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At least 1,189 records · Page 66Linked to original sources
USGS1995

Comparison of BASS and VACM current measurements during STRESS

Current measurements from a vector-averaging current meter (VACM) on a subsurface mooring and a benthic acoustic stress sensor (BASS) on a bottom tripod are compared to assess their relative accuracy. The instruments were deployed off northern California at a midshelf site (water depth approximately 90 m) as part of the STRESS (Sediment Transport Events on Shelves and Slopes) field program. The subsurface mooring and bottom tripod were within a few hundred meters of each other, with the BASS 5.0 m and the VACM 6.7 m above the bottom, during two tripod deployments of 49 and 32 days in the winter of 1988/89. Speed differences between the VACM and BASS current observations have a mean of 0.2 cm s −1 and a standard deviation of 1.2 cm s −1 . If the mean speed profile is logarithmic, the expected mean speed difference due to the vertical separation is about 0.4 cm s −1 . The average speed difference between the VACM and BASS increases as near-bottom wave orbital velocities get large relative to hourly averaged currents, consistent with laboratory studies of VACMs in oscillating flows. Direction differences have a mean of 1° and standard deviations of about 5° for speeds greater than 10 cm s −1 . The relative accuracy of the corresponding velocity measurements is ±2 cm s −1 (mean differences less than 0.6 cm s −1 and standard deviations of about 1 cm s −1 ). The equations used to convert VACM rotor rotation rates to current speed we based on a calibration study by Woodward and Appell rather than one based on a study by Cherriman that is routinely used at the Woods Hole Oceanographic Institution. The former yields closer agreement between the BASS and VACM speed measurements during STRESS (mean speed difference 0.2 cm s −1 versus 1.4 cm s −1 ).

Journal of Atmospheric and Oceanic Technology↗
USGS1996

Preflight and in-flight calibration plan for ASTER

Preflight and in-flight radiometric calibration plans are described for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) that is a multispectral optical imager of high spatial resolution. It is designed for the remote sensing from orbit of land surfaces and clouds, and is expected to be launched in 1998 on NASA's EOS AM-I spacecraft. ASTER acquires images in three separate spectral regions, the visible and near-infrared (VNIR), the shortwave infrared (SWIR), and the thermal infrared (TIR) with three imaging radiometer subsystems. The absolute radiometric accuracy is required to be better than 4% for VNIR and SWIR radiance measurements and 1 to 3 K, depending on the temperature regions from 200 to 370 K, for TIR temperature measurements. A reference beam is introduced at the entrance pupil of each imaging radiometer to provide the in-flight calibration. Thus, the ASTER instrument includes internal onboard calibration units that comprise incandescent lamps for the VNIR and SWIR and a blackbody radiator for the TIR as reference sources. The calibration reliability of the VNIR and SWIR is enhanced by a dual system of onboard calibration units as well as by high-stability halogen lamps. A ground calibration system of spectral radiances traceable to fixed-point blackbodies is used for the preflight VNIR and SWIR calibration. Because of the possibility of nonuniform contamination effects on the partial-aperture onboard calibration, it is desirable to check their results with respect to other methods. Reflectance- and radiance-based vicarious methods have been developed for this purpose. These, and methods involving in-flight cross-calibration with other sensors are also described.

Journal of Atmospheric and Oceanic Technology↗
USGS1997

Estimation of directional surface wave spectra from a towed research catamaran

During the High-Resolution Remote Sensing Main Experiment (1993), wave height was estimated from a moving catamaran using pitch-rate and roll-rate sensors, a three-axis accelerometer, and a capacitive wave wire. The wave spectrum in the frequency band ranging roughly from 0.08 to 0.3 Hz was verified by independent buoy measurements. To estimate the directional frequency spectrum from a wave-wire array, the Data-Adaptive Spectral Estimator is extended to include the Doppler shifting effects of a moving platform. The method is applied to data obtained from a fixed platform during the Risø Air–Sea Experiment (1994) and to data obtained from a moving platform during the Coastal Ocean Processes Experiment (1995). Both results show that the propagation direction of the peak wind waves compares well with the measured wind direction. When swells and local wind waves are not aligned, the method can resolve the difference of propagation directions. Using the fixed platform data a numerical test is conducted that shows that the method is able to distinguish two wave systems propagating at the same frequency but in two different directions.

