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At least 523 records · Page 29Linked to original sources
USGS2012

Evaluation of ground motion scaling methods for analysis of structural systems

Ground motion selection and scaling comprises undoubtedly the most important component of any seismic risk assessment study that involves time-history analysis. Ironically, this is also the single parameter with the least guidance provided in current building codes, resulting in the use of mostly subjective choices in design. The relevant research to date has been primarily on single-degree-of-freedom systems, with only a few studies using multi-degree-of-freedom systems. Furthermore, the previous research is based solely on numerical simulations with no experimental data available for the validation of the results. By contrast, the research effort described in this paper focuses on an experimental evaluation of selected ground motion scaling methods based on small-scale shake-table experiments of re-configurable linear-elastic and nonlinear multi-story building frame structure models. Ultimately, the experimental results will lead to the development of guidelines and procedures to achieve reliable demand estimates from nonlinear response history analysis in seismic design. In this paper, an overview of this research effort is discussed and preliminary results based on linear-elastic dynamic response are presented.

Conference Paper↗
USGS2012

Landsat Data Continuity Mission (LDCM) space to ground mission data architecture

The Landsat Data Continuity Mission (LDCM) is a scientific endeavor to extend the longest continuous multi-spectral imaging record of Earth's land surface. The observatory consists of a spacecraft bus integrated with two imaging instruments; the Operational Land Imager (OLI), built by Ball Aerospace & Technologies Corporation in Boulder, Colorado, and the Thermal Infrared Sensor (TIRS), an in-house instrument built at the Goddard Space Flight Center (GSFC). Both instruments are integrated aboard a fine-pointing, fully redundant, spacecraft bus built by Orbital Sciences Corporation, Gilbert, Arizona. The mission is scheduled for launch in January 2013. This paper will describe the innovative end-to-end approach for efficiently managing high volumes of simultaneous realtime and playback of image and ancillary data from the instruments to the reception at the United States Geological Survey's (USGS) Landsat Ground Network (LGN) and International Cooperator (IC) ground stations. The core enabling capability lies within the spacecraft Command and Data Handling (C&DH) system and Radio Frequency (RF) communications system implementation. Each of these systems uniquely contribute to the efficient processing of high speed image data (up to 265Mbps) from each instrument, and provide virtually error free data delivery to the ground. Onboard methods include a combination of lossless data compression, Consultative Committee for Space Data Systems (CCSDS) data formatting, a file-based/managed Solid State Recorder (SSR), and Low Density Parity Check (LDPC) forward error correction. The 440 Mbps wideband X-Band downlink uses Class 1 CCSDS File Delivery Protocol (CFDP), and an earth coverage antenna to deliver an average of 400 scenes per day to a combination of LGN and IC ground stations. This paper will also describe the integrated capabilities and processes at the LGN ground stations for data reception using adaptive filtering, and the mission operations approach fro- the LDCM Mission Operations Center (MOC) to perform the CFDP accounting, file retransmissions, and management of the autonomous features of the SSR.

Conference Paper↗
USGS2013

A computational- And storage-cloud for integration of biodiversity collections

A core mission of the Integrated Digitized Biocollections (iDigBio) project is the building and deployment of a cloud computing environment customized to support the digitization workflow and integration of data from all U.S. nonfederal biocollections. iDigBio chose to use cloud computing technologies to deliver a cyberinfrastructure that is flexible, agile, resilient, and scalable to meet the needs of the biodiversity community. In this context, this paper describes the integration of open source cloud middleware, applications, and third party services using standard formats, protocols, and services. In addition, this paper demonstrates the value of the digitized information from collections in a broader scenario involving multiple disciplines.

