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USGS2006

Organic geochemistry - A retrospective of its first 70 years

Organic geochemistry had its origin in the early part of the 20th century when organic chemists and geologists realized that detailed information on the organic materials in sediments and rocks was scientifically interesting and of practical importance. The generally acknowledged "father" of organic geochemistry is Alfred E. Treibs (1899-1983), who discovered and described, in 1936, porphyrin pigments in shale, coal, and crude oil, and traced the source of these molecules to their biological precursors. Thus, the year 1936 marks the beginning of organic geochemistry. However, formal organization of organic geochemistry dates from 1959 when the Organic Geochemistry Division (OGD) of The Geochemical Society was founded in the United States, followed 22 years later (1981) by the establishment of the European Association of Organic Geochemists (EAOG). Organic geochemistry (1) has its own journal, Organic Geochemistry (beginning in 1979) which, since 1988, is the official journal of the EAOG, (2) convenes two major conferences [International Meeting on Organic Geochemistry (IMOG), since 1962, and Gordon Research Conferences on Organic Geochemistry (GRC), since 1968] in alternate years, and (3) is the subject matter of several textbooks. Organic geochemistry is now a widely recognized geoscience in which organic chemistry has contributed significantly not only to geology (i.e., petroleum geochemistry, molecular stratigraphy) and biology (i.e., biogeochemistry), but also to other disciplines, such as chemical oceanography, environmental science, hydrology, biochemical ecology, archaeology, and cosmochemistry.

Conference Paper↗

USGS2008

Origins of organic geochemistry

When organic geochemistry actually began as a recognized geoscience is a matter of definition and perspective. Constraints on its beginning are placed by the historical development of its parent disciplines, geology and organic chemistry. These disciplines originated independently and developed in parallel, starting in the latter half of the 18th century and flourishing thereafter into the 21st century. Organic geochemistry began sometime between 1860 and 1983; I argue that 1930 is the best year to mark its origin.

Organic Geochemistry↗

USGS2006

Introduction to ‘Antarctic climate evolution: View from the margin’

This special issue on “Antarctic Climate Evolution—view from the margin” presents results from modelling studies and reports on geoscience data aimed at improving our understanding of the behaviour of the Antarctic ice sheet and the climate of the region. This research field is of interest because of the sensitivity of the polar regions to global warming, and because of the influence of the Antarctic ice sheet on global sea level and climate through most if not all of the Cenozoic Era. The Antarctic ice sheet both responds to and forces changes on global climate and sea level. We need to be aware of the scale and frequency of these changes if we are to understand past patterns of environmental change elsewhere on earth. It was only three decades ago that we discovered from strata drilled in shelf basins on the Antarctic margin that the Antarctic ice sheet had a history that predated the Quaternary ice ages by over 20 million years ( Hayes et al., 1975 ). Later that year the first interpretation of Antarctic glacial history through the Cenozoic Era from oxygen isotopes, recorded in foraminifera from deep-sea sediment cores, was published ( Shackleton and Kennett, 1975 ). Revisions with a more extensive database have modified the story a little ( Miller et al., 1987 , Zachos et al., 2001 ), and there have been recent attempts to resolve the temperature–ice volume ambiguity ( Lear et al., 2000 ). However, reports on strata drilled on the Antarctic margin have unambiguously shown the character of this huge ice sheet, which was oscillating in the Oligocene ( Barrett et al., 1987 , Barrett, 1999 ) with a period and magnitude comparable with the Northern Hemisphere ice sheets of the Quaternary ( Naish et al., 2001a , Naish et al., 2001b ). In this issue we present further research on the history of the Antarctic ice sheet from Oligocene to recent times, most of them from the Antarctic margin, but with some on the nature of the deep-sea isotope record, and others using recently developed modeling techniques to investigate the influence of atmosphere, ocean and biosphere on past Antarctic climate. This special issue is the third in three years on the theme of Antarctic Climate Evolution. The first followed a workshop in Erice, Sicily, in 2001 to report on results from ANTOSTRAT, a SCAR-sponsored project for gathering and analysing circum-Antarctic seismic data for planning and promoting offshore drilling for climate history. The introduction to that issue (Florindo et al., 2003) provides a review of the recent history of circum-Antarctic drilling by the Ocean Drilling Program (Legs 113, 114, 119, 120, 177, 178, 188 and 189) and the Cape Roberts Project. For a more comprehensive review of earlier drilling in the Ross Sea region (Deep Sea Drilling Project Leg 28, Dry Valley Drilling Project, McMurdo Sound Sediment and Tectonic Studies, Cenozoic Investigations in the western Ross Sea) see Hambrey and Barrett (1993). The first of these issues (Florindo et al., 2003) featured a global plate reconstruction of the Southern Hemisphere through Cenozoic time with emphasis on evolution of Cenozoic seaways (Lawver and Gahagan, 2003) along with a study of the inception and early evolution of the EAIS using a new coupled global climate (GCM)–dynamic ice sheet model (DeConto and Pollard, 2003b), as well as data from recent drilling around the margin covering time period from Cretaceous to the present. A second special issue on the same theme (Florindo et al., 2005) also featured a mix of modelling and data papers with a focus on the Eocene–Oligocene boundary and the initiation of ice sheet growth, including a pioneering attempt to evaluate the relative influence of fluvial versus glacial processes in shaping the landscape of the Prydz Bay sector of Antarctica (Jamieson et al., 2005). The remainder of the issue comprised further papers on seismic stratigraphy and reports from drilling around the margin. The papers to be found in this special issue, like the previous two, maintain the mix of modelling- and data-oriented papers that reflect the range of this research.