Journal of Atmospheric and Oceanic Technology↗
USGS2002

Design and performance of a horizontal mooring for upper-ocean research

This paper describes the design and performance of a two-dimensional moored array for sampling horizontal variability in the upper ocean. The mooring was deployed in Massachusetts Bay in a water depth of 84 m for the purpose of measuring the horizontal structure of internal waves. The mooring was instrumented with three acoustic current meters (ACMs) spaced along a 170-m horizontal cable that was stretched between two subsurface buoys 20 m below the sea surface. Five 25-m-long vertical instrument strings were suspended from the horizontal cable. A bottom-mounted acoustic Doppler current profiler (ADCP) was deployed nearby to measure the current velocity throughout the water column. Pressure sensors mounted on the subsurface buoys and the vertical instrument strings were used to measure the vertical displacements of the array in response to the currents. Measurements from the ACMs and the ADCP were used to construct time-dependent, two-dimensional current fields. The current fields were used as input to a numerical model that calculated the deformation of the array with respect to the nominal zero-current configuration. Comparison of the calculated vertical offsets of the downstream subsurface buoy and downstream vertical instrument string with the pressure measurements were used to verify the numerical code. These results were then used to estimate total deformation of the array due to the passage of the internal waves. Based on the analysis of the three internal wave events with the highest measured vertical offsets, it is concluded that the geometry of the main structure (horizontal cable and anchor legs) was kept to within ±2.0 m, and the geometry of the vertical instrument strings was kept to within ±4.0 m except for one instance when the current velocity reached 0.88 m s −1 .

Massachusetts↗
USGS2008

Meteorological characteristics and overland precipitation impacts of atmospheric rivers affecting the West coast of North America based on eight years of SSM/I satellite observations

The pre-cold-frontal low-level jet within oceanic extratropical cyclones represents the lower-tropospheric component of a deeper corridor of concentrated water vapor transport in the cyclone warm sector. These corridors are referred to as atmospheric rivers (ARs) because they are narrow relative to their length scale and are responsible for most of the poleward water vapor transport at midlatitudes. This paper investigates landfalling ARs along adjacent north- and south-coast regions of western North America. Special Sensor Microwave Imager (SSM/ I) satellite observations of long, narrow plumes of enhanced integrated water vapor (IWV) were used to detect ARs just offshore over the eastern Pacific from 1997 to 2005. The north coast experienced 301 AR days, while the south coast had only 115. Most ARs occurred during the warm season in the north and cool season in the south, despite the fact that the cool season is climatologically wettest for both regions. Composite SSM/I IWV analyses showed landfalling wintertime ARs extending northeastward from the tropical eastern Pacific, whereas the summertime composites were zonally oriented and, thus, did not originate from this region of the tropics. Companion SSM/I composites of daily rainfall showed significant orographic enhancement during the landfall of winter (but not summer) ARs. The NCEP-NCAR global reanalysis dataset and regional precipitation networks were used to assess composite synoptic characteristics and overland impacts of landfalling ARs. The ARs possess strong vertically integrated horizontal water vapor fluxes that, on average, impinge on the West Coast in the pre-cold-frontal environment in winter and post-cold-frontal environment in summer. Even though the IWV in the ARs is greater in summer, the vapor flux is stronger in winter due to much stronger flows associated with more intense storms. The landfall of ARs in winter and north-coast summer coincides with anomalous warmth, a trough offshore, and ridging over the Intermountain West, whereas the south-coast summer ARs coincide with relatively cold conditions and a near-coast trough. ARs have a much more profound impact on near-coast precipitation in winter than summer, because the terrain-normal vapor flux is stronger and the air more nearly saturated in winter. During winter, ARs produce roughly twice as much precipitation as all storms. In addition, wintertime ARs with the largest SSM/I IWV are tied to more intense storms with stronger flows and vapor fluxes, and more precipitation. ARs generally increase snow water equivalent (SWE) in autumn/winter and decrease SWE in spring. On average, wintertime SWE exhibits normal gains during north-coast AR storms and above-normal gains during the south-coast AR storms. The north-coast sites are mostly lower in altitude, where warmer-than-normal conditions more frequently yield rain. During those events when heavy rain from a warm AR storm falls on a preexisting snowpack, flooding is more likely to occur. ?? 2008 American Meteorological Society.

