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At least 739 records · Page 41Linked to original sources

Energy map of southwestern Wyoming - Energy data archived, organized, integrated, and accessible

The Wyoming Landscape Conservation Initiative (WLCI) focuses on conserving world-class wildlife resources while facilitating responsible energy development in southwestern Wyoming. To further advance the objectives of the WLCI long-term, science-based effort, a comprehensive inventory of energy resource and production data is being published in two parts. Energy maps, data, documentation and spatial data processing capabilities are available in geodatabase, published map file (pmf), ArcMap document (mxd), Adobe Acrobat PDF map, and other digital formats that can be downloaded at the USGS website.

Wyoming↗

Themed social networking groups as effective sources of data: A country-wide survey on invasive bigheaded carp (Hipophthalmichthys molitrix and H. nobilis) detection and distribution

Citizen science commonly uses social networking platforms because they provide the easiest way to contact people. Social networking platforms can also be especially effective in that they gather people by interest and region. By sharing questionnaires and collecting photographs in angling-themed Facebook groups, we assessed the applicability of social networking groups in citizen science surveys to evaluate the distribution patterns of invasive bigheaded carp in Hungary. Altogether, we received 1,234 responses from 29 Facebook groups to four survey solicitations, with responses coming from 417 locations from across Hungary. The majority of responses were received in the first (mean ± SD; 74.3% ± 5.3) and second days (12.5% ± 5.5) after a survey questionnaire was posted. Group size was positively correlated with reach but inversely with reach ratio (reached members divided by the total number of group members). We collected 311 photos of 622 bigheaded carp, of which 470 were H. molitrix and 67 were H. nobilis . Although spatial bias occurred both in responses to survey questionnaires and available photographs, presence of bigheaded carp was confirmed in all medium and large rivers and many lentic habitats in Hungary. We demonstrated that social media groups can be used to survey interested members of the public and facilitate rapid data collection, providing an effective platform for citizen science. Repeated, spaced sharing of survey solicitations in as many groups as possible (regardless of group size) is the cornerstone for effective data collection. Our survey provided more effective and inexpensively obtained information about the distribution of bigheaded carp than standard catch-based methods.

Citizen Science: Theory and Practice↗

A federal-state partnership for mapping Florida's coast and seafloor

The Florida Coastal Mapping Program, a partnership of state and federal agencies, has a goal of having modern, consistent, high- resolution sea-floor data for all of Florida’s coastal zone in the next decade to support a myriad of coastal zone science and management applications. One of the early steps in the implementation process is to prioritize and justify mapping needs. This is accomplished by holding six regional workshops across the state during which stakeholders and partners are introduced to a newly developed geospatial prioritization tool. Users independently utilize the tool to populate grid cells for a given region, and the result is a cumulative perspective on sea floor mapping priorities to inform future mapping initiatives. The tool also allows participants to indicate their primary use of sea floor mapping data and types of additional data required for their science or management need.

Florida↗

Morphologic evolution of the wilderness area breach at Fire Island, New York—2012–15

