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At least 19 recordsLinked to original sources
USGS1997

The Greenland Sea Odden: Intra- and inter-annual variability

The "Odden" is a large sea ice feature that forms in the East Greenland Sea which generally forms at the beginning of the winter season and can cover 300,000 km2. Throughout the winter, the outer edge of the Odden may advance and retreat by several hundred kilometers on time scales of a few days to weeks. Satellite passive microwave observations from 1978 through 1995 provide a continuous record of the spatial and temporal variations of this extremely dynamic phenomenon. The 17 year record shows both strong inter- and intra-annual variations in Odden extent and temporal behavior. An analysis of the satellite passive microwave derived ice area and extent time series along with meteorological data from the Arctic Drifting Buoy Network determined the meteorological forcing required for Odden growth, maintenance and decay. The key meteorological parameters which cause the rapid ice formation and decay associated with the Odden are, in order of importance, air temperature, wind speed, and wind direction. Atmospheric pressure was found not to play a significant role in the Odden events. Air temperature and wind direction are the dominant variables with temperatures below -9.5??C and winds from the west required to trigger significant Odden ice formation events. ??2004 Copyright SPIE - The International Society for Optical Engineering.

Conference Paper↗
USGS1997

Long time-series of turbid coastal water using AVHRR: An example from Florida Bay, USA

The AVHRR can provide information on the reflectance of turbid case II water, permitting examination of large estuaries and plumes from major rivers. The AVHRR has been onboard several NOAA satellites, with afternoon overpasses since 1981, offering a long time-series to examine changes in coastal water. We are using AVHRR data starting in December 1989, to examine water clarity in Florida Bay, which has undergone a decline since the late 1980's. The processing involves obtaining a nominal reflectance for red light with standard corrections including those for Rayleigh and aerosol path radiances. Established relationships between reflectance and the water properties being measured in the Bay provide estimates of diffuse attenuation and light limitation for phytoplankton and seagrass productivity studies. Processing also includes monthly averages of reflectance and attenuation. The AVHRR data set describes spatial and temporal patterns, including resuspension of bottom sediments in the winter, and changes in water clarity. The AVHRR also indicates that Florida Bay has much higher reflectivity relative to attenuation than other southeastern US estuaries. ??2005 Copyright SPIE - The International Society for Optical Engineering.

Conference Paper↗
USGS2013

Selecting among competing models of electro-optic, infrared camera system range performance

Range performance is often the key requirement around which electro-optical and infrared camera systems are designed. This work presents an objective framework for evaluating competing range performance models. Model selection based on the Akaike’s Information Criterion (AIC) is presented for the type of data collected during a typical human observer and target identification experiment. These methods are then demonstrated on observer responses to both visible and infrared imagery in which one of three maritime targets was placed at various ranges. We compare the performance of a number of different models, including those appearing previously in the literature. We conclude that our model-based approach offers substantial improvements over the traditional approach to inference, including increased precision and the ability to make predictions for some distances other than the specific set for which experimental trials were conducted.

Optical Engineering↗
USGS2013

Landsat Data Continuity Mission, now Landsat-8: six months on-orbit

The Landsat Data Continuity Mission (LDCM) with two pushbroom Earth-imaging sensors, the Operational Land Imager (OLI) and the Thermal InfraRed Sensor (TIRS), was launched on February 11, 2013. Its on-orbit check out period or commissioning phase lasted about 90 days. During this phase the spacecraft and its instruments were activated, operationally tested and their performance verified. In addition, during this period, the spacecraft was temporarily placed in an intermediary orbit where it drifted relative to the Landsat-7 spacecraft, providing near simultaneous imaging for about 3 days, allowing data comparison and cross calibration. After this tandem-imaging period, LDCM was raised to its final altitude and placed in the position formerly occupied by Landsat-5, i.e., 8 days out of phase with Landsat-7, with about a 10:10 AM equatorial crossing time. At the end of commissioning, the satellite was transferred to the United States Geological Survey (USGS), officially renamed Landsat-8 and declared operational. Data were made available to the public beginning May 31, 2013. The performance of the satellite and two instruments has generally been excellent as evidenced in the quality of the distributed data products. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Conference Paper↗
USGS2014