Palaeogeography, Palaeoclimatology, Palaeoecology↗

USGS2018

Interoperability in planetary research for geospatial data analysis

For more than a decade there has been a push in the planetary science community to support interoperable methods for accessing and working with geospatial data. Common geospatial data products for planetary research include image mosaics, digital elevation or terrain models, geologic maps, geographic location databases (e.g., craters, volcanoes) or any data that can be tied to the surface of a planetary body (including moons, comets or asteroids). Several U.S. and international cartographic research institutions have converged on mapping standards that embrace standardized geospatial image formats, geologic mapping conventions, U.S. Federal Geographic Data Committee (FGDC) cartographic and metadata standards, and notably on-line mapping services as defined by the Open Geospatial Consortium (OGC). The latter includes defined standards such as the OGC Web Mapping Services (simple image maps), Web Map Tile Services (cached image tiles), Web Feature Services (feature streaming), Web Coverage Services (rich scientific data streaming), and Catalog Services for the Web (data searching and discoverability). While these standards were developed for application to Earth-based data, they can be just as valuable for planetary domain. Another initiative, called VESPA (Virtual European Solar and Planetary Access), will marry several of the above geoscience standards and astronomy-based standards as defined by International Virtual Observatory Alliance (IVOA). This work outlines the current state of interoperability initiatives in use or in the process of being researched within the planetary geospatial community.

Planetary and Space Science↗

USGS2015

Megathrust earthquakes and sea-level change: A tribute to George Plafker

For numerous scientific disciplines that contribute to the understanding of megathrust earthquakes, 2014 was an anniversary year of two great, >M w 9, earthquakes; fifty years since the March 27 1964 earthquake in Alaska and ten years since the December 26 2004 Aceh-Andaman earthquake and attendant tsunami. 2014 was also the final year of International Geoscience Programme (IGCP) Project 588 “Preparing for Coastal Change”, which was the latest in the 25 year history of IGCP coastal change research.

Quaternary Science Reviews↗

USGS2011

Modeling the height of young forests regenerating from recent disturbances in Mississippi using Landsat and ICESat data

