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At least 1,639 records · Page 91Linked to original sources

USGS2015

An automated approach for mapping persistent ice and snow cover over high latitude regions

We developed an automated approach for mapping persistent ice and snow cover (glaciers and perennial snowfields) from Landsat TM and ETM+ data across a variety of topography, glacier types, and climatic conditions at high latitudes (above ~65°N). Our approach exploits all available Landsat scenes acquired during the late summer (1 August–15 September) over a multi-year period and employs an automated cloud masking algorithm optimized for snow and ice covered mountainous environments. Pixels from individual Landsat scenes were classified as snow/ice covered or snow/ice free based on the Normalized Difference Snow Index (NDSI), and pixels consistently identified as snow/ice covered over a five-year period were classified as persistent ice and snow cover. The same NDSI and ratio of snow/ice-covered days to total days thresholds applied consistently across eight study regions resulted in persistent ice and snow cover maps that agreed closely in most areas with glacier area mapped for the Randolph Glacier Inventory (RGI), with a mean accuracy (agreement with the RGI) of 0.96, a mean precision (user’s accuracy of the snow/ice cover class) of 0.92, a mean recall (producer’s accuracy of the snow/ice cover class) of 0.86, and a mean F-score (a measure that considers both precision and recall) of 0.88. We also compared results from our approach to glacier area mapped from high spatial resolution imagery at four study regions and found similar results. Accuracy was lowest in regions with substantial areas of debris-covered glacier ice, suggesting that manual editing would still be required in these regions to achieve reasonable results. The similarity of our results to those from the RGI as well as glacier area mapped from high spatial resolution imagery suggests it should be possible to apply this approach across large regions to produce updated 30-m resolution maps of persistent ice and snow cover. In the short term, automated PISC maps can be used to rapidly identify areas where substantial changes in glacier area have occurred since the most recent conventional glacier inventories, highlighting areas where updated inventories are most urgently needed. From a longer term perspective, the automated production of PISC maps represents an important step toward fully automated glacier extent monitoring using Landsat or similar sensors.

Remote Sensing↗

USGS2017

Evaluation of the U.S. Geological Survey Landsat burned area essential climate variable across the conterminous U.S. using commercial high-resolution imagery

The U.S. Geological Survey has produced the Landsat Burned Area Essential Climate Variable (BAECV) product for the conterminous United States (CONUS), which provides wall-to-wall annual maps of burned area at 30 m resolution (1984–2015). Validation is a critical component in the generation of such remotely sensed products. Previous efforts to validate the BAECV relied on a reference dataset derived from Landsat, which was effective in evaluating the product across its timespan but did not allow for consideration of inaccuracies imposed by the Landsat sensor itself. In this effort, the BAECV was validated using 286 high-resolution images, collected from GeoEye-1, QuickBird-2, Worldview-2 and RapidEye satellites. A disproportionate sampling strategy was utilized to ensure enough burned area pixels were collected. Errors of omission and commission for burned area averaged 22 ± 4% and 48 ± 3%, respectively, across CONUS. Errors were lowest across the western U.S. The elevated error of commission relative to omission was largely driven by patterns in the Great Plains which saw low errors of omission (13 ± 13%) but high errors of commission (70 ± 5%) and potentially a region-growing function included in the BAECV algorithm. While the BAECV reliably detected agricultural fires in the Great Plains, it frequently mapped tilled areas or areas with low vegetation as burned. Landscape metrics were calculated for individual fire events to assess the influence of image resolution (2 m, 30 m and 500 m) on mapping fire heterogeneity. As the spatial detail of imagery increased, fire events were mapped in a patchier manner with greater patch and edge densities, and shape complexity, which can influence estimates of total greenhouse gas emissions and rates of vegetation recovery. The increasing number of satellites collecting high-resolution imagery and rapid improvements in the frequency with which imagery is being collected means greater opportunities to utilize these sources of imagery for Landsat product validation.

Remote Sensing↗

USGS2017

Nominal 30-m cropland extent map of continental Africa by integrating pixel-based and object-based algorithms using Sentinel-2 and Landsat-8 Data on Google Earth Engine

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, are starting points to develop higher-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as for assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015–2016.