Introduction Hurricane Sandy, which made landfall on October 29, 2012, near Atlantic City, New Jersey, had a significant impact on the coastal system along the south shore of Long Island, New York. A record significant wave height of 9.6 meters (m) was measured at wave buoy 44025 , approximately 48 kilometers offshore of Fire Island, New York. Surge and runup during the storm resulted in extensive beach and dune erosion and breaching of the Fire Island barrier island system at two locations, including a breach that formed within the Otis Pike Fire Island High Dune Wilderness area on the eastern side of Fire Island. The U.S. Geological Survey (USGS) has a long history of conducting morphologic change and processes research at Fire Island. One of the primary objectives of the current research effort is to understand the morphologic evolution of the barrier system on a variety of time scales (from storm scale to decade(s) to century). A number of studies that support the project objectives have been published. Prior to Hurricane Sandy, however, little information was available on specific storm-driven change in this region. The USGS received Hurricane Sandy supplemental funding (project GS2–2B: Linking Coastal Processes and Vulnerability, Fire Island, New York, Regional Study) to enhance existing research efforts at Fire Island. The existing research was greatly expanded to include inner continental shelf mapping and investigations of processes of inner shelf sediment transport; beach and dune response and recovery; and observation, analysis, and modeling of the newly formed breach in the Otis Pike High Dune Wilderness area, herein referred to as the wilderness breach. The breach formed at the site of Old Inlet, which was open from 1763 to 1825. The location of the initial island breaching does not directly correspond with topographic lows of the dunes, but instead the breach formed in the location of a cross-island boardwalk that was destroyed during Hurricane Sandy. From 2013 to November 2015, bathymetric data were collected by the USGS St. Petersburg Coastal and Marine Science Center during three surveys of the breach channel and tidal shoals, and shoreline positions on each side of the breach (also collected by the National Park Service). Additionally, pre-storm topography/bathymetry EAARL–B light detection and ranging (lidar) data were collected by the USGS the day prior to Hurricane Sandy’s landfall. These data serve as a baseline for change analyses during four subsequent periods: June 2013, June 2014, October 2014, and May 2015. The June 2013 single-beam bathymetry data were collected in collaboration with the U.S. Army Corps of Engineers (USACE), using the Lighter Amphibious Resupply Cargo (LARC) vessel, and included the ebb shoal and breach channel. The USGS collected and processed the three additional bathymetric datasets using personal watercraft equipped with single-beam echo sounders and backpack Global Positioning System (GPS) over shallow flood shoals. Eastern and western breach shorelines were surveyed weekly to monthly beginning on November 6, 2012 (by the National Park Service [NPS], and USGS St. Petersburg Coastal and Marine Science Center), with measurements made every few weeks for the first year and every few months after October 2013. The NPS and researchers from Stony Brook University monitored the breach by collecting field data of the breach channel bathymetry, conducting aerial photographic overflights, and performing water-quality analyses (see http://po.msrc.sunysb.edu/GSB/ ). The aerial photography collected and rectified by Stony Brook University is used extensively in our morphologic change description to examine changes to breach shorelines (supplementing shoreline data collected in the field), channel width, and orientation. Due to the uncertainties and the variation in survey methods, a rigorous quantitative analysis was not performed. However, average calculations of various breach metrics allow a qualitative analysis of breach development and evolution. This report presents an overview of the data collected and a summary discussion of the observed changes to the breach system and the seasonal wave climatology associated with the breach morphodynamic response.

New York↗

Topographic lidar survey of Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana, July 12-14, 2013

This Data Series Report contains lidar elevation data collected on July 12 and 14, 2013, for Dauphin Island, Alabama, and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana. Classified point cloud data—data points described in three dimensions—in lidar data exchange format (LAS) and bare earth digital elevation models (DEMs) in ERDAS Imagine raster format (IMG) are available as downloadable files. Photo Science, Inc., was contracted by the U.S. Geological Survey (USGS) to collect and process these data. The lidar data were acquired at a horizontal spacing (or nominal pulse spacing) of 1 meter (m) or less. The USGS surveyed points within the project area from July 14–23, 2013, for use in ground control and accuracy assessment. Photo Science, Inc., calculated a vertical root mean square error (RMSEz) of 0.012 m by comparing 10 surveyed points to an interpolated elevation surface of unclassified lidar data. The USGS also checked the data using 80 surveyed points and unclassified lidar point elevation data and found an RMSEz of 0.073 m. The project specified an RMSEz of 0.0925 m or less. The lidar survey was acquired to document the short- and long-term changes of several different barrier island systems. Specifically, this survey supports detailed studies of Chandeleur and Dauphin Islands that resolve annual changes in beaches, berms and dunes associated with processes driven by storms, sea-level rise, and even human restoration activities. These lidar data are available to Federal, State and local governments, emergency-response officials, resource managers, and the general public.

