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At least 1,135 records · Page 63Linked to original sources
USGS1993

Calibration of the BASS acoustic current meter with carrageenan agar

The BASS current meter can measure currents down to the millimeter per second range. Due to the dependence of zero offset on pressure, determining a sensor referenced velocity requires accurate in situ zeroing of the meter. Previously, flow was restricted during calibration by placing plastic bags around the acoustic volume. In this paper, bacterial grade and carrageenan agars are used in the laboratory to create a zero flow condition during calibration and are shown to be acoustically transparent. Additionally, the results of open ocean and dockside carrageenan and plastic bag comparisons are presented. Carrageenan is shown to reliably provide a low noise, zero mean flow environment that is largely independent of ambient conditions. The improved zeros make millimeter per second accuracy possible under field conditions.

Conference Paper↗
USGS2024

Telecommunications fiber for sensing earthquake aftershocks: Progress and hurdles

Aftershocks offer valuable clues to earthquake behavior. The challenge: quickly deploying sensors to capture the early details of earthquake ruptures within the zone of aftershocks. Telecommunication fibers might be an answer, providing denser networks in otherwise difficult areas, potentially faster than traditional methods.

Conference Paper↗
USGS1986

Shuttle imaging radar: Physical controls on signal penetration and subsurface scattenng in the Eastern Sahara

SIR-A signal penetration and subsurface backscatter within the upper meter or so of the sediment blanket in the Eastern Sahara of southern Egypt and northern Sudan are enhanced both by radar sensor parameters and by the physical and chemical characteristics of eolian and alluvial materials. Interpretation of SIR-A images by McCauley et al. [1], [2] dramatically changed previous concepts of the role that fluvial processes have played over the past 10000 to 30000000 years in shaping this now extremely flat, featureless, and hyperarid landscape. In the present paper we summarize the near-surface stratigraphy, the electrical properties of materials, and the types of radar interfaces found to be responsible for different classes of SIR-A tonal response. The dominant factors related to efficient microwave signal penetration into the sediment blanket include a) favorable distribution of particle sizes, b) extremely low moisture content and c) reduced geometric scattering at the SIR-A frequency (1.3 GHz). The depth of signal penetration that results in a recorded backscatter, here called "radar imaging depth," was documented in the field to be a maximum of 1.5 m, or 0.25 of the calculated "skin depth," for the sediment blanket. Radar imaging depth is estimated to be between 2 and 3 m for active sand dune materials. Diverse permittivity interfaces and volume scatterers within the shallow subsurface are responsible for most of the observed backscatter not directly attributable to grazing outcrops.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2002

Estimating terrestrial snow depth with the Topex-Poseidon altimeter and radiometer

Active and passive microwave measurements obtained by the dual-frequency Topex-Poseidon radar altimeter from the Northern Great Plains of the United States are used to develop a snow pack radar backscatter model. The model results are compared with daily time series of surface snow observations made by the U.S. National Weather Service. The model results show that Ku-band provides more accurate snow depth determinations than does C-band. Comparing the snow depth determinations derived from the Topex-Poseidon nadir-looking passive microwave radiometers with the oblique-looking Satellite Sensor Microwave Imager (SSM/I) passive microwave observations and surface observations shows that both instruments accurately portray the temporal characteristics of the snow depth time series. While both retrievals consistently underestimate the actual snow depths, the Topex-Poseidon results are more accurate.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2004

A geometric performance assessment of the EO-1 advanced land imager

The Earth Observing 1 (EO-1) Advanced Land Imager (ALI) demonstrates technology applicable to a successor system to the Landsat Thematic Mapper series. A study of the geometric performance characteristics of the ALI was conducted under the auspices of the EO-1 Science Validation Team. This study evaluated ALI performance with respect to absolute pointing knowledge, focal plane sensor chip assembly alignment, and band-to-band registration for purposes of comparing this new technology to the heritage Landsat systems. On-orbit geometric calibration procedures were developed that allowed the generation of ALI geometrically corrected products that compare favorably with their Landsat 7 counterparts with respect to absolute geodetic accuracy, internal image geometry, and band registration.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2004