On-orbit performance of the Landsat 8 Operational Land Imager

The Landsat 8 satellite was launched on February 11, 2013, to systematically collect multispectral images for detection and quantitative analysis of changes on the Earth’s surface. The collected data are stored at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and continue the longest archive of medium resolution Earth images. There are two imaging instruments onboard the satellite: the Operational Land Imager (OLI) and the Thermal InfraRed Sensor (TIRS). This paper summarizes radiometric performance of the OLI including the bias stability, the system noise, saturation and other artifacts observed in its data during the first 1.5 years on orbit. Detector noise levels remain low and Signal-To-Noise Ratio high, largely exceeding the requirements. Impulse noise and saturation are present in imagery, but have negligible effect on Landsat 8 products. Oversaturation happens occasionally, but the affected detectors quickly restore their nominal responsivity. Overall, the OLI performs very well on orbit and provides high quality products to the user community. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Conference Paper↗
USGS2010

Levels at gaging stations

Operational procedures at U.S. Geological Survey gaging stations include periodic leveling checks to ensure that gages are accurately set to the established gage datum. Differential leveling techniques are used to determine elevations for reference marks, reference points, all gages, and the water surface. The techniques presented in this manual provide guidance on instruments and methods that ensure gaging-station levels are run to both a high precision and accuracy. Levels are run at gaging stations whenever differences in gage readings are unresolved, stations may have been damaged, or according to a pre-determined frequency. Engineer’s levels, both optical levels and electronic digital levels, are commonly used for gaging-station levels. Collimation tests should be run at least once a week for any week that levels are run, and the absolute value of the collimation error cannot exceed 0.003 foot/100 feet (ft). An acceptable set of gaging-station levels consists of a minimum of two foresights, each from a different instrument height, taken on at least two independent reference marks, all reference points, all gages, and the water surface. The initial instrument height is determined from another independent reference mark, known as the origin, or base reference mark. The absolute value of the closure error of a leveling circuit must be less than or equal to 0.003√n ft, where n is the total number of instrument setups, and may not exceed |0.015| ft regardless of the number of instrument setups. Closure error for a leveling circuit is distributed by instrument setup and adjusted elevations are determined. Side shots in a level circuit are assessed by examining the differences between the adjusted first and second elevations for each objective point in the circuit. The absolute value of these differences must be less than or equal to 0.005 ft. Final elevations for objective points are determined by averaging the valid adjusted first and second elevations. If final elevations indicate that the reference gage is off by |0.015| ft or more, it must be reset.

Techniques and Methods↗
USGS2012

Profile measurements and data from the 2011 Optics, Acoustics, and Stress In Situ (OASIS) project at the Martha's Vineyard Coastal Observatory

This report documents data collected by the U.S. Geological Survey (USGS) for the Coastal Model Applications and Field Measurements project under the auspices of the U.S. Navy Office of Naval Research Optics, Acoustics, and Stress In Situ (OASIS) Project. The objective of the measurements was to relate optical and acoustic properties of suspended particles to changes in particle size, concentration, and vertical distribution in the bottom boundary layer near the seafloor caused by wave- and current-induced stresses. This information on the physics of particle resuspension and aggregation and light penetration and water clarity will help improve models of sediment transport, benthic primary productivity, and underwater visibility. There is well-established technology for acoustic profiling, but optical profiles are more difficult to obtain because of the rapid attenuation of light in water. A specially modified tripod with a moving arm was designed to solve this problem by moving instruments vertically in the bottom boundary layer, between the bottom and about 2 meters above the seafloor. The profiling arm was designed, built, and tested during spring and summer 2011 by a team of USGS scientists, engineers, and technicians. To accommodate power requirements and the large data files recorded by some of the optical instruments, the tripod was connected via underwater cable to the Martha's Vineyard Coastal Observatory, operated by the Woods Hole Oceanographic Institution (WHOI). This afforded real-time Internet communication with the embedded computers aboard the tripod. Instruments were mounted on the profiling arm, and additional instruments were mounted elsewhere on the tripod and nearby on the seafloor. The tripod and a small mooring for a profiling current meter were deployed on September 17, 2011, at the Martha's Vineyard Coastal Observatory 12-meter-deep underwater node about 2 kilometers south of Martha's Vineyard, Massachusetts. Divers assisted in the deployment and cleaned the instrument surfaces on the tripod approximately once per week until the tripod and current meter were recovered on October 23, 2011. There was a range of wave and current conditions during the 36-day deployment, including the distant passage of Hurricane Ophelia, several moderate wave events, and a significant local gale that generated wave heights greater than 4 meters at the 12-meter site and knocked over the tripod 3 days before it was recovered. All but one of the instruments functioned well and provided complete datasets. The details of these data and the location of files containing the best basic version of the data are described in this report.