Alabama;Louisiana↗

Data categories for marine planning

The U.S. National Ocean Policy calls for a science- and ecosystem-based approach to comprehensive planning and management of human activities and their impacts on America’s oceans. The Ocean Community in Data.gov is an outcome of 2010–2011 work by an interagency working group charged with designing a national information management system to support ocean planning. Within the working group, a smaller team developed a list of the data categories specifically relevant to marine planning. This set of categories is an important consensus statement of the breadth of information types required for ocean planning from a national, multidisciplinary perspective. Although the categories were described in a working document in 2011, they have not yet been fully implemented explicitly in online services or geospatial metadata, in part because authoritative definitions were not created formally. This document describes the purpose of the data categories, provides definitions, and identifies relations among the categories and between the categories and external standards. It is intended to be used by ocean data providers, managers, and users in order to provide a transparent and consistent framework for organizing and describing complex information about marine ecosystems and their connections to humans.

Open-File Report↗

Global Visualization (GloVis) Viewer

GloVis (http://glovis.usgs.gov) is a browse image-based search and order tool that can be used to quickly review the land remote sensing data inventories held at the U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS). GloVis was funded by the AmericaView project to reduce the difficulty of identifying and acquiring data for user-defined study areas. Updated daily with the most recent satellite acquisitions, GloVis displays data in a mosaic, allowing users to select any area of interest worldwide and immediately view all available browse images for the following Landsat data sets: Multispectral Scanner (MSS), Multi-Resolution Land Characteristics (MRLC), Orthorectified, Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and ETM+ Scan Line Corrector-off (SLC-off). Other data sets include Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectroradiometer (MODIS), Aqua MODIS, and the Earth Observing-1 (EO-1) Advanced Land Imager (ALI) and Hyperion data.

Fact Sheet↗

Raw and processed ground-penetrating radar and postprocessed differential global positioning system data collected from Assateague Island, Maryland, October 2014

Scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center acquired sediment cores, sediment surface grab samples, ground-penetrating radar (GPR) and Differential Global Positioning System (DGPS) data from Assateague Island, Maryland, in October 2014. The objectives were to identify washover deposits in the stratigraphic record to aid in understanding barrier island evolution. This report serves as an archive of GPR and DGPS data collected from Assateague Island in October 2014. Data products, including raw GPR and processed DGPS data, elevation corrected GPR profiles, and accompanying Federal Geographic Data Committee metadata can be downloaded from the Data Downloads page.

Maryland↗

Can machine learning accelerate process understanding and decision-relevant predictions of river water quality?

The global decline of water quality in rivers and streams has resulted in a pressing need to design new watershed management strategies. Water quality can be affected by multiple stressors including population growth, land use change, global warming, and extreme events, with repercussions on human and ecosystem health. A scientific understanding of factors affecting riverine water quality and predictions at local to regional scales, and at sub-daily to decadal timescales are needed for optimal management of watersheds and river basins. Here, we discuss how machine learning (ML) can enable development of more accurate, computationally tractable, and scalable models for analysis and predictions of river water quality. We review relevant state-of-the art applications of ML for water quality models and discuss opportunities to improve the use of ML for emerging computational and mathematical methods for model selection, hyperparameter optimization, incorporating process knowledge into ML models, improving explainablity, uncertainty quantification, and model-data integration. We then present considerations for using ML to address water quality problems given their scale and complexity, available data and computational resources, and stakeholder needs. When combined with decades of process understanding, interdisciplinary advances in knowledge-guided ML, information theory, data integration, and analytics can help address fundamental science questions and enable decision-relevant predictions of riverine water quality.

Hydrological Processes↗

Climate change alters aging patterns of reservoir aquatic habitats

Two slow-moving developments are threatening reservoir aquatic habitats globally: aging and climate change. These events are projected to transform reservoir aquatic habitats in various and often unpredictable ways. Aging affects in-lake habitats directly, whereas climate change affects both in-lake and off-lake conditions. Climate change is expected to accelerate and, in some instances, possibly decelerate aging. Aging can be indexed as functional age, an index that signals the position of a reservoir along its lifespan relying on in-lake descriptors of aquatic habitat. Using existing habitat datasets and climate projections, we developed semi-quantitative predictions about the effect of climate change on reservoir functional age in the USA. Driven by increased warming, functional age was predicted to increase latitudinally from south to north with no obvious longitudinal gradient. Functional age also changed with precipitation, increasing latitudinally from south to north and longitudinally in the east and west but decreasing in the central USA. Our projections are tentative because of the uncertain nature of reservoir aging and climate change sciences, as well as the inexactness of available data and models. We review general strategies suitable for systematically dealing with the unpredictable and constantly changing conditions expected to occur this century as reservoirs certainly continue to get older, within the scope of uncertain climate change projections.