Journal of Hydrometeorology↗
USGS2007

Enhancing water cycle measurements for future hydrologic research

The Consortium of Universities for the Advancement of Hydrologic Sciences, Inc., established the Hydrologic Measurement Facility to transform watershed-scale hydrologic research by facilitating access to advanced instrumentation and expertise that would not otherwise be available to individual investigators. We outline a committee-based process that determined which suites of instrumentation best fit the needs of the hydrological science community and a proposed mechanism for the governance and distribution of these sensors. Here, we also focus on how these proposed suites of instrumentation can be used to address key scientific challenges, including scaling water cycle science in time and space, broadening the scope of individual subdisciplines of water cycle science, and developing mechanistic linkages among these subdisciplines and spatio-temporal scales. ?? 2007 American Meteorological Society.

Bulletin of the American Meteorological Society↗
USGS2013

Tracking animals in freshwater with electronic tags: past, present and future

Considerable technical developments over the past half century have enabled widespread application of electronic tags to the study of animals in the wild, including in freshwater environments. We review the constraints associated with freshwater telemetry and biologging and the technical developments relevant to their use. Technical constraints for tracking animals are often influenced by the characteristics of the animals being studied and the environment they inhabit. Collectively, they influence which and how technologies can be used and their relative effectiveness. Although radio telemetry has historically been the most commonly used technology in freshwater, passive integrated transponder (PIT) technology, acoustic telemetry and biologgers are becoming more popular. Most telemetry studies have focused on fish, although an increasing number have focused on other taxa, such as turtles, crustaceans and molluscs. Key technical developments for freshwater systems include: miniaturization of tags for tracking small-size life stages and species, fixed stations and coded tags for tracking large samples of animals over long distances and large temporal scales, inexpensive PIT systems that enable mass tagging to yield population- and community-level relevant sample sizes, incorporation of sensors into electronic tags, validation of tag attachment procedures with a focus on maintaining animal welfare, incorporation of different techniques (for example, genetics, stable isotopes) and peripheral technologies (for example, geographic information systems, hydroacoustics), development of novel analytical techniques, and extensive international collaboration. Innovations are still needed in tag miniaturization, data analysis and visualization, and in tracking animals over larger spatial scales (for example, pelagic areas of lakes) and in challenging environments (for example, large dynamic floodplain systems, under ice). There seems to be a particular need for adapting various global positioning system and satellite tagging approaches to freshwater. Electronic tagging provides a mechanism to collect detailed information from imperilled animals and species that have no direct economic value. Current and future advances will continue to improve our knowledge of the natural history of aquatic animals and ecological processes in freshwater ecosystems while facilitating evidence-based resource management and conservation.

Animal Biotelemetry↗
USGS2013

The environmental-data automated track annotation (Env-DATA) system: linking animal tracks with environmental data

The movement of animals is strongly influenced by external factors in their surrounding environment such as weather, habitat types, and human land use. With advances in positioning and sensor technologies, it is now possible to capture animal locations at high spatial and temporal granularities. Likewise, scientists have an increasing access to large volumes of environmental data. Environmental data are heterogeneous in source and format, and are usually obtained at different spatiotemporal scales than movement data. Indeed, there remain scientific and technical challenges in developing linkages between the growing collections of animal movement data and the large repositories of heterogeneous remote sensing observations, as well as in the developments of new statistical and computational methods for the analysis of movement in its environmental context. These challenges include retrieval, indexing, efficient storage, data integration, and analytical techniques.

Movement Ecology↗
USGS2018

Towards coordinated regional multi-satellite InSAR volcano observations: Results from the Latin America pilot project

Within Latin America, about 319 volcanoes have been active in the Holocene, but 202 of these volcanoes have no seismic, deformation or gas monitoring. Following the 2012 Santorini Report on satellite Earth Observation and Geohazards, the Committee on Earth Observation Satellites (CEOS) developed a 4-year pilot project (2013-2017) to demonstrate how satellite observations can be used to monitor large numbers of volcanoes cost-effectively, particularly in areas with scarce instrumentation and/or difficult access. The pilot aims to improve disaster risk management (DRM) by working directly with the volcano observatories that are governmentally responsible for volcano monitoring as well as with the international space agencies (ESA, CSA, ASI, DLR, JAXA, NASA, CNES). The goal is to make sure that the most useful data are collected at each volcano following the guidelines of the Santorini report that observation frequency is related to volcano activity, and to communicate the results to the local institutions in a timely fashion. Here we highlight how coordinated multi-satellite observations have been used by volcano observatories to monitor volcanoes and respond to crises. Our primary tool is measurements of ground deformation made by Interferometric Synthetic Aperture Radar (InSAR), which have been used in conjunction with other observations to determine the alert level at these volcanoes, served as an independent check on ground sensors, guided the deployment of ground instruments, and aided situational awareness. During this time period, we find 26 volcanoes deforming, including 18 of the 28 volcanoes that erupted - those eruptions without deformation were less than 2 on the VEI scale. Another 7 volcanoes were restless and the volcano observatories requested satellite observations, but no deformation was detected. We describe the lessons learned about the data products and information that are most needed by the volcano observatories in the different countries using information collected by questionnaires. We propose a practical strategy for regional to global satellite volcano monitoring for use by volcano observatories in Latin America and elsewhere to realize the vision of the Santorini report.