Remote Sensing↗

USGS2019

Evaluation of stream and wetlands restoration using UAS-based thermal infrared mapping

Large-scale wetland restoration often focuses on repairing the hydrologic connections degraded by anthropogenic modifications. Of these hydrologic connections, groundwater discharge is an important target, as these surface water ecosystem control points are important to thermal stability, among other ecosystem services. However, evaluating the effectiveness of the restoration activities on establishing groundwater discharge connection is often difficult over the vast area and often challenging or inaccessible terrain of wetlands. Unoccupied aerial systems (UAS) are now routinely used for collecting aerial imagery and creating digital surface models (DSM). Lightweight thermal infrared (TIR) sensors provide another payload option for generation of sub-meter resolution aerial TIR orthophotos. This technology allows for the rapid and safe survey of groundwater discharge areas. Aerial TIR water-surface data were collected March 2019 at Tidmarsh Farms, a former commercial cranberry peatland located in coastal Massachusetts, USA (41°54'17.6"N 70°34'17.4"W), where stream and wetland restoration actions were completed in 2016. Here we present a 0.4 km2 georeferenced, temperature calibrated TIR orthophoto of the area. The image represents a mosaic of nearly 900 TIR images captured by UAS in a single morning with a total flight time of 36 minutes, and is supported by a DSM derived from UAS visible imagery. The survey was conducted in winter to maximize temperature contrast between relatively warm groundwater and colder ambient surface environment; lower-density groundwater rises above cool surface waters and thus can be imaged by a UAS. The resulting TIR orthomosaic shows fine detail of seepage distribution and downstream influence along the several restored channel forms, which was an objective of the ecological restoration design. The restored stream channel has increased connectivity to peatland groundwater discharge, reducing the ecosystem thermal stressors. Such aerial techniques can be used to guide ecological restoration design and assess post-restoration outcomes, especially in settings where ecosystem structure and function is governed by groundwater and surface water interaction.

Water↗

USGS2014

Detecting emergence, growth, and senescence of wetland vegetation with polarimetric synthetic aperture radar (SAR) data

Wetlands provide ecosystem goods and services vitally important to humans. Land managers and policymakers working to conserve wetlands require regularly updated information on the statuses of wetlands across the landscape. However, wetlands are challenging to map remotely with high accuracy and consistency. We investigated the use of multitemporal polarimetric synthetic aperture radar (SAR) data acquired with Canada’s Radarsat-2 system to track within-season changes in wetland vegetation and surface water. We speculated, a priori , how temporal and morphological traits of different types of wetland vegetation should respond over a growing season with respect to four energy-scattering mechanisms. We used ground-based monitoring data and other ancillary information to assess the limits and consistency of the SAR data for tracking seasonal changes in wetlands. We found the traits of different types of vertical emergent wetland vegetation were detected well with the SAR data and corresponded with our anticipated backscatter responses. We also found using data from Landsat’s optical/infrared sensors in conjunction with SAR data helped remove confusion of wetland features with upland grasslands. These results suggest SAR data can provide useful monitoring information on the statuses of wetlands over time.

Water↗

USGS2016

Integrating remote sensing with species distribution models; Mapping tamarisk invasions using the Software for Assisted Habitat Modeling (SAHM)

Early detection of invasive plant species is vital for the management of natural resources and protection of ecosystem processes. The use of satellite remote sensing for mapping the distribution of invasive plants is becoming more common, however conventional imaging software and classification methods have been shown to be unreliable. In this study, we test and evaluate the use of five species distribution model techniques fit with satellite remote sensing data to map invasive tamarisk ( Tamarix spp.) along the Arkansas River in Southeastern Colorado. The models tested included boosted regression trees (BRT), Random Forest (RF), multivariate adaptive regression splines (MARS), generalized linear model (GLM), and Maxent. These analyses were conducted using a newly developed software package called the Software for Assisted Habitat Modeling (SAHM). All models were trained with 499 presence points, 10,000 pseudo-absence points, and predictor variables acquired from the Landsat 5 Thematic Mapper (TM) sensor over an eight-month period to distinguish tamarisk from native riparian vegetation using detection of phenological differences. From the Landsat scenes, we used individual bands and calculated Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and tasseled capped transformations. All five models identified current tamarisk distribution on the landscape successfully based on threshold independent and threshold dependent evaluation metrics with independent location data. To account for model specific differences, we produced an ensemble of all five models with map output highlighting areas of agreement and areas of uncertainty. Our results demonstrate the usefulness of species distribution models in analyzing remotely sensed data and the utility of ensemble mapping, and showcase the capability of SAHM in pre-processing and executing multiple complex models.