Conference Paper↗
USGS2015

Discovering loose group movement patterns from animal trajectories

The technical advances of positioning technologies enable us to track animal movements at finer spatial and temporal scales, and further help to discover a variety of complex interactive relationships. In this paper, considering the loose gathering characteristics of the real-life groups' members during the movements, we propose two kinds of loose group movement patterns and corresponding discovery algorithms. Firstly, we propose the weakly consistent group movement pattern which allows the gathering of a part of the members and individual temporary leave from the whole during the movements. To tolerate the high dispersion of the group at some moments (i.e. to adapt the discontinuity of the group's gatherings), we further scheme the weakly consistent and continuous group movement pattern. The extensive experimental analysis and comparison with the real and synthetic data shows that the group pattern discovery algorithms proposed in this paper are similar to the the real-life frequent divergences of the members during the movements, can discover more complete memberships, and have considerable performance.

Conference Paper↗
USGS2022

Physics-guided machine learning from simulation data: An application in modeling lake and river systems

This paper proposes a new physics-guided machine learning approach that incorporates the scientific knowledge in physics-based models into machine learning models. Physics-based models are widely used to study dynamical systems in a variety of scientific and engineering problems. Although they are built based on general physical laws that govern the relations from input to output variables, these models often produce biased simulations due to inaccurate parameterizations or approximations used to represent the true physics. In this paper, we aim to build a new data-driven framework to monitor dynamical systems by extracting general scientific knowledge embodied in simulation data generated by the physics-based model. To handle the bias in simulation data caused by imperfect parameterization, we propose to extract general physical relations jointly from multiple sets of simulations generated by a physics-based model under different physical parameters. In particular, we develop a spatio-temporal network architecture that uses its gating variables to capture the variation of physical parameters. We initialize this model using a pre-training strategy that helps discover common physical patterns shared by different sets of simulation data. Then we fine-tune it using limited observation data via a contrastive learning process. By leveraging the complementary strength of machine learning and domain knowledge, our method has been shown to produce accurate predictions, use less training samples and generalize to out-of-sample scenarios. We further show that the method can provide insights about the variation of physical parameters over space and time in two domain applications: predicting temperature in streams and predicting temperature in lakes.

Conference Paper↗
USGS2008

Updated radiometric calibration for the Landsat-5 thematic mapper reflective bands

The Landsat-5 Thematic Mapper (TM) has been the workhorse of the Landsat system. Launched in 1984, it continues collecting data through the time frame of this paper. Thus, it provides an invaluable link to the past history of the land features of the Earth's surface, and it becomes imperative to provide an accurate radiometric calibration of the reflective bands to the user community. Previous calibration has been based on information obtained from prelaunch, the onboard calibrator, vicarious calibration attempts, and cross-calibration with Landsat-7. Currently, additional data sources are available to improve this calibration. Specifically, improvements in vicarious calibration methods and development of the use of pseudoinvariant sites for trending provide two additional independent calibration sources. The use of these additional estimates has resulted in a consistent calibration approach that ties together all of the available calibration data sources. Results from this analysis indicate a simple exponential, or a constant model may be used for all bands throughout the lifetime of Landsat-5 TM. Where previously time constants for the exponential models were approximately one year, the updated model has significantly longer time constants in bands 1-3. In contrast, bands 4, 5, and 7 are shown to be best modeled by a constant. The models proposed in this paper indicate calibration knowledge of 5% or better early in life, decreasing to nearly 2% later in life. These models have been implemented at the U.S. Geological Survey Earth Resources Observation and Science (EROS) and are the default calibration used for all Landsat TM data now distributed through EROS. ?? 2008 IEEE.

Conference Paper↗
USGS2016

Best practices in passive remote sensing VNIR hyperspectral system hardware calibrations

Hyperspectral imaging (HSI) is an exciting and rapidly expanding area of instruments and technology in passive remote sensing. Due to quickly changing applications, the instruments are evolving to suit new uses and there is a need for consistent definition, testing, characterization and calibration. This paper seeks to outline a broad prescription and recommendations for basic specification, testing and characterization that must be done on Visible Near Infra-Red grating-based sensors in order to provide calibrated absolute output and performance or at least relative performance that will suit the user’s task. The primary goal of this paper is to provide awareness of the issues with performance of this technology and make recommendations towards standards and protocols that could be used for further efforts in emerging procedures for national laboratory and standards groups.