Journal of Applied Volcanology↗
USGS2021

Drivers of realized satellite tracking duration in marine turtles

Background Satellite tags have revolutionized our understanding of marine animal movements. However, tags may stop transmitting for many reasons and little research has rigorously examined tag failure. Using a long-term, large-scale, multi-species dataset, we evaluated factors influencing tracking duration of satellite tags to inform study design for future tracking studies. Methods We leveraged data on battery status transmitted with location data, recapture events, and number of transmission days to probabilistically quantify multiple potential causes of failure (i.e., battery failure, premature detachment, and tag damage/fouling). We used a combination of logistic regressions and an ordinary linear model including several predictor variables (i.e., tag type, battery life, species, sex, size, and foraging region). Results We examined subsets of data from 360 satellite tags encompassing 86,889 tracking days deployed on four species of marine turtles throughout the Gulf of Mexico, Caribbean, and Bahamas from 2008 to 2019. Only 4.1% of batteries died before failure due to other causes. We observed species-specific variation in how long tags remain attached: hawksbills retained 50% of their tags for 1649 days (95% CI 995–1800), loggerheads for 584 days (95% CI 400–690), and green turtles for 294 days (95% CI 198–450). Estimated tracking duration varied by foraging region (Caribbean: 385 days; Bahamas: 356; southern Gulf of Mexico [SGOM]: 276, northern Gulf of Mexico [NGOM]: 177). Additionally, we documented species-specific variation in estimated tracking duration among foraging regions. Based on sensor data, within the Gulf of Mexico, across species, we estimated that 50% of tags began to foul after 83 95% CI (70–120) days. Conclusions The main factor that limited tracking duration was tag damage (i.e., fouling and/or antenna breakage). Turtles that spent most of their time in the Gulf of Mexico had shorter tracking durations than those in the Bahamas and Caribbean, with shortest durations observed in the NGOM. Additionally, tracking duration varied by species, likely as a result of behaviors that damage tags. This information will help researchers, tag companies, permitting agencies, and funders better predict expected tracking durations, improving study designs for imperiled marine turtles. Our results highlight the heterogeneity in telemetry device longevity, and we provide a framework for researchers to evaluate telemetry devices with respect to their study objectives.

Alabama, Florida, Louisiana, Mississippi, Texas↗
USGS2024

A benchmark for computational analysis of animal behavior, using animal-borne tags

Background Animal-borne sensors (‘bio-loggers’) can record a suite of kinematic and environmental data, which are used to elucidate animal ecophysiology and improve conservation efforts. Machine learning techniques are used for interpreting the large amounts of data recorded by bio-loggers, but there exists no common framework for comparing the different machine learning techniques in this domain. This makes it difficult to, for example, identify patterns in what works well for machine learning-based analysis of bio-logger data. It also makes it difficult to evaluate the effectiveness of novel methods developed by the machine learning community. Methods To address this, we present the Bio-logger Ethogram Benchmark (BEBE), a collection of datasets with behavioral annotations, as well as a modeling task and evaluation metrics. BEBE is to date the largest, most taxonomically diverse, publicly available benchmark of this type, and includes 1654 h of data collected from 149 individuals across nine taxa. Using BEBE, we compare the performance of deep and classical machine learning methods for identifying animal behaviors based on bio-logger data. As an example usage of BEBE, we test an approach based on self-supervised learning. To apply this approach to animal behavior classification, we adapt a deep neural network pre-trained with 700,000 h of data collected from human wrist-worn accelerometers. Results We find that deep neural networks out-perform the classical machine learning methods we tested across all nine datasets in BEBE. We additionally find that the approach based on self-supervised learning out-performs the alternatives we tested, especially in settings when there is a low amount of training data available. Conclusions In light of these results, we are able to make concrete suggestions for designing studies that rely on machine learning to infer behavior from bio-logger data. Therefore, we expect that BEBE will be useful for making similar suggestions in the future, as additional hypotheses about machine learning techniques are tested. Datasets, models, and evaluation code are made publicly available at https://github.com/earthspecies/BEBE , to enable community use of BEBE.