Massachusetts↗
USGS2011

Early in-flight detection of SO 2 via Differential Optical Absorption Spectroscopy: A feasible aviation safety measure to prevent potential encounters with volcanic plumes

Volcanic ash constitutes a risk to aviation, mainly due to its ability to cause jet engines to fail. Other risks include the possibility of abrasion of windshields and potentially serious damage to avionic systems. These hazards have been widely recognized 5 since the early 1980s, when volcanic ash provoked several incidents of engine failure in commercial aircraft. In addition to volcanic ash, volcanic gases also pose a threat. Prolonged and/or cumulative exposure to sulphur dioxide (SO 2 ) or sulphuric acid (H 2 SO 4 ) aerosols potentially affects e.g. windows, air frame and may cause permanent damage to engines. SO 2 receives most attention among the gas species commonly found in 10 volcanic plumes because its presence above the lower troposphere is a clear proxy for a volcanic cloud and indicates that fine ash could also be present. Up to now, remote sensing of SO 2 via Differential Optical Absorption Spectroscopy (DOAS) in the ultraviolet spectral region has been used to measure volcanic clouds from ground based, airborne and satellite platforms. Attention has been given to vol- 15 canic emission strength, chemistry inside volcanic clouds and measurement procedures were adapted accordingly. Here we present a set of experimental and model results, highlighting the feasibility of DOAS to be used as an airborne early detection system of SO 2 in two spatial dimensions. In order to prove our new concept, simultaneous airborne and ground-based measurements of the plume of Popocatepetl volcano, Mexico, were conducted in April 2010. The plume extended at an altitude around 5250 m above sea level and was approached and traversed at the same altitude with several forward looking DOAS systems aboard an airplane. These DOAS systems measured SO 2 in the flight direction and at ±40 mrad (2.3◦) angles relative to it in both, horizontal and vertical directions. The approaches started at up to 25 km distance to 25 the plume and SO 2 was measured at all times well above the detection limit. In combination with radiative transfer studies, this study indicates that an extended volcanic cloud with a concentration of 1012 molecules cm−3 at typical flight levels of 10 km can be detected unambiguously at distances of up to 80 km away. This range provides enough time (approx. 5 min) for pilots to take action to avoid entering a volcanic cloud in the flight path, suggesting that this technique can be used as an effective aid to prevent dangerous aircraft encounters with potentially ash rich volcanic clouds.

Popocatepetl volcano↗
USGS1992

Planetary maps

An important goal of the USGS planetary mapping program is to systematically map the geology of the Moon, Mars, Venus, and Mercury, and the satellites of the outer planets. These geologic maps are published in the USGS Miscellaneous Investigations (I) Series. Planetary maps on sale at the USGS include shaded-relief maps, topographic maps, geologic maps, and controlled photomosaics. Controlled photomosaics are assembled from two or more photographs or images using a network of points of known latitude and longitude. The images used for most of these planetary maps are electronic images, obtained from orbiting television cameras, various optical-mechanical systems. Photographic film was only used to map Earth's Moon.

General Information Product↗
USGS1986

Mass storage estimates for the digital mapping era.