Conference Paper↗
USGS2021

Comparing geometric differences between Landsat Collection 1 to Collection 2 level-1 products

In late 2020 the U.S. Geological Survey (USGS) began the distribution of Landsat products associated with their collection 2 reprocessing of the archive. Several changes were implemented within the Landsat Product Generation System (LPGS) and the calibration parameters applied to the Landsat imagery for the collection 2 processing. When comparing between collection 1 and collection 2 products, radiometric and geometric differences will be present. One of the most substantial changes between the two collections was an adjustment to the ground control which made the control more accurate from an absolute and relative perspective. Some of the other changes associated with collection 2 processing were to the Digital Elevation Model (DEM) used in terrain correction, the Thermal Infrared Sensor (TIRS) relative gains, TIRS absolute calibration, Operational Land Imagery (OLI) absolute gain model, OLI relative gain, and OLI bias calculation to name a few. Although these changes also have an effect on the differences between the product associated with these two collections, the change in the ground control, although typically less than one 30-meter multispectral pixel in magnitude, will have the largest effect on the differences between the products. This change in ground control is also a spatially dynamic change that although is low in spatial frequency, is nonlinear and is not a change that can be modeled on a global or even on a local Worldwide Reference System-2 (WRS-2) path and row scale. The effects of these ground control changes will be discussed and demonstrated within this paper along with examples showing their effect on specific datasets. This paper demonstrates some of these geometric differences associated with the ground control through both the registration statistics created during product generation and through an example comparison of a set of collection 1 and collection 2 products.

Conference Paper↗
USGS2004

Visual enhancement of unmixed multispectral imagery using adaptive smoothing

Adaptive smoothing (AS) has been previously proposed as a method to smooth uniform regions of an image, retain contrast edges, and enhance edge boundaries. The method is an implementation of the anisotropic diffusion process which results in a gray scale image. This paper discusses modifications to the AS method for application to multi-band data which results in a color segmented image. The process was used to visually enhance the three most distinct abundance fraction images produced by the Lagrange constraint neural network learning-based unmixing of Landsat 7 Enhanced Thematic Mapper Plus multispectral sensor data. A mutual information-based method was applied to select the three most distinct fraction images for subsequent visualization as a red, green, and blue composite. A reported image restoration technique (partial restoration) was applied to the multispectral data to reduce unmixing error, although evaluation of the performance of this technique was beyond the scope of this paper. The modified smoothing process resulted in a color segmented image with homogeneous regions separated by sharpened, coregistered multiband edges. There was improved class separation with the segmented image, which has importance to subsequent operations involving data classification.

Conference Paper↗
USGS2007

Consistency of L4 TM absolute calibration with respect to the L5 TM sensor based on near-simultaneous image acquisition

The Landsat archive provides more than 35 years of uninterrupted multispectral remotely sensed data of Earth observations. Since 1972, Landsat missions have carried different types of sensors, from the Return Beam Vidicon (RBV) camera to the Enhanced Thematic Mapper Plus (ETM+). However, the Thematic Mapper (TM) sensors on Landsat 4 (L4) and Landsat 5 (L5), launched in 1982 and 1984 respectively, are the backbone of an extensive archive. Effective April 2, 2007, the radiometric calibration of L5 TM data processed and distributed by the U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) was updated to use an improved lifetime gain model, based on the instrument's detector response to pseudo-invariant desert site data and cross-calibration with the L7 ETM+. However, no modifications were ever made to the radiometric calibration procedure of the Landsat 4 (L4) TM data. The L4 TM radiometric calibration procedure has continued to use the Internal Calibrator (IC) based calibration algorithms and the post calibration dynamic ranges, as previously defined. To evaluate the "current" absolute accuracy of these two sensors, image pairs from the L5 TM and L4 TM sensors were compared. The number of coincident image pairs in the USGS EROS archive is limited, so the scene selection for the cross-calibration studies proved to be a challenge. Additionally, because of the lack of near-simultaneous images available over well-characterized and traditionally used calibration sites, alternate sites that have high reflectance, large dynamic range, high spatial uniformity, high sun elevation, and minimal cloud cover were investigated. The alternate sites were identified in Yuma, Iraq, Egypt, Libya, and Algeria. The cross-calibration approach involved comparing image statistics derived from large common areas observed eight days apart by the two sensors. This paper summarizes the average percent differences in reflectance estimates obtained between the two sensors. The work presented in this paper is a first step in understanding the current performance of L4 TM absolute calibration and potentially serves as a platform to revise and improve the radiometric calibration procedures implemented for the processing of L4 TM data.