Landsat-5 TM reflective-band absolute radiometric calibration

The Landsat-5 Thematic Mapper (TM) sensor provides the longest running continuous dataset of moderate spatial resolution remote sensing imagery, dating back to its launch in March 1984. 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 of each detector. Due to observed degradations in the IC, a new procedure was implemented for U.S.-processed data in May 2003. This new calibration procedure is based on a lifetime radiometric calibration model for the instrument's reflective bands (1-5 and 7) and is derived, in part, from the IC response without the related degradation effects and is tied to the cross calibration with the Landsat-7 Enhanced Thematic Mapper Plus. Reflective-band absolute radiometric accuracy of the instrument tends to be on the order of 7% to 10%, based on a variety of calibration methods.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2004

Landsat-7 ETM+ on-orbit reflective-band radiometric stability and absolute calibration

Launched in April 1999, the Landsat-7 Enhanced Thematic Mapper Plus (ETM+) instrument is in its sixth year of operation. The ETM+ instrument has been the most stable of any of the Landsat instruments. To date, the best onboard calibration source for the reflective bands has been the Full Aperture Solar Calibrator, a solar-diffuser-based system, which has indicated changes of between 1% to 2% per year in the ETM+ gain for bands 1-4 and 8 and less than 0.5%/year for bands 5 and 7. However, most of this change is believed to be caused by changes in the solar diffuser panel, as opposed to a change in the instrument's gain. This belief is based partially on vicarious calibrations and observations of "invariant sites", hyperarid sites of the Sahara and Arabia. Weighted average slopes determined from these datasets suggest changes of 0.0% to 0.4% per year for bands 1-4 and 8 and 0.4% to 0.5% per year for bands 5 and 7. Absolute calibration of the reflective bands of the ETM+ is consistent with vicarious observations and other sensors generally at the 5% level, though there appear to be some systematic differences.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2004

Landsat-7 ETM+ on-orbit reflective-band radiometric characterization

The Landsat-7 Enhanced Thematic Mapper Plus (ETM+) has been and continues to be radiometrically characterized using the Image Assessment System (IAS), a component of the Landsat-7 Ground System. Key radiometric properties analyzed include: overall, coherent, and impulse noise; bias stability; relative gain stability; and other artifacts. The overall instrument noise is characterized across the dynamic range of the instrument during solar diffuser deployments. Less than 1% per year increases are observed in signal-independent (dark) noise levels, while signal-dependent noise is stable with time. Several coherent noise sources exist in ETM+ data with scene-averaged magnitudes of up to 0.4 DN, and a noise component at 20 kHz whose magnitude varies across the scan and peaks at the image edges. Bit-flip noise does not exist on the ETM+. However, impulse noise due to charged particle hits on the detector array has been discovered. The instrument bias is measured every scan line using a shutter. Most bands show less than 0.1 DN variations in bias across the instrument lifetime. The panchromatic band is the exception, where the variation approaches 2 DN and is related primarily to temperature. The relative gains of the detectors, i.e., each detector's gain relative to the band average gain, have been stable to /spl plusmn/0.1% over the mission life. Two exceptions to this stability include band 2 detector 2, which dropped about 1% in gain about 3.5 years after launch and stabilized, and band 7 detector 5, which has changed several tenths of a percent several times since launch. Memory effect and scan-correlated shift, a hysteresis and a random change in bias between multiple states, respectively, both of which have been observed in previous Thematic Mapper sensors, have not been convincingly found in ETM+ data. Two artifacts, detector ringing and "oversaturation", affect a small amount of ETM+ data.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2004

In-flight validation and recovery of water surface temperature with Landsat-5 thermal infrared data using an automated high-altitude lake validation site at Lake Tahoe