Journal of Visualized Experiments↗

USGS2024

River channel response to the removal of the Pilchuck River Diversion Dam, Washington State

In August 2020, the 3-m tall Pilchuck River Diversion Dam was removed from the Pilchuck River, allowing free fish passage to the upper third of the watershed for the first time in over a century. The narrow, 300-m long impoundment behind the dam was estimated to hold 4,000–7,500 m 3 of sand and gravel, representing less than one year's typical bedload flux. Repeat cross section surveys, stage sensors, and time-lapse cameras were used to document the physical channel response over the first year following dam removal. A total of 7,400 m 3 (effectively 100%) of impoundment sediment was eroded in the first year, with 25% accomplished by manual regrading during dam removal. Most river-caused erosion occurred during a sequence of modest flows in October 2020. Downstream deposition totaled 4,300 m 3 , predominately filling in the first 100 m downstream of the dam site. Deposition tapered below detectable levels within 350 m, and most downstream channel adjustments occurred before November 2020. Multiple high flows after December 2020 caused little upstream or downstream change. The physical river response to this dam removal then appears to have been largely accomplished within several months by modest flows, consistent with pre-removal modeling and observations from other regional dam removals. Efficient sediment evacuation was likely aided by the narrow and steep-walled impoundment geometry. Our observations support existing guidance that the physical river response to small dam removals is typically rapid and modest; the benefits of removal may then often be gained with minimal negative downstream geomorphic impacts.

Washington↗

USGS2020

Using thermal infrared cameras to detect avian chicks at various distances and vegetative coverages

Population monitoring of nesting waterbirds often involves frequent entries into the colony, but alternative methods such as local remotely sensed thermal imaging may help reduce disturbance while providing a cost-effective way to survey breeding populations. Such an approach can have high initial costs, however, which may have reduced the number of studies investigating functionality of paired thermal infrared camera and small unmanned aerial systems. Here, we take the first step of exploring the ability of two thermal infrared cameras to detect an avian chick under varying vegetative cover and distances, preceding field-mounting applications on a small unmanned aerial system. We created seven “bioboxes” to simulate a range of natural vegetation types and densities for a globally important colonial ground-nesting waterbird species, the common tern Sterna hirundo . We placed a juvenile chicken Gallus gallus (surrogate for the locally endangered common tern) in each box, and we tested two market-accessible infrared cameras (produced by FLIR Systems and Infrared Cameras, Inc.) at five elevations using a stationary boom (maximum height = 12 m). We applied computer-based digital thresholding to collected images, identifying pixels meeting one of seven threshold values. The chick was visible from at least one threshold value in 19 and 31 of 35 processed by the FLIR Systems and Infrared Cameras, respectively. Percentage of the chick identified across thresholds was generally highest at lower threshold values and elevations and decreased as elevation and threshold increased; however, the relative importance of each variable changed dramatically across bioboxes and camera types. Ability to detect a chick from processed images generally decreased with increasing elevation, and although we made no quantitative comparisons among boxes, detectability appeared greatest in images from both cameras when little or no vegetation was present. Interestingly, no single threshold value was best for all bioboxes. We observed notable differences between cameras including visual resolution of detected temperature differentials and image processing speed. Results of this controlled study show promise for the use of thermal infrared systems for detecting cryptic species in vegetation. Future research should work to combine thermal infrared and visual sensors with small unmanned aerial systems to test applicability in a mobile field application.

Journal of Fish and Wildlife Management↗

USGS2003

Determination of water depth with high-resolution satellite imagery over variable bottom types

A standard algorithm for determining depth in clear water from passive sensors exists; but it requires tuning of five parameters and does not retrieve depths where the bottom has an extremely low albedo. To address these issues, we developed an empirical solution using a ratio of reflectances that has only two tunable parameters and can be applied to low-albedo features. The two algorithms--the standard linear transform and the new ratio transform--were compared through analysis of IKONOS satellite imagery against lidar bathymetry. The coefficients for the ratio algorithm were tuned manually to a few depths from a nautical chart, yet performed as well as the linear algorithm tuned using multiple linear regression against the lidar. Both algorithms compensate for variable bottom type and albedo (sand, pavement, algae, coral) and retrieve bathymetry in water depths of less than 10-15 m. However, the linear transform does not distinguish depths >15 m and is more subject to variability across the studied atolls. The ratio transform can, in clear water, retrieve depths in >25 m of water and shows greater stability between different areas. It also performs slightly better in scattering turbidity than the linear transform. The ratio algorithm is somewhat noisier and cannot always adequately resolve fine morphology (structures smaller than 4-5 pixels) in water depths >15-20 m. In general, the ratio transform is more robust than the linear transform.