Conference Paper↗
USGS2008

Development of landsat-5 thematic mapper internal calibrator gain and offset table

The National Landsat Archive Production System (NLAPS) has been the primary processing system for Landsat data since U.S. Geological Survey (USGS) Earth Resources Observation and Science Center (EROS) started archiving Landsat data. NLAPS converts raw satellite data into radiometrically and geometrically calibrated products. NLAPS has historically used the Internal Calibrator (IC) to calibrate the reflective bands of the Landsat-5 Thematic Mapper (TM), even though the lamps in the IC were less stable than the TM detectors, as evidenced by vicarious calibration results. In 2003, a major effort was made to model the actual TM gain change and to update NLAPS to use this model rather than the unstable IC data for radiometric calibration. The model coefficients were revised in 2007 to reflect greater understanding of the changes in the TM responsivity. While the calibration updates are important to users with recently processed data, the processing system no longer calculates the original IC gain or offset. For specific applications, it is useful to have a record of the gain and offset actually applied to the older data. Thus, the NLAPS calibration database was used to generate estimated daily values for the radiometric gain and offset that might have been applied to TM data. This paper discusses the need for and generation of the NLAPSIC gain and offset tables. A companion paper covers the application of and errors associated with using these tables.

Conference Paper↗
USGS2008

L5 TM radiometric recalibration procedure using the internal calibration trends from the NLAPS trending database

From the Landsat program's inception in 1972 to the present, the earth science user community has benefited from a historical record of remotely sensed data. The multispectral data from the Landsat 5 (L5) Thematic Mapper (TM) sensor provide the backbone for this extensive archive. Historically, the radiometric calibration procedure for this imagery used the instrument's response to the Internal Calibrator (IC) on a scene-by-scene basis to determine the gain and offset for each detector. The IC system degraded with time causing radiometric calibration errors up to 20 percent. In May 2003 the National Landsat Archive Production System (NLAPS) was updated to use a gain model rather than the scene acquisition specific IC gains to calibrate TM data processed in the United States. Further modification of the gain model was performed in 2007. L5 TM data that were processed using IC prior to the calibration update do not benefit from the recent calibration revisions. A procedure has been developed to give users the ability to recalibrate their existing Level-1 products. The best recalibration results are obtained if the work order report that was originally included in the standard data product delivery is available. However, many users may not have the original work order report. In such cases, the IC gain look-up table that was generated using the radiometric gain trends recorded in the NLAPS database can be used for recalibration. This paper discusses the procedure to recalibrate L5 TM data when the work order report originally used in processing is not available. A companion paper discusses the generation of the NLAPS IC gain and bias look-up tables required to perform the recalibration.

Conference Paper↗
USGS2005

Coal systems analysis: A new approach to the understanding of coal formation, coal quality and environmental considerations, and coal as a source rock for hydrocarbons

Coal is an important and required energy source for today's world. Current rates of world coal consumption are projected to continue at approximately the same (or greater) levels well into the twenty-first century. This paper will provide an introduction to the concept of coal systems analysis and the accompanying volume of papers will provide examples of how coal systems analysis can be used to understand, characterize, and evaluate coal and coal gas resources. Coal systems analysis incorporates the various disciplines of coal geology to provide a complete characterization of the resource. The coal system is divided into four stages: (1) accumulation, (2) preservation-burial, (3) diagenesis-coalification, and (4) coal and hydrocarbon resources. These stages are briefly discussed and key references and examples of the application of coal systems analysis are provided.

