trumbull, Washington, Winchester, Wolcott, and Woodbridge. The factual information on the following pages was the basis for a companion interpretive report, Connecticut Water Resources Bulletin No. 19 (Wilson, W. E., and others, in preparation, 1970). The basic-data report can be used alone for detailed information needed in planning water resources development at specific sites or it can be used to supplement the interpretive report. Data were collected for this investigation from 1965 to 1967. Water levels measured in wells as part of this investigation were published in Connecticut Water Resources Bulletin No. 7 (Meikle and Baker, 1965) and No. 13 (Meikle, 1967) with water-level data from other wells throughout the State. Publications containing relevant ground-water information are listed on page those concerned with streamflow are on page 5 and those on quality of water, are on page 6. The locations of sites at which data were collected are shown on plate A in the back pocket of this report. Data presented here were collected by the U.S. Geological Survey unless otherwise noted.

Connecticut↗
USGS1972

Photogeology: Part W: Apollo 16 landing site: summary of Earth-based remote sensing data

The purpose of the infrared (IR) and radar study of the Apollo data is to establish lunar surface conditions in the vicinity of the orbital tracks of the Apollo command modules during the J-series missions. Correlations and comparisons between the Earth-based radar observations, IR observations, and other data will be plotted on photomaps produced from the mapping and panoramic cameras. In addition, the Apollo photography will be used to improve the classifications of the anomalous IR and radar features. The three sets of Earth-based data have already been obtained. The IR (11 μm) data (ref. 29-112) were obtained during a total lunar eclipse. More than a thousand thermally anomalous regions with an unusually high population of exposed boulders have been identified (ref. 29-113). The 70-cm radar backscatter observations made at the same resolution as the IR measurements show regions of anomalous backscatter. These regions have been explained as roughness caused by the boulders on the surface and below the surface. The high-resolution 3.8-cm radar backscatter measurements (ref. 29-114) reveal in great detail regions of anomalous radar backscatter. At this short radar wavelength, small-scale surface and subsurface roughness and boulders less than the order of 10 cm are responsible for the anomalous returns. Previous studies have revealed strong correlation between these three data sets (refs. 29-115 to 29-117). The strongest anomalies (anomalous at all three wavelengths) correspond to features interpreted geologically as young Copernican craters. There are, however, many combinations of enhancements from IR only, 70-cm radar only, 3.8-cm radar only, or combinations of two of these types but not a third. The variation of intensity in all combinations indicates a very complex set of features. These data provide information about the surface on a centimeter- and meter-sized scale although the basic instrumental resolution was 2 to 15 km. The Apollo orbital photography and observations at the landing sites, used in conjunction with the remote sensing data, can significantly improve geologic and geophysical interpretations of lunar surface conditions.

Book chapter↗
USGS2010

New software methods in radar ornithology using WSR-88D weather data and potential application to monitoring effects of climate change on bird migration

Radar ornithology has provided tools for studying the movement of birds, especially related to migration. Researchers have presented qualitative evidence suggesting that birds, or at least migration events, can be identified using large broad scale radars such as the WSR-88D used in the NEXRAD weather surveillance system. This is potentially a boon for ornithologists because such data cover a large portion of the United States, are constantly being produced, are freely available, and have been archived since the early 1990s. A major obstacle to this research, however, has been that identifying birds in NEXRAD data has required a trained technician to manually inspect a graphically rendered radar sweep. A single site completes one volume scan every five to ten minutes, producing over 52,000 volume scans in one year. This is an immense amount of data, and manual classification is infeasible. We have developed a system that identifies biological echoes using machine learning techniques. This approach begins with training data using scans that have been classified by experts, or uses bird data collected in the field. The data are preprocessed to ensure quality and to emphasize relevant features. A classifier is then trained using this data and cross validation is used to measure performance. We compared neural networks, naive Bayes, and k-nearest neighbor classifiers. Empirical evidence is provided showing that this system can achieve classification accuracies in the 80th to 90th percentile. We propose to apply these methods to studying bird migration phenology and how it is affected by climate variability and change over multiple temporal scales.