Limnology and Oceanography↗

USGS2013

Recent lake ice-out phenology within and among lake districts of Alaska, U.S.A.

The timing of ice-out in high latitudes is a fundamental threshold for lake ecosystems and an indicator of climate change. In lake-rich regions, the loss of ice cover also plays a key role in landscape and climatic processes. Thus, there is a need to understand lake ice phenology at multiple scales. In this study, we observed ice-out timing on 55 large lakes in 11 lake districts across Alaska from 2007 to 2012 using satellite imagery. Sensor networks in two lake districts validated satellite observations and provided comparison with smaller lakes. Over this 6 yr period, the mean lake ice-out for all lakes was 27 May and ranged from 07 May in Kenai to 06 July in Arctic Coastal Plain lake districts with relatively low inter-annual variability. Approximately 80% of the variation in ice-out timing was explained by the date of 0°C air temperature isotherm and lake area. Shoreline irregularity, watershed area, and river connectivity explained additional variation in some districts. Coherence in ice-out timing within the lakes of each district was consistently strong over this 6 yr period, ranging from r-values of 0.5 to 0.9. Inter-district analysis of coherence also showed synchronous ice-out patterns with the exception of the two arctic coastal districts where ice-out occurs later (June–July) and climatology is sea-ice influenced. These patterns of lake ice phenology provide a spatially extensive baseline describing short-term temporal variability, which will help decipher longer term trends in ice phenology and aid in representing the role of lake ice in land and climate models in northern landscapes.

Alaska↗

USGS1996

A preliminary survey of the broadband seismic wavefield at Puu Oo, the active vent of Kilauea volcano, Hawaii

The seismic wavefield near an active volcanic vent consists of superimposed signals in a wide range of frequency bands from sources inside and outside the volcano. To characterize the broadband wavefield near Puu Oo, we deployed a profile of three three-component broadband sensors in a 200 m long line about 1.5 km WSW of the active vent. During this period, Puu Oo maintained a constant, but very low level of activity. The digital data logger recorded the wavefield continuously in the frequency band between 0.01 and 40 Hz between June 25 and July 9, 1994. At the same time, local wind conditions along with air temperature and pressure were monitored by a portable digital weather station. On the basis of characteristic elements, such as waveform, spatial coherence between stations, particle motion and power spectra, the wavefield can be divided into three bands. The dominant signals in the frequency band between 0.01 and 0.1 Hz are not coherent among the stations. Their ground velocities correlate with the wind speed. The signals in the 0.1 to 0.5 Hz band are coherent across the profile and most probably represent a superposition of volcanic tremor and microseisms from the Pacific Ocean. Much of the energy above 0.5 Hz can be attributed to activity at the vent. Power spectra from recordings of the transverse components show complex peaks between 0.5 and 3 Hz which vary in amplitude due to site effects and distance. On the other hand, power spectra calculated from the radial components show a clearly periodic pattern of peaks at 1 Hz intervals for some time segments. A further remarkable feature of the power spectra is that they are highly stationary.

Hawaii↗

USGS2011

Entrainment of bed sediment by debris flows: results from large-scale experiments

When debris flows grow by entraining sediment, they can become especially hazardous owing to increased volume, speed, and runout. To investigate the entrainment process, we conducted eight largescale experiments in the USGS debris-flow flume. In each experiment, we released a 6 m3 water-saturated debris flow across a 47-m long, ~12-cm thick bed of partially saturated sediment lining the 31º flume. Prior to release, we used low-intensity overhead sprinkling and real-time monitoring to control the bed-sediment wetness. As each debris flow descended the flume, we measured the evolution of flow thickness, basal total normal stress, basal pore-fluid pressure, and sediment scour depth. When debris flows traveled over relatively dry sediment, net scour was minimal, but when debris flows traveled over wetter sediment (volumetric water content > 0.22), debris-flow volume grew rapidly and flow speed and runout were enhanced. Data from scour sensors showed that entrainment occurred by rapid (5-10 cm/s), progressive scour rather than by mass failure at depth. Overriding debris flows rapidly generated high basal pore-fluid pressures when they loaded and deformed bed sediment, and in wetter beds these pressures approached lithostatic levels. Reduction of intergranular friction within the bed sediment thereby enhanced scour efficiency, entrainment, and runout.