Special Papers of the Geological Society of Americ↗
USGS2010

Geologic map of Lake Mead and surrounding regions, southern Nevada, southwestern Utah, and northwestern Arizona

Regional stratigraphic units and structural features of the Lake Mead region are presented as a 1:250,000 scale map, and as a Geographic Information System database. The map, which was compiled from existing geologic maps of various scales, depicts geologic units, bedding and foliation attitudes, faults and folds. Units and structural features were generalized to highlight the regional stratigraphic and tectonic aspects of the geology of the Lake Mead region. This map was prepared in support of the papers presented in this volume, Special Paper 463, as well as to facilitate future investigations in the region. Stratigraphic units exposed within the area record 1800 million years of geologic history and include Proterozoic crystalline rocks, Paleozoic and Mesozoic sedimentary rocks, Mesozoic plutonic rocks, Cenozoic volcanic and intrusive rocks, sedimentary rocks and surficial deposits. Following passive margin sedimentation in the Paleozoic and Mesozoic, late Mesozoic (Sevier) thrusting and Late Cretaceous and early Tertiary compression produced major folding, reverse faulting, and thrust faulting in the Basin and Range, and resulted in regional uplift and monoclinal folding in the Colorado Plateau. Cenozoic extensional deformation, accompanied by sedimentation and volcanism, resulted in large-magnitude high- and low-angle normal faulting and strike-slip faulting in the Basin and Range; on the Colorado Plateau, extension produced north-trending high-angle normal faults. The latest history includes integration of the Colorado River system, dissection, development of alluvial fans, extensive pediment surfaces, and young faulting. Stratigraphic units exposed within the area record 1800 million years of geologic history and include Proterozoic crystalline rocks, Paleozoic and Mesozoic sedimentary rocks, Mesozoic plutonic rocks, Cenozoic volcanic and intrusive rocks, sedimentary rocks and surfi cial deposits. Following passive margin sedimentation in the Paleozoic and Mesozoic, late Mesozoic (Sevier) thrusting and Late Cretaceous and early Tertiary compression produced major folding, reverse faulting, and thrust faulting in the Basin and Range, and resulted in regional uplift and monoclinal folding in the Colorado Plateau. Cenozoic extensional deformation, accompanied by sedimentation and volcanism, resulted in large-magnitude high- and low-angle normal faulting and strike-slip faulting in the Basin and Range; on the Colorado Plateau, extension produced north-trending high-angle normal faults. The latest history includes integration of the Colorado River system, dissection, development of alluvial fans, extensive pediment surfaces, and young faulting.

Arizona, Nevada, Utah↗
USGS2022

Modeling reservoir release using pseudo-prospective learning and physical simulations to predict water temperature

This paper proposes a new data-driven method for predicting water temperature in stream networks with reservoirs. The water flows released from reservoirs greatly affect the water temperature of downstream river segments. However, the information of released water flow is often not available for many reservoirs, which makes it difficult for data-driven models to capture the impact to downstream river segments. In this paper, we first build a state-aware graph model to represent the interactions amongst streams and reservoirs, and then propose a parallel learning structure to extract the reservoir release information and use it to improve the prediction. In particular, for reservoirs with no available release information, we mimic the water managers' release decision process through a pseudo-prospective learning method, which infers the release information from anticipated water temperature dynamics. For reservoirs with the release information, we leverage a physics-based model to simulate the water release temperature and transfer such information to guide the learning process for other reservoirs. The evaluation for the Delaware River Basin shows that the proposed method brings over 10% accuracy improvement over existing data-driven models for stream temperature prediction when the release data is not available for any reservoirs. The performance is further improved after we incorporate the release data and physical simulations for a subset of reservoirs.