Conference Paper↗
USGS1981

The role of remotely sensed and other spatial data for predictive modeling: the Umatilla, Oregon example

The U. S. Geological Survey's Earth Resources Observations Systems Data Center, in cooperation with the U.S. Army Corps of Engineers, Portland District, developed and tested techniques that used remotely sensed and other spatial data in predictive models to evaluate irrigation agriculture in the Umatilla River Basin of north-central Oregon. Landsat data and 1:24,000-scale aerial photographs were initially used to map he expansion of irrigate from 1973 to 1979 and to identify crops under irrigation in 1979. The crop data were then used with historical water requirement figures and digital topographic and hydrographic data to estimate water and power use for the 1979 irrigation season. The final project task involved production of a composite map of land suitability for irrigation development based on land cover (from Landsat), land-ownership, soil irrigability, slope gradient, and potential energy costs. The methods and data used in the study demonstrated the flexibility of remotely sensed and other spatial data as input for predictive models. When combined, they provided useful answers to complex questions facing resource managers.

Oregon↗
USGS1993

History of greenness mapping at the EROS data center

In 1987, the U.S. Geological Survey's EROS Data Center (EDC)installed a system to acquire, process, and distribute advanced very high resolution radiometer (AVHRR) satellite image data collected over North America. Using this system, the EDC began an experimental greenness mapping program as part of the U.S. Agency for the International Development Famine Early Warning System. The program used the greenness information derived from AVHRR data to identify potential outbreaks of locusts and grasshoppers in the Sahelian region of Africa. In 1988, the EDC began greenness mapping projects in Africa and the northern Great Plains of the United States. In 1989, the system was augmented to acquire AVHRR information for the rest of the world. As a result, the greenness mapping program was able to collect data for fire danger assessment, agricultural assessment, and land characterization. Illustrations of each of the mapping projects trace the chronology of the greenness mapping program at the EDC. Displays represent the initial activity in Africa and the transition of the north Great Plains project to the current conterminous U.S. project. The program's expansion to include Alaska, Eurasia, a prototype North America data set, and ultimately, an experimental global land 1-km product is also shown. The poster describes major technical advances in data processing, the development of derivative products, the magnitude of the data volume of each level, and major applications.

Pecora 12 Symposium↗
USGS1986

Vegetation and terrain mapping in Alaska using Landsat MSS and digital terrain data

During the past 5 years, the U.S. Geological Survey's (USGS) Earth Resources Observation Systems (EROS) Data Center Field Office in Anchorage, Alaska has worked cooperatively with Federal and State resource management agencies to produce land-cover and terrain maps for 245 million acres of Alaska. The need for current land-cover information in Alaska comes principally from the mandates of the Alaska National Interest Lands Conservation Act (ANILCA), December 1980, which requires major land management agencies to prepare comprehensive management plans. The land-cover mapping projects integrate digital Landsat data, terrain data, aerial photographs, and field data. The resultant land-cover and terrain maps and associated data bases are used for resource assessment, management, and planning by many Alaskan agencies including the U.S. Fish and Wildlife Service, U.S. Forest Service, Bureau of Land Management, and Alaska Department of Natural Resources. Applications addressed through use of the digital land-cover and terrain data bases range from comprehensive refuge planning to multiphased sampling procedures designed to inventory vegetation statewide. The land-cover mapping programs in Alaska demonstrate the operational utility of digital Landsat data and have resulted in a new land-cover mapping program by the USGS National Mapping Division to compile 1:250,000-scale land-cover maps in Alaska using a common statewide land-cover map legend.

Alaska↗
USGS1995

Effects of empirical versus model-based reflectance calibration on automated analysis of imaging spectrometer data: a case study from the Drum Mountains, Utah

Data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) have been calibrated to surface reflectance using an empirical method and an atmospheric model-based method. Single spectra extracted from both calibrated data sets for locations with known mineralogy compared favorably with laboratory and field spectral measurements of samples from the same locations. Generally, spectral features were somewhat subdued in data calibrated using the model-based method when compared with those calibrated using the empirical method. Automated feature extraction and expert system analysis techniques have been successfully applied to both data sets to produce similar endmember probability images and spectral endmember libraries. Linear spectral unmixing procedures applied to both calibrated data sets produced similar image maps. These comparisons demonstrated the utility of the model-based approach for atmospherically correcting imaging spectrometer data prior to extraction of scientific information. The results indicated that imaging spectrometer data can be calibrated and analyzed without a priori knowledge of the remote target.