The absolute radiometric accuracy of the thermal infrared band (B6) of the Thematic Mapper (TM) instrument on the Landsat-5 (L5) satellite was assessed over a period of approximately four years using data from the Lake Tahoe automated validation site (California-Nevada). The Lake Tahoe site was established in July 1999, and measurements of the skin and bulk temperature have been made approximately every 2 min from four permanently moored buoys since mid-1999. Assessment involved using a radiative transfer model to propagate surface skin temperature measurements made at the time of the L5 overpass to predict the at-sensor radiance. The predicted radiance was then convolved with the L5B6 system response function to obtain the predicted L5B6 radiance, which was then compared with the radiance measured by L5B6. Twenty-four cloud-free scenes acquired between 1999 and 2003 were used in the analysis with scene temperatures ranging between 4/spl deg/C and 22/spl deg/C. The results indicate L5B6 had a radiance bias of 2.5% (1.6/spl deg/C) in late 1999, which gradually decreased to 0.8% (0.5/spl deg/C) in mid-2002. Since that time, the bias has remained positive (predicted minus measured) and between 0.3% (0.2/spl deg/C) and 1.4% (0.9/spl deg/C). The cause for the cold bias (L5 radiances are lower than expected) is unresolved, but likely related to changes in instrument temperature associated with changes in instrument usage. The in situ data were then used to develop algorithms to recover the skin and bulk temperature of the water by regressing the L5B6 radiance and the National Center for Environmental Prediction (NCEP) total column water data to either the skin or bulk temperature. Use of the NCEP data provides an alternative approach to the split-window approach used with instruments that have two thermal infrared bands. The results indicate the surface skin and bulk temperature can be recovered with a standard error of 0.6/spl deg/C. This error is larger than errors obtained with other instruments due, in part, to the calibration bias. L5 provides the only long-duration high spatial resolution thermal infrared measurements of the land surface. If these data are to be used effectively in studies designed to monitor change, it is essential to continue to monitor instrument performance in-flight and develop quantitative algorithms for recovering surface temperature.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2008

Ocean wavenumber estimation from wave-resolving time series imagery

We review several approaches that have been used to estimate ocean surface gravity wavenumbers from wave-resolving remotely sensed image sequences. Two fundamentally different approaches that utilize these data exist. A power spectral density approach identifies wavenumbers where image intensity variance is maximized. Alternatively, a cross-spectral correlation approach identifies wavenumbers where intensity coherence is maximized. We develop a solution to the latter approach based on a tomographic analysis that utilizes a nonlinear inverse method. The solution is tolerant to noise and other forms of sampling deficiency and can be applied to arbitrary sampling patterns, as well as to full-frame imagery. The solution includes error predictions that can be used for data retrieval quality control and for evaluating sample designs. A quantitative analysis of the intrinsic resolution of the method indicates that the cross-spectral correlation fitting improves resolution by a factor of about ten times as compared to the power spectral density fitting approach. The resolution analysis also provides a rule of thumb for nearshore bathymetry retrievals-short-scale cross-shore patterns may be resolved if they are about ten times longer than the average water depth over the pattern. This guidance can be applied to sample design to constrain both the sensor array (image resolution) and the analysis array (tomographic resolution). ?? 2008 IEEE.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2010

A procedure for radiometric recalibration of Landsat 5 TM reflective-band data

From the Landsat program's inception in 1972 to the present, the Earth science user community has been benefiting 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 the L5 TM imagery used the detectors' 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%. In May 2003, the L5 TM data processed and distributed by the U.S. Geological Survey (USGS) Earth Resources Observation and Science Center through the National Landsat Archive Production System (NLAPS) were updated to use a lifetime lookup-table (LUT) gain model to radiometrically calibrate TM data instead of using scene-specific IC gains. Further modification of the gain model was performed in 2007. The L5 TM data 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 included in the original standard data product delivery is available. However, if users do not have the original work-order report, the IC trends can be used for recalibration. The IC trends were generated using the radiometric gain trends recorded in the NLAPS database. This paper provides the details of the recalibration procedure for the following: 1) data processed using IC where users have the work-order file; 2) data processed using IC where users do not have the work-order file; 3) data processed using prelaunch calibration parameters; and 4) data processed using the previous version of the LUT (e.g., LUT03) that was released before April 2, 2007.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2012