Movement Ecology↗
USGS2025

Near real-time indicators of burn severity in the western U.S. from active fire tracking

Background Timely information on wildfire burn severity is critical to assess and mitigate potential post-fire impacts on soils, vegetation, and hillslope stability. Tracking individual fire spread and intensity using satellite active fire data provides a pathway to near real-time (NRT) information. Here, we generated a large database ( n = 2177) of wildfire events in the western United States (U.S.) between 2012 and 2021 using active fire detections from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (SNPP) satellite and the Fire Events Data Suite (FEDS) algorithm to track large fire growth every 12 h. We integrated fire tracking data with final fire perimeters and burn severity data from the Monitoring Trends in Burn Severity (MTBS) program to evaluate the relationship between burn severity and fire behavior metrics derived from the fire tracking approach, including the rate of fire spread and average fire radiative power (FRP) of fire detections for each 12-h growth increment. Results When stratified by vegetation type, FRP and rate of spread metrics were positively correlated with classified burn severity for each 12-h growth increment, highlighting the potential to rapidly identify areas of high and low severity burning. In forests, integrated measures of FRP over the fire lifetime captured persistent flaming and smoldering that compensated for initial differences between AM (01:30) and PM (13:30) fire detections. Predictive modeling of these relationships based on multiple fire behavior indicators and vegetation type from the LANDFIRE program yielded an accuracy of 78% for the separation of unburned/low and moderate/high burn severity classes. Conclusions These results demonstrate the ability to capture within-fire differences in burn severity using NRT indicators from fire tracking to assist with emergency management and disaster preparedness for post-fire hazards, such as landslides, debris flows, or changes in stream flow and water quality. As VIIRS data are available within minutes of each satellite overpass in the U.S., rapid estimates of burn severity based on fire tracking can be made days or weeks before a large wildfire is fully contained.

western United States↗
USGS2008

Towards continuous 4D microgravity monitoring of volcanoes

Four-dimensional or time-lapse microgravity monitoring has been used effectively on volcanoes for decades to characterize the changes in subsurface volcanic systems. With measurements typically lasting from a few days to weeks and then repeated a year later, the spatial resolution of theses studies is often at the expense of temporal resolution and vice versa. Continuous gravity studies with one to two instruments operating for a short period of time (weeks to months) have shown enticing evidence of very rapid changes in the volcanic plumbing system (minutes to hours) and in one case precursory signals leading to eruptive activity were detected. The need for true multi-instrument networks is clear if we are to have both the temporal and spatial reso-lution needed for effective volcano monitoring. However, the high cost of these instruments is currently limiting the implementation of continuous microgravity networks. An interim approach to consider is the development of a collaborative network of researchers able to bring multiple instruments together at key volcanoes to investigate multitemporal physical changes in a few type volcanoes. However, to truly move forward, it is imperative that new low-cost instruments are developed to increase the number of instruments available at a single site. Only in this way can both the temporal and spatial integrity of monitoring be maintained. Integration of these instruments into a multiparameter network of continuously recording sensors is essential for effective volcano monitoring and hazard mitigation.

Geophysics↗
USGS2016

Dense surface seismic data confirm non-double-couple source mechanisms induced by hydraulic fracturing

We have determined source mechanisms for nine high-quality microseismic events induced during hydraulic fracturing of the Montney Shale in Canada. Seismic data were recorded using a dense regularly spaced grid of sensors at the surface. The design and geometry of the survey are such that the recorded P-wave amplitudes essentially map the upper focal hemisphere, allowing the source mechanism to be interpreted directly from the data. Given the inherent difficulties of computing reliable moment tensors (MTs) from high-frequency microseismic data, the surface amplitude and polarity maps provide important additional confirmation of the source mechanisms. This is especially critical when interpreting non-shear source processes, which are notoriously susceptible to artifacts due to incomplete or inaccurate source modeling. We have found that most of the nine events contain significant non-double-couple (DC) components, as evident in the surface amplitude data and the resulting MT models. Furthermore, we found that source models that are constrained to be purely shear do not explain the data for most events. Thus, even though non-DC components of MTs can often be attributed to modeling artifacts, we argue that they are required by the data in some cases, and can be reliably computed and confidently interpreted under favorable conditions.