Conference Paper↗
USGS2008

Large-scale marine ecosystem change and the conservation of marine mammals

Papers in this Special Feature stem from a symposium on large-scale ecosystem change and the conservation of marine mammals convened at the 86th Annual Meeting of the American Society of Mammalogists in June 2006. Major changes are occurring in multiple aspects of the marine environment at unprecedented rates, within the life spans of some individual marine mammals. Drivers of change include shifts in climate, acoustic pollution, disturbances to trophic structure, fisheries interactions, harmful algal blooms, and environmental contaminants. This Special Feature provides an in-depth examination of 3 issues that are particularly troublesome. The 1st article notes the huge spatial and temporal scales of change to which marine mammals are showing ecological responses, and how these species can function as sentinels of such change. The 2nd paper describes the serious problems arising from conflicts with fisheries, and the 3rd contribution reviews the growing issues associated with underwater noise. ?? 2008 American Society of Mammalogists.

Conference Paper↗
USGS2006

Biodiversity management of fens and fen meadows by grazing, cutting and burning

Question: Can the biodiversity of fens in Europe and North America be maintained through the use of grazing (especially cattle grazing), fire, and/or cutting? Location: European and North American fens. Methods: This paper is a review of the literature on the effects of grazing, fire and cutting on fens, to explore the relationship between management and biodiversity in fens. Results: A reduction of cattle grazing, mowing and burning in fens has led to a reduction in biodiversity in fens. The vegetation of abandoned fens shifts to trees and shrubs after 10-15 years, which shade the smaller and rarer species of these wetlands. While careful use of fire is used to manage fens in North America, it is not widely used in European fens, perhaps because the peat of drained fens may catch fire. Cattle grazing cannot be considered a natural disturbance in North America, since cattle did not evolve on that continent. In Europe, cattle do not generally graze in unaltered fens, but they do use slightly drained fen meadows. Conclusions: Three approaches have been used to control the dominance of tall woody and herbaceous species in abandoned fens, including the re-introduction of cattle, mowing, and burning. Overgrazing results in a permanent reduction in biodiversity, therefore cattle re-introduction must be approached cautiously. In Europe, but not in North America, mowing has been an important management tool, and mowing has been successful in maintaining species richness, particularly in fens that have been mowed annually for centuries. Fire has been the most common and successful management tool in North America although it is not effective in removing shrubs that have become large. Because the problems and solutions are similar, the literature of both European and North American fen management can be analyzed to better assess the management of fens on both continents. Many management questions require further study and these are listed in the paper. ?? IAVS; Opulus Press.

Conference Paper↗
USGS1969

Flow of a disperse emulsion of crude oil in water in porous media

It has been suggested that oil migrates through reservoir sands in the form of a fine, disperse emulsion of oil in water, and that oil accumulations occur where the stream enters finer-grained rock such as silt or shale. In order to investigate the possible mechanisms, stable emulsions of oil in water were prepared without the use of wetting agents. They consisted of droplets 1/2 to 1-1/2 microns in diameter, in a concentration of 20 to 40 parts of oil per million of water. These emulsions passed freely through filter paper and ordinary passed freely through filter paper and ordinary sand. A plastic tube containing glass beads of 200-microns diameter included a bed 1/2-cm thick of crushed beads 37 to 88 microns in diameter. When the emulsion was passed through this tube, up to 80 percent of the oil was screened out at the coarse-fine interface. The amount removed depended on the contrast in grain size, the nature and the preferential wettability of the media. Similar results occurred when quartz sand was used as the coarse, and crushed sand as the fine medium. This screening did not occur as a result of capillary effects., because the pores were many times the diameter of the droplets. The oil collected as a result of flocculation of the droplets into strings and clusters., and the oil saturation in the pores consisted of masses of droplets with very little coalescence. Possibly electrostatic forces are more important Possibly electrostatic forces are more important than capillary in the behavior of fine, disperse, oil-in-water emulsions. our current ideas on multiphase flow in porous media may not apply to disperse emulsions.

Conference Paper↗