Development of the Landsat Data Continuity Mission cloud-cover assessment algorithms

The upcoming launch of the Operational Land Imager (OLI) will start the next era of the Landsat program. However, the Automated Cloud-Cover Assessment (CCA) (ACCA) algorithm used on Landsat 7 requires a thermal band and is thus not suited for OLI. There will be a thermal instrument on the Landsat Data Continuity Mission (LDCM)-the Thermal Infrared Sensor-which may not be available during all OLI collections. This illustrates a need for CCA for LDCM in the absence of thermal data. To research possibilities for full-resolution OLI cloud assessment, a global data set of 207 Landsat 7 scenes with manually generated cloud masks was created. It was used to evaluate the ACCA algorithm, showing that the algorithm correctly classified 79.9% of a standard test subset of 3.95 109 pixels. The data set was also used to develop and validate two successor algorithms for use with OLI data-one derived from an off-the-shelf machine learning package and one based on ACCA but enhanced by a simple neural network. These comprehensive CCA algorithms were shown to correctly classify pixels as cloudy or clear 88.5% and 89.7% of the time, respectively.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2012

Landsat-7 ETM+: 12 years on-orbit reflective-band radiometric performance

The Landsat-7 ETM+ sensor has been operating on orbit for more than 12 years, and characterizations of its performance have been ongoing over this period. In general, the radiometric performance of the instrument has been remarkably stable: 1) noise performance has degraded by 2% or less overall, with a few detectors displaying step changes in noise of 2% or less; 2) coherent noise frequencies and magnitudes have generally been stable, though the within-scan amplitude variation of the 20 kHz noise in bands 1 and 8 disappeared with the failure of the scan line corrector and a new similar frequency noise (now about 18 kHz) has appeared in two detectors in band 5 and increased in magnitude with time; 3) bias stability has been better than 0.25 DN out of a normal value of 15 DN in high gain; 4) relative gains, the differences in response between the detectors in the band, have generally changed by 0.1% or less over the mission, with the exception of a few detectors with a step response change of 1% or less; and 5) gain stability averaged across all detectors in a band, which is related to the stability of the absolute calibration, has been more stable than the techniques used to measure it. Due to the inability to confirm changes in the gain (beyond a few detectors that have been corrected back to the band average), ETM+ reflective band data continues to be calibrated with the prelaunch measured gains. In the worst case, some bands may have changed as much as 2% in uncompensated absolute calibration over the 12 years.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2012

Landsat 4 Thematic Mapper calibration update

The Landsat 4 Thematic Mapper (TM) collected imagery of the Earth's surface from 1982 to 1993. Although largely overshadowed by Landsat 5 which was launched in 1984, Landsat 4 TM imagery extends the TM-based record of the Earth back to 1982 and also substantially supplements the image archive collected by Landsat 5. To provide a consistent calibration record for the TM instruments, Landsat 4 TM was cross-calibrated to Landsat 5 using nearly simultaneous overpass imagery of pseudo-invariant calibration sites (PICS) in the time period of 1988-1990. To determine if the radiometric gain of Landsat 4 had changed over its lifetime, time series from two PICS locations (a Saharan site known as Libya 4 and a site in southwest North America, commonly referred to as the Sonoran Desert site) were developed. The results indicated that Landsat 4 had been very stable over its lifetime, with no discernible degradation in sensor performance in all reflective bands except band 1. In contrast, band 1 exhibited a 12% decay in responsivity over the lifetime of the instrument. Results from this paper have been implemented at USGS EROS, which enables users of Landsat TM data sets to obtain consistently calibrated data from Landsat 4 and 5 TM as well as Landsat 7 ETM+ instruments.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2013

Evaluation of ISCCP multisatellite radiance calibration for geostationary imager visible channels using the moon