Geophysics↗
USGS2025

Drone-based radiometric surveys provide high-resolution mine waste characterization

Airborne radiometric surveys use passive geophysical techniques to characterize geochemical variations at or near earth’s surface. These methods have been used for a variety of mapping applications, including mineral resource evaluation. However, detailed characterization of smaller geologic targets, including mine waste features, requires flying at lower altitudes and with tighter line spacing than is feasible with traditional aircraft. Here, a small uncrewed aircraft system (sUAS) equipped with a radiometric sensor was used to acquire high-resolution gamma-spectrometry over small mine waste features and a low-grade stockpile in southwestern New Mexico. The sUAS radiometric system mapped local variability within each survey area and revealed ~2–10 m wide zones where radioelements K, Th, and U may be elevated 2–10× the surrounding material. Additionally, the sUAS radiometric data revealed radioelement variability across survey sites, which correlated reasonably well with variability seen in geochemical samples at each survey site, even though samples collected from individual sites showed high local variability. The sUAS data characterized local heterogeneity within mine waste and other small geologic targets at scales of a few meters to tens of meters, which is not possible with traditional crewed aircraft, and with continuity of coverage that is not possible with ground surveys, thus filling a key gap in geophysical survey spatial resolution.

New Mexico↗
USGS1997

Models and methods to characterize site amplification from a pair of records

The paper presents a tutorial review of the models and methods that are used to characterize site amplification from the pairs of rock- and soil-site records, and introduces some new techniques with better theoretical foundations. The models and methods discussed include spectral and cross-spectral ratios, spectral ratios for downhole records, response spectral ratios, constant amplification factors, parametric models, physical models, and time-varying filters. An extensive analytical and numerical error analysis of spectral and cross-spectral ratios shows that probabilistically cross-spectral ratios give more reliable estimates of site amplification. Spectral ratios should not be used to determine site amplification from downhole-surface recording pairs because of the feedback in the downhole sensor. Response spectral ratios are appropriate for low frequencies, but overestimate the amplification at high frequencies. The best method to be used depends on how much precision is required in the estimates.

Earthquake Spectra↗
USGS2018

Characteristics of tropical tree species in hyperspectral and multispectral data

Remote sensing has been hailed as a promising technology to provide spatially explicit information on tree species distribution. Such information is of high value for ecologists and forest managers, particularly in tropical environments in which it is acquired by costly field inventories performed at the plot level (∼1 ha). Over the last decade, hyperspectral sensors, usually on board airborne platforms, have been successfully employed for tropical tree species classification. Most of the studies focused on the improvement of the classification accuracy, without examining the sources of variability in canopy reflectance that contribute to discriminate among species. Trees of different species usually feature distinct crown structural and chemical characteristics defined by size, shape, leaf density, branching, pigment and nonpigment biochemical constituents, among others. Understanding the role of these characteristics on tree species discrimination is important to improve and optimize the use of hyperspectral data. Here, we show how spectral characteristics of tree species, from highly diverse tropical forests, are related to their chemical and structural properties. These spectral characteristics were retrieved by spectral mixture and feature analysis, using narrow-band data acquired in the optical domain (450–2400 nm). Finally, we assessed how the spectral resolution affects the classification accuracy and spectral separability.

Book chapter↗
USGS2018

Correcting spacecraft jitter in HiRISE images

Mechanical oscillations or vibrations on spacecraft, also called pointing jitter, cause geometric distortions and/or smear in high-resolution digital images acquired from orbit. Geometric distortion is especially a problem with pushbroom sensors, such as the High Resolution Imaging Science Experiment (HiRISE) instrument on-board the Mars Reconnaissance Orbiter (MRO). Geometric distortions occur at a range of frequencies that may not be obvious in the image products, but can cause problems with stereo image correlation in the production of digital elevation models, and in measuring surface changes in time series with orthorectified images. The HiRISE focal plane comprises a staggered array of fourteen charge-coupled devices (CCDs) with pixel instantaneous field of view (IFOV) of 1 microradian. The high spatial resolution of HiRISE makes it both sensitive to, and an excellent recorder of jitter. We present an algorithm using Fourier analysis to resolve the jitter function for a HiRISE image that is then used to update instrument pointing information to remove geometric distortions from the image. Implementation of the jitter analysis and image correction is performed on selected HiRISE images made available to the public. Results show marked reduction of geometric distortions. This work has applications to similar cameras operating now (such as the Lunar Reconnaissance Orbiter Camera Narrow Angle Camera (LROC NAC) on-board the Lunar Reconnaissance Orbiter) and to the design of future instruments (such as the Europa Imaging System, planned for the Europa Clipper mission).

Book chapter↗