Proponents of the digital era recognize that a break-through in mass storage technology may be required to attain a reasonable degree of computerization of the cartographic mapping and data management process. This paper provides the rationale for estimating that about 1014 bits of digital mass storage are needed for developing a digital 1:24 000-scale topographic data base of the US. Also, it will discuss the optical disk as a leading candidate for handling the mass storage dilemma.-from Author

Photogrammetric Engineering and Remote Sensing↗
USGS2022

CoastalImageLib: An open-source Python package for creating common coastal image products

CoastalImageLib is a Python library that produces common coastal image products intended for quantitative analysis of coastal environments. This library contains functions to georectify and merge multiple oblique camera views, produce statistical image products for a given set of images, and create subsampled pixel instruments for use in bathymetric inversion, surface current estimation, run-up calculations, and other quantitative analyses. This package intends to be an open-source broadly generalizable front end to future coastal imaging applications, ultimately expanding user accessibility to optical remote sensing of coastal environments. This package was developed and tested on data collected from the Argus Tower, a 43 m tall observation structure in Duck, North Carolina at the US Army Engineer Research and Development Center’s Field Research Facility that holds six stationary cameras which collect twice-hourly coastal image products. Thus, CoastalImageLib also contains functions designed to interface with the file storage and collection system implemented at the Argus Tower.

SoftwareX↗
USGS1983

The relationship of acquisition systems to automated stereo correlation.

Today a concerted effort is being made to expedite the mapping process through automated correlation of stereo data. Stereo correlation involves the comparison of radiance (brightness) signals or patterns recorded by sensors. Conventionally, two-dimensional area correlation is utilized but this is a rather slow and cumbersome procedure. Digital correlation can be performed in only one dimension where suitable signal patterns exist, and the one-dimensional mode is much faster. Electro-optical (EO) systems, suitable for space use, also have much greater flexibility than film systems. Thus, an EO space system can be designed which will optimize one-dimensional stereo correlation and lead toward the automation of topographic mapping.-from Author

Photogrammetric Engineering and Remote Sensing↗
USGS2009

Multi-temporal RADARSAT-1 and ERS backscattering signatures of coastal wetlands in southeastern Louisiana

Using multi-temporal European Remote-sensing Satellites (ERS-1/-2) and Canadian Radar Satellite (RADARSAT-1) synthetic aperture radar (SAR) data over the Louisiana coastal zone, we characterize seasonal variations of radar backscat-tering according to vegetation type. Our main findings are as follows. First, ERS-1/-2 and RADARSAT-1 require careful radiometric calibration to perform multi-temporal backscattering analysis for wetland mapping. We use SAR backscattering signals from cities for the relative calibration. Second, using seasonally averaged backscattering coefficients from ERS-1/-2 and RADARSAT-1, we can differentiate most forests (bottomland and swamp forests) and marshes (freshwater, intermediate, brackish, and saline marshes) in coastal wetlands. The student t-test results support the usefulness of season-averaged backscatter data for classification. Third, combining SAR backscattering coefficients and an optical-sensor-based normalized difference vegetation index can provide further insight into vegetation type and enhance the separation between forests and marshes. Our study demonstrates that SAR can provide necessary information to characterize coastal wetlands and monitor their changes.

Photogrammetric Engineering and Remote Sensing↗
USGS2006

Hydratools manual version 1.0, documentation for a MATLAB ® -based post-processing package for the Sontek Hydra

The Sediment Transport Instrumentation Group (STG) at the U.S. Geological Survey (USGS) Woods Hole Science Center has a long-standing comitment to providing scientists with high quality oceanographic data. To meet this commitment, STG personnel are vigilant in checking data as well as hardware for signs of instrument malfunction. STG data sets are accompanied by processing histories to detail data processing procedures that may have modified the natural data signal while removing noise from the data. The history also allows the data to be reprocessed in the ligth of new insight into instrument function and moored conditions. This toolbox was compiled to meet these data quality commitments for data generated by Sontek Hydra systems using both ADV and PCADP probes. In the mid 1900's, the USGS Coastal and Marine Program began frequent deployments of Sontek Hydra systems in support of projects in estuaries, coastal, and continental shelf regions nationwide. Hydra data sets are large and complex in structure, and existing processing and editing tools consisted of fragments of MATLAB code written by USGS scientists to satisfy personal research needs. This code did not meet STG quality control criteria. This toolbox permits engineers and scientists to monitor data quality by: 1. processing data with interactive critical review; 2. preserving data quality indicators; 3. preserving minimally processed and partially processed versions of data sets. STG usually deploys ADV and PCADP probes configured as downward looking, mounted on bottom tripods, with the objective of measuring high-resolution near-bed currents. The velocity profiles are recorded with minimal internal data processing. Also recorded are parameters such as temperature, conductivity, optical backscatter, light transmission, and high frequency pressure. Sampling consists of high-frequency bursts(1–10 Hz) bursts of long duration (5–30 minutes) at regular and recurring intervals for a duration of 1 to 6 months. The result is very large data files, often 500 MB per Hydra, per deployment, in Sontek's compressed binary format. This section introduces the Hydratools toolbox and provides information about the history of the system's development. The USGS philosophy regarding data quality is discussed to provide an understating of the motivation for creating the system. General information about the following topics will also be discussed: hardware and software required for the system, basic processing steps, limitations of program usage, and features that are unique to the programs.