Many forestry and earth science applications require spatially detailed forest height data sets. Among the various remote sensing technologies, lidar offers the most potential for obtaining reliable height measurement. However, existing and planned spaceborne lidar systems do not have the capability to produce spatially contiguous, fine resolution forest height maps over large areas. This paper describes a Landsat–lidar fusion approach for modeling the height of young forests by integrating historical Landsat observations with lidar data acquired by the Geoscience Laser Altimeter System (GLAS) instrument onboard the Ice, Cloud, and land Elevation (ICESat) satellite. In this approach, “young” forests refer to forests reestablished following recent disturbances mapped using Landsat time-series stacks (LTSS) and a vegetation change tracker (VCT) algorithm. The GLAS lidar data is used to retrieve forest height at sample locations represented by the footprints of the lidar data. These samples are used to establish relationships between lidar-based forest height measurements and LTSS–VCT disturbance products. The height of “young” forest is then mapped based on the derived relationships and the LTSS–VCT disturbance products. This approach was developed and tested over the state of Mississippi. Of the various models evaluated, a regression tree model predicting forest height from age since disturbance and three cumulative indices produced by the LTSS–VCT method yielded the lowest cross validation error. The R 2 and root mean square difference (RMSD) between predicted and GLAS-based height measurements were 0.91 and 1.97 m, respectively. Predictions of this model had much higher errors than indicated by cross validation analysis when evaluated using field plot data collected through the Forest Inventory and Analysis Program of USDA Forest Service. Much of these errors were due to a lack of separation between stand clearing and non-stand clearing disturbances in current LTSS–VCT products and difficulty in deriving reliable forest height measurements using GLAS samples when terrain relief was present within their footprints. In addition, a systematic underestimation of about 5 m by the developed model was also observed, half of which could be explained by forest growth that occurred between field measurement year and model target year. The remaining difference suggests that tree height measurements derived using waveform lidar data could be significantly underestimated, especially for young pine forests. Options for improving the height modeling approach developed in this study were discussed.

Remote Sensing of Environment↗

USGS2012

A multi-sensor lidar, multi-spectral and multi-angular approach for mapping canopy height in boreal forest regions

Spatially explicit representations of vegetation canopy height over large regions are necessary for a wide variety of inventory, monitoring, and modeling activities. Although airborne lidar data has been successfully used to develop vegetation canopy height maps in many regions, for vast, sparsely populated regions such as the boreal forest biome, airborne lidar is not widely available. An alternative approach to canopy height mapping in areas where airborne lidar data is limited is to use spaceborne lidar measurements in combination with multi-angular and multi-spectral remote sensing data to produce comprehensive canopy height maps for the entire region. This study uses spaceborne lidar data from the Geosciences Laser Altimeter System (GLAS) as training data for regression tree models that incorporate multi-angular and multi-spectral data from the Multi-Angle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging SpectroRadiometer (MODIS) to map vegetation canopy height across a 1,300,000 km 2 swath of boreal forest in Interior Alaska. Results are compared to in situ height measurements as well as airborne lidar data. Although many of the GLAS-derived canopy height estimates are inaccurate, applying a series of filters incorporating both data associated with the GLAS shots as well as ancillary data such as land cover can identify the majority of height estimates with significant errors, resulting in a filtered dataset with much higher accuracy. Results from the regression tree models indicate that late winter MISR imagery acquired under snow-covered conditions is effective for mapping canopy heights ranging from 5 to 15 m, which includes the vast majority of forests in the region. It appears that neither MISR nor MODIS imagery acquired during the growing season is effective for canopy height mapping, although including summer multi-spectral MODIS data along with winter MISR imagery does appear to provide a slight increase in the accuracy of resulting height maps. The finding that winter, snow-covered MISR imagery can be used to map canopy height is important because clear sky days are nearly three times as common during the late winter period as during the growing season. The increased odds of acquiring cloud-free imagery during the target acquisition period make regularly updated forest height inventories for Interior Alaska much more feasible. A major advantage of the GLAS–MISR–MODIS canopy height mapping methodology described here is that this approach uses only data that is freely available worldwide, making the approach potentially applicable across the entire circumpolar boreal forest region.

Remote Sensing of Environment↗

USGS2014

Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD)