Since 1983, the International Satellite Cloud Climatology Project (ISCCP) has collected Earth radiance data from the succession of geostationary and polar-orbiting meteorological satellites operated by weather agencies worldwide. Meeting the ISCCP goals of global coverage and decade-length time scales requires consistent and stable calibration of the participating satellites. For the geostationary imager visible channels, ISCCP calibration provides regular periodic updates from regressions of radiances measured from coincident and collocated observations taken by Advanced Very High Resolution Radiometer instruments. As an independent check of the temporal stability and intersatellite consistency of ISCCP calibrations, we have applied lunar calibration techniques to geostationary imager visible channels using images of the Moon found in the ISCCP data archive. Lunar calibration enables using the reflected light from the Moon as a stable and consistent radiometric reference. Although the technique has general applicability, limitations of the archived image data have restricted the current study to Geostationary Operational Environmental Satellite and Geostationary Meteorological Satellite series. The results of this lunar analysis confirm that ISCCP calibration exhibits negligible temporal trends in sensor response but have revealed apparent relative biases between the satellites at various levels. However, these biases amount to differences of only a few percent in measured absolute reflectances. Since the lunar analysis examines only the lower end of the radiance range, the results suggest that the ISCCP calibration regression approach does not precisely determine the intercept or the zero-radiance response level. We discuss the impact of these findings on the development of consistent calibration for multisatellite global data sets.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2022

Using piecewise regression to identify biological phenomena in biotelemetry datasets

1. Technological advances in the field of animal tracking have greatly expanded the potential to remotely monitor animals, opening the door to exploring how animals shift their behavior over time or respond to external stimuli. A wide variety of animal-borne sensors can provide information on an animal’s location, movement characteristics, external environmental conditions, and internal physiological status. 2. Here, we demonstrate how piecewise regression can be used to identify the presence and timing of potential shifts in a variety of biological responses using GPS telemetry and other biologging data streams. Different biological latent states can be inferred by partitioning a time-series into multiple segments based on changes in modeled responses (e.g., their mean, variance, trend, degree of autocorrelation) and specifying a unique model structure for each interval. 3. We provide six example applications highlighting a variety of taxonomic species, data streams, timescales and biological phenomena. These examples include a short-term behavioural response (flee and return) by a trumpeter swan Cygnus buccinator following a GPS collar deployment; remote identification of parturition based on movements by a pregnant moose Alces alces ; a physiological response (spike in heart-rate) in a black bear Ursus americanus to a stressful stimulus(presence of a drone); a mortality event of a trumpeter swan signalled by changes in collar temperature and overall dynamic body acceleration; an unsupervised method for identifying the onset, return, duration and staging use of sandhill crane Antigone canadensis migration; and estimation of the transition between incubation and brood-rearing (i.e. hatching) for a breeding trumpeter swan. 4. We implement analyses using the MCP package in R, which provides functionality for specifying and fitting a wide variety of user-defined model structures in a Bayesian framework and methods for assessing and comparing models using information criteria and cross-validation measures.

Journal of Animal Ecology↗
USGS2015

Classification of ephemeral, intermittent, and perennial stream reaches using a TOPMODEL-based approach

Whether a waterway is temporary or permanent influences regulatory protection guidelines, however, classification can be subjective due to a combination of factors, including time of year, antecedent moisture conditions, and previous experience of the field investigator. Our objective was to develop a standardized protocol using publicly available spatial information to classify ephemeral, intermittent, and perennial streams. Our hypothesis was that field observations of flow along the stream channel could be compared to results from a hydrologic model, providing an objective method of how these stream reaches can be identified. Flow-state sensors were placed at ephemeral, intermittent, and perennial stream reaches from May to December 2011 in the Appalachian coal basin of eastern Kentucky. This observed flow record was then used to calibrate the simulated saturation deficit in each channel reach based on the topographic wetness index used by TOPMODEL. Saturation deficit values were categorized as flow or no-flow days, and the simulated record of streamflow was compared to the observed record. The hydrologic model was more accurate for simulating flow during the spring and fall seasons. However, the model effectively identified stream reaches as intermittent and perennial in each of the two basins.

Journal of the American Water Resources Associatio↗