Open-File Report↗
USGS2009

Optical satellite data volcano monitoring: a multi-sensor rapid response system

In this chapter, the use of satellite remote sensing to monitor active geological processes is described. Specifically, threats posed by volcanic eruptions are briefly outlined, and essential monitoring requirements are discussed. As an application example, a collaborative, multi-agency operational volcano monitoring system in the north Pacific is highlighted with a focus on the 2007 eruption of Kliuchevskoi volcano, Russia. The data from this system have been used since 2004 to detect the onset of volcanic activity, support the emergency response to large eruptions, and assess the volcanic products produced following the eruption. The overall utility of such integrative assessments is also summarized. The work described in this chapter was originally funded through two National Aeronautics and Space Administration (NASA) Earth System Science research grants that focused on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument. A skilled team of volcanologists, geologists, satellite tasking experts, satellite ground system experts, system engineers and software developers collaborated to accomplish the objectives. The first project, Automation of the ASTER Emergency Data Acquisition Protocol for Scientific Analysis, Disaster Monitoring, and Preparedness , established the original collaborative research and monitoring program between the University of Pittsburgh (UP), the Alaska Volcano Observatory (AVO), the NASA Land Processes Distributed Active Archive Center (LP DAAC) at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, and affiliates on the ASTER Science Team at the Jet Propulsion Laboratory (JPL) as well as associates at the Earth Remote Sensing Data Analysis Center (ERSDAC) in Japan. This grant, completed in 2008, also allowed for detailed volcanic analyses and data validation during three separate summer field campaigns to Kamchatka Russia. The second project, Expansion and synergistic use of the ASTER Urgent Request Protocol (URP) for natural disaster monitoring and scientific analysis , has expanded the project to other volcanoes around the world and is in progress through 2011. The focus on ASTER data is due to the suitability of the sensor for natural disaster monitoring and the availability of data. The instrument has several unique facets that make it especially attractive for volcanic observations (Ramsey and Dehn, 2004). Specifically, ASTER routinely collects data at night, it has the ability to generate digital elevation models using stereo imaging, it can collect data in various gain states to minimize data saturation, it has a cross-track pointing capability for faster targeting, and it collects data up to ±85° latitude for better global coverage. As with any optical imaging-based remote sensing, the viewing conditions can negatively impact the data quality. This impact varies across the optical and thermal infrared wavelengths as well as being a function of the specific atmospheric window within a given wavelength region. Water vapor and cloud formation can obscure surface data in the visible and near infrared (VNIR)/shortwave infrared (SWIR) region due mainly to non-selective scattering of the incident photons. In the longer wavelengths of the thermal infrared (TIR), scattering is less of an issue, but heavy cloud cover can still obscure the ground due to atmospheric absorption. Thin clouds can be optically-transparent in the VNIR and TIR regions, but can cause errors in the extracted surface reflectance or derived surface temperatures. In regions prone to heavy cloud cover, optical remote sensing can be improved through increased temporal resolution. As more images are acquired in a given time period the chances of a clear image improve dramatically. The Advanced Very High Resolution Radiometer (AVHRR) routine monitoring, which commonly collects 4-6 images per day of any north Pacific volcano, takes advantage of this fact. The rapid response program described in this chapter also improves the temporal resolution of the ASTER instrument. ASTER has been acquiring images of volcanic eruptions since soon after its launch in December 1999. An early example included the observations of the large pyroclastic flow deposit emplaced at Bezymianny volcano in Kamchatka, Russia. The first images in March 2000, just weeks after the eruption, revealed the extent, composition, and cooling history of this large deposit and of the active lava dome (Ramsey and Dehn, 2004). The initial results from these early datasets spurred interest in using ASTER data for expanded volcano monitoring in the north Pacific. It also gave rise to the multi-year NASA-funded programs of rapid response scheduling and imaging throughout the Aleutian, Kamchatka and Kurile arcs. Since the formal establishment of the programs, the data have provided detailed descriptions of the eruptions of Augustine, Bezymianny, Kliuchevskoi and Sheveluch volcanoes over the past nine years (Wessels et al., in press; Carter et al., 2007, 2008; Ramsey et al., 2008; Rose and Ramsey, 2009). The initial research focus of this rapid response program was specifically on automating the ASTER sensor’s ability for targeted observational scheduling using the expedited data system. This urgent request protocol is one of the unique characteristics of ASTER. It provides a limited number of emergency observations, typically at a much-improved temporal resolution and quicker turnaround with data processing in the United States rather than in Japan. This can speed the reception of the processed data by several days to a week. The ongoing multi-agency research and operational collaboration has been highly successful. AVO serves as the primary source for status information on volcanic activity, working closely with the National Weather Service (NWS), Federal Aviation Administration (FAA), military and other state and federal emergency services. Collaboration with the Russian Institute of Volcanology and Seismology (IVS)/Kamchatka Volcanic Eruption Response Team (KVERT) is also maintained. Once a volcano is identified as having increased thermal output, ASTER is automatically tasked and the volcano is targeted at the next available opportunity. After the data are acquired, scientists at all the agencies have access to the images, with the primary science analysis carried out at the University of Pittsburgh and AVO. Results are disseminated to the responsible monitoring agencies and the global community through e-mail mailing lists.