Forest cover loss and bare ground gain from 2006 to 2010 for the conterminous United States (CONUS) were quantified at a 30 m spatial resolution using Web-Enabled Landsat Data available from the USGS Center for Earth Resources Observation and Science (EROS) (http://landsat.usgs.gov/WELD.php). The approach related multi-temporal WELD metrics and expert-derived training data for forest cover loss and bare ground gain through a decision tree classification algorithm. Forest cover loss was reported at state and ecoregional scales, and the identification of core forests' absent of change was made and verified using LiDAR data from the GLAS (Geoscience Laser Altimetry System) instrument. Bare ground gain correlated with population change for large metropolitan statistical areas (MSAs) outside of desert or semi-desert environments. GoogleEarth™ time-series images were used to validate the products. Mapped forest cover loss totaled 53,084 km2 and was found to be depicted conservatively, with a user's accuracy of 78% and a producer's accuracy of 68%. Excluding errors of adjacency, user's and producer's accuracies rose to 93% and 89%, respectively. Mapped bare ground gain equaled 5974 km2 and nearly matched the estimated area from the reference (GoogleEarth™) classification; however, user's (42%) and producer's (49%) accuracies were much less than those of the forest cover loss product. Excluding errors of adjacency, user's and producer's accuracies rose to 62% and 75%, respectively. Compared to recent 2001–2006 USGS National Land Cover Database validation data for forest loss (82% and 30% for respective user's and producer's accuracies) and urban gain (72% and 18% for respective user's and producer's accuracies), results using a single CONUS-scale model with WELD data are promising and point to the potential for national-scale operational mapping of key land cover transitions. However, validation results highlighted limitations, some of which can be addressed by improving training data, creating a more robust image feature space, adding contemporaneous Landsat 5 data to the inputs, and modifying definition sets to account for differences in temporal and spatial observational scales. The presented land cover extent and change data are available via the official WELD website (ftp://weldftp.cr.usgs.gov/CONUS_5Y_LandCover/ftp://weldftp.cr.usgs.gov/CONUS_5Y_LandCover/).

Remote Sensing of Environment↗

USGS2002

Health impacts of coal and coal use: Possible solutions

Coal will be a dominant energy source in both developed and developing countries for at least the first half of the 21st century. Environmental problems associated with coal, before mining, during mining, in storage, during combustion, and postcombustion waste products are well known and are being addressed by ongoing research. The connection between potential environmental problems with human health is a fairly new field and requires the cooperation of both the geoscience and medical disciplines. Three research programs that illustrate this collaboration are described and used to present a range of human health problems that are potentially caused by coal. Domestic combustion of coal in China has, in some cases, severely affected human health. Both on a local and regional scale, human health has been adversely affected by coals containing arsenic, fluorine, selenium, and possibly, mercury. Balkan endemic nephropathy (BEN), an irreversible kidney disease of unknown origin, has been related to the proximity of Pliocene lignite deposits. The working hypothesis is that groundwater is leaching toxic organic compounds as it passes through the lignites and that these organics are then ingested by the local population contributing to this health problem. Human disease associated with coal mining mainly results from inhalation of particulate matter during the mining process. The disease is Coal Worker's Pneumoconiosis characterized by coal dust-induced lesions in the gas exchange regions of the lung; the coal worker's "black lung disease". ?? 2002 Elsevier Science B.V. All rights reserved.

International Journal of Coal Geology↗

USGS2011

Geoinformatics in the public service: Building a cyberinfrastructure across the geological surveys

Advanced information technology infrastructure is increasingly being employed in the Earth sciences to provide researchers with efficient access to massive central databases and to integrate diversely formatted information from a variety of sources. These geoinformatics initiatives enable manipulation, modeling and visualization of data in a consistent way, and are helping to develop integrated Earth models at various scales, and from the near surface to the deep interior. This book uses a series of case studies to demonstrate computer and database use across the geosciences. Chapters are thematically grouped into sections that cover data collection and management; modeling and community computational codes; visualization and data representation; knowledge management and data integration; and web services and scientific workflows. Geoinformatics is a fascinating and accessible introduction to this emerging field for readers across the solid Earth sciences and an invaluable reference for researchers interested in initiating new cyberinfrastructure projects of their own.