Photogrammetric Engineering and Remote Sensing↗
USGS2012

Using computational modeling of river flow with remotely sensed data to infer channel bathymetry

As part of an ongoing investigation into the use of computational river flow and morphodynamic models for the purpose of correcting and extending remotely sensed river datasets, a simple method for inferring channel bathymetry is developed and discussed. The method is based on an inversion of the equations expressing conservation of mass and momentum to develop equations that can be solved for depth given known values of vertically-averaged velocity and water-surface elevation. The ultimate goal of this work is to combine imperfect remotely sensed data on river planform, water-surface elevation and water-surface velocity in order to estimate depth and other physical parameters of river channels. In this paper, the technique is examined using synthetic data sets that are developed directly from the application of forward two-and three-dimensional flow models. These data sets are constrained to satisfy conservation of mass and momentum, unlike typical remotely sensed field data sets. This provides a better understanding of the process and also allows assessment of how simple inaccuracies in remotely sensed estimates might propagate into depth estimates. The technique is applied to three simple cases: First, depth is extracted from a synthetic dataset of vertically averaged velocity and water-surface elevation; second, depth is extracted from the same data set but with a normally-distributed random error added to the water-surface elevation; third, depth is extracted from a synthetic data set for the same river reach using computed water-surface velocities (in place of depth-integrated values) and water-surface elevations. In each case, the extracted depths are compared to the actual measured depths used to construct the synthetic data sets (with two- and three-dimensional flow models). Errors in water-surface elevation and velocity that are very small degrade depth estimates and cannot be recovered. Errors in depth estimates associated with assuming water-surface velocities equal to depth-integrated velocities are substantial, but can be reduced with simple corrections.

Conference Paper↗
USGS2006

Textural analysis of marine sediments at the USGS Woods Hole Science Center; methodology and data on DVD

Marine sediments off the eastern United States vary markedly in texture (i.e., the size, shape, composition, and arrangement of their grains) due to a complex geologic history. For descriptive purposes, however, it is typically most useful to classify these sediments according to their grain-size distributions. In 1962, the U.S. Geological Survey began a program to study the marine geology of the continental margin off the Atlantic coast of the United States. As part of this program and numerous subsequent projects, thousands of sediment grab samples and cores were collected and analyzed for grain size at the Woods Hole Science Center. USGS Open-File Report 2005-1001 (Poppe et al., 2005), available on DVD and online, describes the field methods used to collect marine sediment samples as well as the laboratory methods used to determine and characterize grain-size distributions, and presents these data in several formats that can be readily employed by interested parties. The report is divided into three sections. The first section discusses procedures and contains pictures of the equipment, analytical flow diagrams, video clips with voice commentary, classification schemes, useful forms and compiled and uncompiled versions of the data-acquisition and data-processing software with documentation. The second section contains the grain-size data for more than 23,000 analyses in two “flat-file” formats, a data dictionary, and color-coded browse maps. The third section provides a GIS data catalog of the available point, interpretive, and baseline data layers, with FGDC-compliant metadata to help users visualize the textural information in a geographic context.

Conference Paper↗
USGS1976

Geothermal flux through palagonitized tephra, Surtsey, Iceland: The Surtsey temperature-data-relay experiment via Landsat-1