Book chapter↗
USGS2004

An evaluation of gap-filled Landsat SLC-off imagery for wildland fire burn severity mapping

n May 31, 2003 unusual artifacts appeared within image data collected by the Enhanced Thematic Mapper plus (ETM+) instrument on-board the Landsat 7 spacecraft. The U.S. Geological Survey (USGS), with the support of NASA, has been working to find a means of compensating for the data gaps that result from a failure of the instrument’s scan line corrector (SLC). The SLC is an electromechanical device that compensates for the forward motion of the spacecraft by modifying the instrument’s optical path. The problem is likely due to a mechanical failure of the device for which there is no redundancy and that cannot be repaired or coaxed back into service. Further information regarding Landsat 7 and the SLC failure can be found at the Landsat Project home page (http://landsat7.usgs.gov).

Photogrammetric Engineering and Remote Sensing↗
USGS2022

DSWEmod - The production of high-frequency surface water map composites from daily MODIS images

Optical satellite imagery is commonly used for monitoring surface water dynamics, but clouds and cloud shadows present challenges in assembling complete water time series. To test whether the daily revisit rate of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery can reduce cloud obstruction and improve high-frequency surface water mapping, we compared map results derived from Landsat (30-m) and MODIS (250-m) data across the state of California for 2003–2019. We adapted the Dynamic Surface Water Extent (DSWE) model in Google Earth Engine to generate surface water map composites from MODIS imagery every 5, 10, 15, and 30 days, and compared products to monthly Landsat-based DSWE maps. Results for DSWEmod (DSWE MODIS) in California suggest that more than 5% data loss (cloud obstruction, etc.) was present in only 2% of the 15-day time series, as compared to 32% of the monthly Landsat DSWE time series. The five-day DSWEmod composites averaged 8.4% obscuration in the winter months. Area estimates derived from cloud-filtered MODIS and Landsat monthly products have the highest linear correlations compared to streamgage discharge records, suggesting that monthly scale analyses best explain the relationship between surface water area and general streamflow dynamics. Shorter-interval DSWEmod products have lower correlations but utility for understanding the timing of surface water peaks and past flood events.

Journal of the American Water Resources Associatio↗