Book chapter↗

USGS1999

A comparison of the weights-of-evidence method and probabilistic neural networks

The need to integrate large quantities of digital geoscience information to classify locations as mineral deposits or nondeposits has been met by the weights-of-evidence method in many situations. Widespread selection of this method may be more the result of its ease of use and interpretation rather than comparisons with alternative methods. A comparison of the weights-of-evidence method to probabilistic neural networks is performed here with data from Chisel Lake-Andeson Lake, Manitoba, Canada. Each method is designed to estimate the probability of belonging to learned classes where the estimated probabilities are used to classify the unknowns. Using these data, significantly lower classification error rates were observed for the neural network, not only when test and training data were the same (0.02 versus 23%), but also when validation data, not used in any training, were used to test the efficiency of classification (0.7 versus 17%). Despite these data containing too few deposits, these tests of this set of data demonstrate the neural network's ability at making unbiased probability estimates and lower error rates when measured by number of polygons or by the area of land misclassified. For both methods, independent validation tests are required to ensure that estimates are representative of real-world results. Results from the weights-of-evidence method demonstrate a strong bias where most errors are barren areas misclassified as deposits. The weights-of-evidence method is based on Bayes rule, which requires independent variables in order to make unbiased estimates. The chi-square test for independence indicates no significant correlations among the variables in the Chisel Lake–Andeson Lake data. However, the expected number of deposits test clearly demonstrates that these data violate the independence assumption. Other, independent simulations with three variables show that using variables with correlations of 1.0 can double the expected number of deposits as can correlations of −1.0. Studies done in the 1970s on methods that use Bayes rule show that moderate correlations among attributes seriously affect estimates and even small correlations lead to increases in misclassifications. Adverse effects have been observed with small to moderate correlations when only six to eight variables were used. Consistent evidence of upward biased probability estimates from multivariate methods founded on Bayes rule must be of considerable concern to institutions and governmental agencies where unbiased estimates are required. In addition to increasing the misclassification rate, biased probability estimates make classification into deposit and nondeposit classes an arbitrary subjective decision. The probabilistic neural network has no problem dealing with correlated variables—its performance depends strongly on having a thoroughly representative training set. Probabilistic neural networks or logistic regression should receive serious consideration where unbiased estimates are required. The weights-of-evidence method would serve to estimate thresholds between anomalies and background and for exploratory data analysis.

Natural Resources Research↗

USGS2003

Typing mineral deposits using their grades and tonnages in an artificial neural network

A test of the ability of a probabilistic neural network to classify deposits into types on the basis of deposit tonnage and average Cu, Mo, Ag, Au, Zn, and Pb grades is conducted. The purpose is to examine whether this type of system might serve as a basis for integrating geoscience information available in large mineral databases to classify sites by deposit type. Benefits of proper classification of many sites in large regions are relatively rapid identification of terranes permissive for deposit types and recognition of specific sites perhaps worthy of exploring further. Total tonnages and average grades of 1,137 well-explored deposits identified in published grade and tonnage models representing 13 deposit types were used to train and test the network. Tonnages were transformed by logarithms and grades by square roots to reduce effects of skewness. All values were scaled by subtracting the variable's mean and dividing by its standard deviation. Half of the deposits were selected randomly to be used in training the probabilistic neural network and the other half were used for independent testing. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class (type) and each variable (grade or tonnage). Deposit types were selected to challenge the neural network. For many types, tonnages or average grades are significantly different from other types, but individual deposits may plot in the grade and tonnage space of more than one type. Porphyry Cu, porphyry Cu-Au, and porphyry Cu-Mo types have similar tonnages and relatively small differences in grades. Redbed Cu deposits typically have tonnages that could be confused with porphyry Cu deposits, also contain Cu and, in some situations, Ag. Cyprus and kuroko massive sulfide types have about the same tonnages. Cu, Zn, Ag, and Au grades. Polymetallic vein, sedimentary exhalative Zn-Pb, and Zn-Pb skarn types contain many of the same metals. Sediment-hosted Au, Comstock Au-Ag, and low-sulfide Au-quartz vein types are principally Au deposits with differing amounts of Ag. Given the intent to test the neural network under the most difficult conditions, an overall 75% agreement between the experts and the neural network is considered excellent. Among the largestclassification errors are skarn Zn-Pb and Cyprus massive sulfide deposits classed by the neuralnetwork as kuroko massive sulfides—24 and 63% error respectively. Other large errors are the classification of 92% of porphyry Cu-Mo as porphyry Cu deposits. Most of the larger classification errors involve 25 or fewer training deposits, suggesting that some errors might be the result of small sample size. About 91% of the gold deposit types were classed properly and 98% of porphyry Cu deposits were classes as some type of porphyry Cu deposit. An experienced economic geologist would not make many of the classification errors that were made by the neural network because the geologic settings of deposits would be used to reduce errors. In a separate test, the probabilistic neural network correctly classed 93% of 336 deposits in eight deposit types when trained with presence or absence of 58 minerals and six generalized rock types. The overall success rate of the probabilistic neural network when trained on tonnage and average grades would probably be more than 90% with additional information on the presence of a few rock types.