continental United States↗

Segmenting images automatically for granulometry and sedimentology: a martian case study

In a companion work, we bridge the gap between mature segmentation software used in terrestrial sedimentology and emergent planetary segmentation with an original algorithm optimized to segment whole images from the Microscopic Imager (MI) of the Mars Exploration Rovers (MER). In this work, we compare its semi-automated outcome with manual photoanalyses using unconsolidated sediment at Gusev and Meridiani Planum sites for geologic context. On average, our code and manual segmentation converge to within ~10% in the number and total area of identified grains in a pseudo-random, single blind comparison of 50 samples. Unlike manual segmentation, it also locates finer grains in an image with internal consistency, enabling robust comparisons across geologic contexts. When implemented in Mathematica- 8, the algorithm segments an entire MI image within minutes, surpassing the extent and speed possible with manual segmentation by about a factor of ten. These results indicate that our algorithm enables not only new sedimentological insight from the MER MI data, but also detailed sedimentology with the Mars Science Laboratory’s Mars Hand Lens Instrument.

Icarus↗

The global Landsat archive: Status, consolidation, and direction

New and previously unimaginable Landsat applications have been fostered by a policy change in 2008 that made analysis-ready Landsat data free and open access. Since 1972, Landsat has been collecting images of the Earth, with the early years of the program constrained by onboard satellite and ground systems, as well as limitations across the range of required computing, networking, and storage capabilities. Rather than robust on-satellite storage for transmission via high bandwidth downlink to a centralized storage and distribution facility as with Landsat-8, a network of receiving stations, one operated by the U.S. government, the other operated by a community of International Cooperators (ICs), were utilized. ICs paid a fee for the right to receive and distribute Landsat data and over time, more Landsat data was held outside the archive of the United State Geological Survey (USGS) than was held inside, much of it unique. Recognizing the critical value of these data, the USGS began a Landsat Global Archive Consolidation (LGAC) initiative in 2010 to bring these data into a single, universally accessible, centralized global archive, housed at the Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota. The primary LGAC goals are to inventory the data held by ICs, acquire the data, and ingest and apply standard ground station processing to generate an L1T analysis-ready product. As of January 1, 2015 there were 5,532,454 images in the USGS archive. LGAC has contributed approximately 3.2 million of those images, more than doubling the original USGS archive holdings. Moreover, an additional 2.3 million images have been identified to date through the LGAC initiative and are in the process of being added to the archive. The impact of LGAC is significant and, in terms of images in the collection, analogous to that of having had two additional Landsat-5 missions. As a result of LGAC, there are regions of the globe that now have markedly improved Landsat data coverage, resulting in an enhanced capacity for mapping, monitoring change, and capturing historic conditions. Although future missions can be planned and implemented, the past cannot be revisited, underscoring the value and enhanced significance of historical Landsat data and the LGAC initiative. The aim of this paper is to report the current status of the global USGS Landsat archive, document the existing and anticipated contributions of LGAC to the archive, and characterize the current acquisitions of Landsat-7 and Landsat-8. Landsat-8 is adding data to the archive at an unprecedented rate as nearly all terrestrial images are now collected. We also offer key lessons learned so far from the LGAC initiative, plus insights regarding other critical elements of the Landsat program looking forward, such as acquisition, continuity, temporal revisit, and the importance of continuing to operationalize the Landsat program.