Conference Paper↗

USGS2016

Colored dissolved organic matter in shallow estuaries: relationships between carbon sources and light attenuation

Light availability is of primary importance to the ecological function of shallow estuaries. For example, benthic primary production by submerged aquatic vegetation is contingent upon light penetration to the seabed. A major component that attenuates light in estuaries is colored dissolved organic matter (CDOM). CDOM is often measured via a proxy, fluorescing dissolved organic matter (fDOM), due to the ease of in situ fDOM sensor measurements. Fluorescence must be converted to CDOM absorbance for use in light attenuation calculations. However, this CDOM–fDOM relationship varies among and within estuaries. We quantified the variability in this relationship within three estuaries along the mid-Atlantic margin of the eastern United States: West Falmouth Harbor (MA), Barnegat Bay (NJ), and Chincoteague Bay (MD/VA). Land use surrounding these estuaries ranges from urban to developed, with varying sources of nutrients and organic matter. Measurements of fDOM (excitation and emission wavelengths of 365 nm (±5 nm) and 460 nm (±40 nm), respectively) and CDOM absorbance were taken along a terrestrial-to-marine gradient in all three estuaries. The ratio of the absorption coefficient at 340 nm (m −1 ) to fDOM (QSU) was higher in West Falmouth Harbor (1.22) than in Barnegat Bay (0.22) and Chincoteague Bay (0.17). The CDOM : fDOM absorption ratio was variable between sites within West Falmouth Harbor and Barnegat Bay, but consistent between sites within Chincoteague Bay. Stable carbon isotope analysis for constraining the source of dissolved organic matter (DOM) in West Falmouth Harbor and Barnegat Bay yielded δ 13 C values ranging from −19.7 to −26.1 ‰ and −20.8 to −26.7 ‰, respectively. Concentration and stable carbon isotope mixing models of DOC (dissolved organic carbon) indicate a contribution of 13 C-enriched DOC in the estuaries. The most likely source of 13 C-enriched DOC for the systems we investigated is Spartina cordgrass. Comparison of DOC source to CDOM : fDOM absorption ratios at each site demonstrates the relationship between source and optical properties. Samples with 13 C-enriched carbon isotope values, indicating a greater contribution from marsh organic material, had higher CDOM : fDOM absorption ratios than samples with greater contribution from terrestrial organic material. Applying a uniform CDOM : fDOM absorption ratio and spectral slope within a given estuary yields errors in modeled light attenuation ranging from 11 to 33 % depending on estuary. The application of a uniform absorption ratio across all estuaries doubles this error. This study demonstrates that light attenuation coefficients for CDOM based on continuous fDOM records are highly dependent on the source of DOM present in the estuary. Thus, light attenuation models for estuaries would be improved by quantification of CDOM absorption and DOM source identification.

Biogeosciences↗

USGS2021

Synoptic analysis of a decade of daily measurements of SO2 emission in the troposphere from volcanoes of the global ground-based Network for Observation of Volcanic and Atmospheric Change