Natural Resources Research↗

USGS1999

Digital photogrammetric analysis of the IMP camera images: Mapping the Mars Pathfinder landing site in three dimensions

This paper describes our photogrammetric analysis of the Imager for Mars Pathfinder data, part of a broader program of mapping the Mars Pathfinder landing site in support of geoscience investigations. This analysis, carried out primarily with a commercial digital photogrammetric system, supported by our in‐house Integrated Software for Imagers and Spectrometers (ISIS), consists of three steps: (1) geometric control: simultaneous solution for refined estimates of camera positions and pointing plus three‐dimensional (3‐D) coordinates of ∼10 3 features sitewide, based on the measured image coordinates of those features; (2) topographic modeling: identification of ∼3×10 5 closely spaced points in the images and calculation (based on camera parameters from step 1) of their 3‐D coordinates, yielding digital terrain models (DTMs); and (3) geometric manipulation of the data: combination of the DTMs from different stereo pairs into a sitewide model, and reprojection of image data to remove parallax between the different spectral filters in the two cameras and to provide an undistorted planimetric view of the site. These processes are described in detail and example products are shown. Plans for combining the photogrammetrically derived topographic data with spectrophotometry are also described. These include photometric modeling using surface orientations from the DTM to study surface microtextures and improve the accuracy of spectral measurements, and photoclinometry to refine the DTM to single‐pixel resolution where photometric properties are sufficiently uniform. Finally, the inclusion of rover images in a joint photogrammetric analysis with IMP images is described. This challenging task will provide coverage of areas hidden to the IMP, but accurate ranging of distant features can be achieved only if the lander is also visible in the rover image used.

Journal of Geophysical Research E: Planets↗

USGS2005

Applying petrophysical models to radar travel time and electrical resistivity tomograms: Resolution-dependent limitations

[1] Geophysical imaging has traditionally provided qualitative information about geologic structure; however, there is increasing interest in using petrophysical models to convert tomograms to quantitative estimates of hydrogeologic, mechanical, or geochemical parameters of interest (e.g., permeability, porosity, water content, and salinity). Unfortunately, petrophysical estimation based on tomograms is complicated by limited and variable image resolution, which depends on (1) measurement physics (e.g., electrical conduction or electromagnetic wave propagation), (2) parameterization and regularization, (3) measurement error, and (4) spatial variability. We present a framework to predict how core‐scale relations between geophysical properties and hydrologic parameters are altered by the inversion, which produces smoothly varying pixel‐scale estimates. We refer to this loss of information as “correlation loss.” Our approach upscales the core‐scale relation to the pixel scale using the model resolution matrix from the inversion, random field averaging, and spatial statistics of the geophysical property. Synthetic examples evaluate the utility of radar travel time tomography (RTT) and electrical‐resistivity tomography (ERT) for estimating water content. This work provides (1) a framework to assess tomograms for geologic parameter estimation and (2) insights into the different patterns of correlation loss for ERT and RTT. Whereas ERT generally performs better near boreholes, RTT performs better in the interwell region. Application of petrophysical models to the tomograms in our examples would yield misleading estimates of water content. Although the examples presented illustrate the problem of correlation loss in the context of near‐surface geophysical imaging, our results have clear implications for quantitative analysis of tomograms for diverse geoscience applications.

Journal of Geophysical Research B: Solid Earth↗

USGS2022

Near-surface geophysics perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

Pointing to the Integrated, Coordinated, Open, Networked Findability, Accessibility, Interoperability, and Reusability (ICON-FAIR) principles, we have determined several opportunities for implementation within the realm of near-surface geophysics (NSG), representing a broad range of data acquisition and processing technologies. Our work explores the multifaceted community-driven nature of NSG and, by applying ICON-FAIR principles, we identify three key strategic objectives: (i) the development of an approach to integrating NSG into other geoscience data collection projects, (ii) the creation of coordinated and open standardized NSG data, and (iii) the networking of post-secondary institutions to foster an equipment sharing consortium. The precedence within the geoscientific community demonstrates that there are significant opportunities for advancing interdisciplinary applications of NSG through the implementation of structural change within the ICON-FAIR framework.