The net geothermal flux through palagonitized basaltic tephra rims of the Surtur I and Surtur II craters at Surtsey, Iceland, in 1972, is estimated at 780 ±325 μ cal cm -2 s -1 , indicating a decline since 1969 when a flux of 1,500 μ cal cm -2 s -1 was estimated. Heat flux in this range characterizes the postvolcanic environment on Surtsey in which the subaerial palagonitization of basaltic tephra is associated with mass transfer of hydrothermal vapor, either of meteoric or sea-water origin, only a few years after cessation of eruptive activity. The flux estimation is the result of the Surtsey data-relay experiment via Landsat-1 which was carried. out in several phases. Successful field installation and test transmissions demonstrated the feasibility of repetitive long-distance (that is, 4,800-km) data transmission and reception from a volcanic environment in Iceland via the Landsat Data Collection System. Temperature data were transmitted for a 38-day period in November and December 1972. A near-surface vertical gradient of 69.4 °C/m was obtained, suggesting a mixed mechanism of heat transfer, partitioned between conduction and convection. Comparison of four methods for estimating fluxes between 500 and 1,500 μ cal cm -2 s -1 , using temperature data derived from the Data Collection Platform, suggests that, where the only temperature available are from the surface and a depth of 1 m, methods of estimating the net geothermal flux from examination of spectral radiance are superior to methods that assume dominant convection or conduction. A computerized thermal-modeling technique to construct parametric diurnal surface-temperature curves is particularly applicable. Flux-estimation methods that assume dominant convection or conduction are limited by the lack of temperature data at greater depths and lack of knowledge of the exact energy partition.

Surtsey↗
USGS2022

Update on the Center for Engineering Strong-Motion Data (CESMD)

he Center for Engineering Strong-Motion Data (CESMD), an internationally utilized joint center of the U.S. Geological Survey (USGS) and the California Geological Survey (CGS), provides a unified access point for earthquake strong-motion records and station metadata from the CGS California Strong-Motion Instrumentation Program (CSMIP), the USGS National Strong-Motion Project (NSMP), the USGS Advanced National Seismic System (ANSS), and other affiliates. The CESMD works closely with the ANSS and with the Consortium of Organizations for Strong-Motion Observation Systems (COSMOS) to engage with strong-motion networks in the U.S. and other countries to receive, process, and post records. The CESMD has recently developed new tools to facilitate access to strong-motion data and metadata for use in post-earthquake response and scientific research applications. The Center provides raw and processed strong-motion data via its Engineering Data Center (EDC) and the Virtual Data Center (VDC) web portals, currently hosting more than 60,000 records with peak ground accelerations greater than 0.1% g, from over 3,000 earthquakes. This short paper provides updates of the available strong-motion data, station metadata, recent enhancements and developments of the tools, and applications that are made available to users for accessing strong-motion data.

Conference Paper↗
USGS2023

Development of small uncrewed aerial systems for multi-instrument geophysical data acquisition in active geothermal systems

Small Uncrewed Aerial Systems (sUAS) serve as critical platforms for geophysical data collection at an intermediate scale between lower resolution, regional datasets collected via crewed aerial surveys, and high resolution, but spatially sparse sampling of ground-based data collection methods. Advances in sensor design and sUAS capabilities have led to rapid advances in the amount and type of geophysical data that can be acquired using sUAS-based survey designs (Gavazzi et al., 2019). Here we showcase the utility of a single sUAS (the Matrice 600 Pro and accompanying sensor package) that collects magnetic, thermal infra-red (TIR) and gas (CO2, SO2, H2S, water vapor) data for use in geothermal resource exploration and monitoring, with case studies in eastern California and Iceland. The work highlights the flexibility of modern sUAS systems for single-team acquisition of multiple independent but coupled geophysical data which allow for a multidisciplinary approach to geothermal systems research. We summarize the workflows involved in collecting each dataset as well as several common issues encountered both during data collection and data processing.

Conference Paper↗
USGS2006

Dissemination of LANDFIRE Prototype Project data

The transfer of LANDFIRE data to users is the most important aspect of the Landscape Fire and Resource Management Planning Tools Project (LANDFIRE Prototype Project). The creation of an accurate, consistent, nationwide data set provides the foundation for a successful project. The final step is to make the data readily available to the user community. User capabilities and needs vary widely. Many users require LANDFIRE data to solve day-to-day wildfire management problems such as planning fuel treatments or managing active wildfires. Others use LANDFIRE data to gather information over large geographic areas for strategic planning and analyses. The diversity of users and the variety of applications of LANDFIRE data present an interesting challenge: to develop a data dissemination system that is comprehensive, user-friendly, and flexible. The system must be functional across many levels of technology, ranging from powerful computing capability to support national-scale strategic planning to field-level tactical wildfire operations support. The system must be sustainable, dependable, affordable, and adaptable to various levels of and changes in technology.

General Technical Report↗