Volcanic plumes are common and far-reaching manifestations of volcanic activity during and between eruptions. Observations of the rate of emission and composition of volcanic plumes are essential to recognize and, in some cases, predict the state of volcanic activity. Measurements of the size and location of the plumes are important to assess the impact of the emission from sporadic or localized events to persistent or widespread processes of climatic and environmental importance. These observations provide information on volatile budgets on Earth, chemical evolution of magmas, and atmospheric circulation and dynamics. Space-based observations during the last decades have given us a global view of Earth's volcanic emission, particularly of sulfur dioxide ( SO 2 ). Although none of the satellite missions were intended to be used for measurement of volcanic gas emission, specially adapted algorithms have produced time-averaged global emission budgets. These have confirmed that tropospheric plumes, produced from persistent degassing of weak sources, dominate the total emission of volcanic SO 2 . Although space-based observations have provided this global insight into some aspects of Earth's volcanism, it still has important limitations. The magnitude and short-term variability of lower-atmosphere emissions, historically less accessible from space, remain largely uncertain. Operational monitoring of volcanic plumes, at scales relevant for adequate surveillance, has been facilitated through the use of ground-based scanning differential optical absorption spectrometer (ScanDOAS) instruments since the beginning of this century, largely due to the coordinated effort of the Network for Observation of Volcanic and Atmospheric Change (NOVAC). In this study, we present a compilation of results of homogenized post-analysis of measurements of SO 2 flux and plume parameters obtained during the period March 2005 to January 2017 of 32 volcanoes in NOVAC. This inventory opens a window into the short-term emission patterns of a diverse set of volcanoes in terms of magma composition, geographical location, magnitude of emission, and style of eruptive activity. We find that passive volcanic degassing is by no means a stationary process in time and that large sub-daily variability is observed in the flux of volcanic gases, which has implications for emission budgets produced using short-term, sporadic observations. The use of a standard evaluation method allows for intercomparison between different volcanoes and between ground- and space-based measurements of the same volcanoes. The emission of several weakly degassing volcanoes, undetected by satellites, is presented for the first time. We also compare our results with those reported in the literature, providing ranges of variability in emission not accessible in the past. The open-access data repository introduced in this article will enable further exploitation of this unique dataset, with a focus on volcanological research, risk assessment, satellite-sensor validation, and improved quantification of the prevalent tropospheric component of global volcanic emission.

Earth System Science Data↗

USGS2016

A multi-decade record of high-quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT)

The Surface Ocean CO 2 Atlas (SOCAT) is a synthesis of quality-controlled f CO 2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.7 million f CO 2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.6 million f CO 2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water f CO 2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water f CO 2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) “living data” publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014).

Earth System Science Data↗

USGS2014

Hillslope-scale experiment demonstrates role of convergence during two-step saturation

Subsurface flow and storage dynamics at hillslope scale are difficult to ascertain, often in part due to a lack of sufficient high-resolution measurements and an incomplete understanding of boundary conditions, soil properties, and other environmental aspects. A continuous and extreme rainfall experiment on an artificial hillslope at Biosphere 2's Landscape Evolution Observatory (LEO) resulted in saturation excess overland flow and gully erosion in the convergent hillslope area. An array of 496 soil moisture sensors revealed a two-step saturation process. First, the downward movement of the wetting front brought soils to a relatively constant but still unsaturated moisture content. Second, soils were brought to saturated conditions from below in response to rising water tables. Convergent areas responded faster than upslope areas, due to contributions from lateral subsurface flow driven by the topography of the bottom boundary, which is comparable to impermeable bedrock in natural environments. This led to the formation of a groundwater ridge in the convergent area, triggering saturation excess runoff generation. This unique experiment demonstrates, at very high spatial and temporal resolution, the role of convergence on subsurface storage and flow dynamics. The results bring into question the representation of saturation excess overland flow in conceptual rainfall-runoff models and land-surface models, since flow is gravity-driven in many of these models and upper layers cannot become saturated from below. The results also provide a baseline to study the role of the co-evolution of ecological and hydrological processes in determining landscape water dynamics during future experiments in LEO.

Hydrology and Earth System Sciences↗

USGS2018

A novel technique for precision geometric correction of jitter distortion for the Europa Imaging System and other rolling shutter cameras

We use simulated images to demonstrate a novel technique for mitigating geometric distortions caused by platform motion (“jitter”) as two-dimensional image sensors are exposed and read out line by line (“rolling shutter”). The results indicate that the Europa Imaging System (EIS) on NASA’s Europa Clipper can likely meet its scientific goals requiring 0.1-pixel precision. We are therefore adapting the software used to demonstrate and test rolling shutter jitter correction to become part of the standard processing pipeline for EIS. The correction method will also apply to other rolling-shutter cameras, provided they have the operational flexibility to read out selected “check lines” at chosen times during the systematic readout of the frame area

The International Archives of the Photogrammetry, ↗

USGS2017

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 type 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 over time in orthorectified images. The HiRISE focal plane comprises a staggered array of fourteen charge-coupled devices (CCDs) with pixel 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. Resulting corrected images and updated pointing information are made available to the public. Results show marked reduction of geometric distortions. This work has applications to similar cameras operating now, and to the design of future instruments (such as the Europa Imaging System).

The International Archives of the Photogrammetry, ↗