Earth and Space Science↗

USGS2021

Earthcasting: Geomorphic forecasts for society

Over the last several decades, the study of Earth surface processes has progressed from a descriptive science to an increasingly quantitative one due to advances in theoretical, experimental, and computational geosciences. The importance of geomorphic forecasts has never been greater, as technological development and global climate change threaten to reshape the landscapes that support human societies and natural ecosystems. Here we explore best practices for developing socially relevant forecasts of Earth surface change, a goal we are calling “earthcasting”. We suggest that earthcasts have the following features: they focus on temporal (∼1–∼100 years) and spatial (∼1 m–∼10 km) scales relevant to planning; they are designed with direct involvement of stakeholders and public beneficiaries through the evaluation of the socioeconomic impacts of geomorphic processes; and they generate forecasts that are clearly stated, testable, and include quantitative uncertainties. Earthcasts bridge the gap between Earth surface researchers and decision-makers, stakeholders, researchers from other disciplines, and the general public. We investigate the defining features of earthcasts and evaluate some specific examples. This paper builds on previous studies of prediction in geomorphology by recommending a roadmap for (a) generating earthcasts, especially those based on modeling; (b) transforming a subset of geomorphic research into earthcasts; and (c) communicating earthcasts beyond the geomorphology research community. Earthcasting exemplifies the social benefit of geomorphology research, and it calls for renewed research efforts toward further understanding the limits of predictability of Earth surface systems and processes, and the uncertainties associated with modeling geomorphic processes and their impacts.

Earth's Future↗

USGS2022

Achievements and prospects of global broadband seismographic networks after 30 years of continuous geophysical observations

Global seismographic networks (GSNs) emerged during the late nineteenth and early twentieth centuries, facilitated by seminal international developments in theory, technology, instrumentation, and data exchange. The mid- to late-twentieth century saw the creation of the World-Wide Standardized Seismographic Network (1961) and International Deployment of Accelerometers (1976), which advanced global geographic coverage as seismometer bandwidth increased greatly allowing for the recording of the Earth's principal seismic spectrum. The modern era of global observations and rapid data access began during the 1980s, and notably included the inception of the GEOSCOPE initiative (1982) and GSN (1988). Through continual improvements, GEOSCOPE and the GSN have realized near-real time recording of ground motion with state-of-art data quality, dynamic range, and timing precision to encompass 180 seismic stations, many in very remote locations. Data from GSNs are increasingly integrated with other geophysical data (e.g., space geodesy, infrasound and Interferometric Synthetic Aperture Radar). Globally distributed seismic data are critical to resolving crust, mantle, and core structure; illuminating features of the plate tectonic and mantle convection system; rapid characterization of earthquakes; identification of potential tsunamis; global nuclear test verification; and provide sensitive proxies for environmental changes. As the global geosciences community continues to advance our understanding of Earth structure and processes controlling elastic wave propagation, GSN infrastructure offers a springboard to realize increasingly multi-instrument geophysical observatories. Here, we review the historical, scientific, and monitoring heritage of GSNs, summarize key discoveries, and discuss future associated opportunities for Earth Science.

Reviews of Geophysics↗

USGS2010

Geophysical studies of the West Antarctic rift system

The West Antarctic rift system extends over a 3000 × 750 km, largely ice covered area from the Ross Sea to the base of the Antarctic Peninsula, comparable in area to the Basin and Range and the East African rift system. A spectacular rift shoulder scarp along which peaks reach 4–5 km maximum elevation marks one flank and extends from northern Victoria Land-Queen Maud Mountains to the Ellsworth-Whitmore-Horlick Mountains. The rift shoulder has maximum present physiographic relief of 5 km in the Ross Embayment and 7 km in the Ellsworth Mountains-Byrd Subglacial Basin area. The Transantarctic Mountains part of the rift shoulder (and probably the entire shoulder) has been interpreted as rising since about 60 Ma, at episodic rates of ∼1 km/m.y., most recently since mid-Pliocene time, rather than continuously at the mean rate of 100 m/m.y. The rift system is characterized by bimodal alkaline volcanic rocks ranging from at least Oligocene to the present. These are exposed asymmetrically along the rift flanks and at the south end of the Antarctic Peninsula. The trend of the Jurassic tholeiites (Ferrar dolerites, Kirkpatric basalts) marking the Jurassic Transantarctic rift is coincident with exposures of the late Cenozoic volcanic rocks along the section of the Transantarctic Mountains from northern Victoria Land to the Horlick Mountains. The Cenozoic rift shoulder diverges here from the Jurassic tholeiite trend, and the tholeiites are exposed continuously (including the Dufek intrusion) along the lower- elevation (1–2 km) section of Transantarctic Mountains to the Weddell Sea. Widely spaced aeromagnetic profiles in West Antarctica indicate the absence of Cenozoic volcanic rocks in the ice covered part of the Whitmore-Ellsworth-Mountain block and suggest their widespread occurrence beneath the western part of the ice sheet overlying the Byrd Subglacial Basin. A German Federal Institute for Geosciences and Natural Resources (BGR)-U.S. Geological Survey (USGS) aeromagnetic survey over the Ross Sea continental shelf indicates rift fabric and suggests numerous submarine volcanoes along discrete NNW trending zones. A Bouguer anomaly range of approximately 200 (+50 to −150) mGal having 4–7 mGal/km gradients where measured in places marks the rift shoulder from northern Victoria Land possibly to the Ellsworth Mountains (where data are too sparse to determine maximum amplitude and gradient). The steepest gravity gradients across the rift shoulder require high density (mafic or ultramafic?) rock within the crust as well as at least 12 km of thinner crust beneath the West Antarctic rift system in contrast to East Antarctica. Sparse land seismic data reported along the rift shoulder, where velocities are greater than 7 km/s, and marine data indicating velocities above 7 km/s beneath the Ross Sea continental shelf support this interpretation. The maximum Bouguer gravity range in the Pensacola Mountains area of the Transantarctic Mountains is only about 130 mGal with a maximum 2 mGal/km gradient, which can be explained solely by 8 km of crustal thickening. Large offset seismic profiles over the Ross Sea shelf collected by the German Antarctic North Victoria Land Expedition V (GANOVEX V) combined with earlier USGS and other results indicate 17–21 km thickness for the crust beneath the Ross Sea shelf which we interpret as evidence of extended rifted continental crust. A regional positive Bouguer anomaly (0 to +50 mGal), the width of the rift, extends from the Ross Sea continental shelf throughout the Ross Embayment and Byrd Subglacial Basin area of the West Antarctic rift system and indicates that the Moho is approximately 20 km deep tied to the seismic results (probably coincident with the top of the asthenosphere) rather than the 30 km reported in earlier interpretations. The interpretation of horst and graben structures in the Ross Sea, made from marine seismic reflection data, probably can be extended throughout the rift (i.e., the Ross Ice shelf and the Byrd Subglacial Basin areas). The near absence of earthquakes in the West Antarctic rift system probably results from a combination of primarily sparse seismograph coverage and, secondarily, suppression of earthquakes by the ice sheet (e.g., Johnston, 1987) and very high seismicity shortly after deglaciation in the Ross Embayment followed by abnormally low seismicity at present (e.g., Muir Wood, 1989). The evidence of high temperatures at shallow depth beneath the Ross Sea continental shelf and adjacent Transantarctic Mountains is supportive of thermal uplift of the mountains associated with lateral heat conduction from the rift and can possibly also explain the volcanism, rifting, and high elevation of the entire rift shoulder to the Ellsworth-Horlick-Whitmore Mountains. We infer that the Gondwana breakup and the West Antarctic rift are part of a continuously propagating rift that started in the Jurassic when Africa separated from East Antarctica (including the failed Jurassic Transantarctic rift). Rifting proceeded clockwise around East Antarctica to the separation of New Zealand and the Campbell Plateau about 85–95 Ma and has continued (with a spreading center jump) to its present location in the Ross Embayment and West Antarctica. The Cenozoic activity of the West Antarctic rift system appears to be continuous in time with rifting in the same area that began only in the late Mesozoic. Although the mechanism for rifting is not completely explained, we suggest a combination of the flexural rigidity model (Stem and ten Brink, 1989) proposed for the Ross Embayment and the thermal plume or hot spot concepts. The propagating rift may have been “captured” by the thermal plume.

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