Remote Sensing of Environment↗

Quantifying uncertainty for remote spectroscopy of surface composition

Remote surface measurements by imaging spectrometers play an important role in planetary and Earth science. To make these measurements, investigators calibrate instrument data to absolute units, invert physical models to estimate atmospheric effects, and then determine surface properties from the spectral reflectance. This study quantifies the uncertainty in this process. Global missions demand predictive uncertainty models that can estimate future errors for varied environments and observing conditions. Here we validate uncertainty predictions with remote surface composition retrievals and in situ measurements in a field analogue of Earth and planetary exploration. We consider rover transects at Cuprite, Nevada, and remote observations by NASA's Next- Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG). We show that accounting for input uncertainties can benefit mineral detection methods such as constrained spectrum fitting. This suggests that operational uncertainty estimates could improve future NASA missions like the Earth Mineral dust source InvesTigation (EMIT) and the Lunar Trailblazer mission, as well as NASA's Decadal Surface Biology and Geology (SBG) Investigation.

Remote Sensing of Environment↗

FTIR and py-GC-MS spectra of true-fern and seed-fern sphenopterids (Sydney Coalfield, Nova Scotia, Canada, Pennsylvanian)

Sphenopterid specimens from the Late Pennsylvanian of Sydney Coalfield, Canada, are investigated by FTIR and py-GC-MS techniques as part of an on-going research project into the biochemistry and chemotaxonomy of Pennsylvanian-age pteridophylls. Included in the investigation are samples of the true-fern species Oligocarpia brongniartii and Zeilleria delicatula that are preserved as naturally macerated cuticles (NMC), and the seed-fern Eusphenopteris neuropteroides that is also preserved as a compression/impression. FTIR spectra of NMC seed-fern E. neuropteroides, and fern sphenopterid O. brongniartii are very similar, except that the latter does not have aromatic bands in the 700-900 cm-1 out-of-plane region, py-GC-MS show more aromatic compounds for the seed fern than for the two true-fern sphenopterids. Another difference between seed-fern and true-fern sphenopterids is a lower ratio of CH2 to CH3 in chemically treated specimens (CTC) for the seed fern. These observations suggest slightly higher aromaticity for the seed ferns, perhaps related to some chemotaxonomic differences. Comparison of FTIR and py-GC-MS characteristics of sphenopterids and other plant groups shows that these two techniques have potential to identifying chemotaxonomic signals from Carboniferous pteridophylls in general, although more data are needed to confirm this. ?? 2002 Elsevier Science B.V. All rights reserved.

International Journal of Coal Geology↗

Field calibration and validation of remote-sensing surveys

The Optical Collection Suite (OCS) is a ground-truth sampling system designed to perform in situ measurements that help calibrate and validate optical remote-sensing and swath-sonar surveys for mapping and monitoring coastal ecosystems and ocean planning. The OCS system enables researchers to collect underwater imagery with real-time feedback, measure the spectral response, and quantify the water clarity with simple and relatively inexpensive instruments that can be hand-deployed from a small vessel. This article reviews the design and performance of the system, based on operational and logistical considerations, as well as the data requirements to support a number of coastal science and management projects. The OCS system has been operational since 2009 and has been used in several ground-truth missions that overlapped with airborne lidar bathymetry (ALB), hyperspectral imagery (HSI), and swath-sonar bathymetric surveys in the Gulf of Maine, southwest Alaska, and the US Virgin Islands (USVI). Research projects that have used the system include a comparison of backscatter intensity derived from acoustic (multibeam/interferometric sonars) versus active optical (ALB) sensors, ALB bottom detection, and seafloor characterization using HSI and ALB.

Alaska↗

The role of citzens in detecting and responding to a rapid marine invasion

Documenting and responding to species invasions requires innovative strategies that account for ecological and societal complexities. We used the recent expansion of Indo-Pacific lionfish ( Pterois volitans / miles ) throughout northern Gulf of Mexico coastal waters to evaluate the role of stakeholders in documenting and responding to a rapid marine invasion. We coupled an online survey of spearfishers and citizen science monitoring programs with traditional fishery-independent data sources and found that citizen observations documented lionfish 1–2 years earlier and more frequently than traditional reef fish monitoring programs. Citizen observations first documented lionfish in 2010 followed by rapid expansion and proliferation in 2011 (+367%). From the survey of spearfishers, we determined that diving experience and personal observations of lionfish strongly influenced perceived impacts, and these perceptions were powerful predictors of support for initiatives. Our study demonstrates the value of engaging citizens for assessing and responding to large-scale and time-sensitive conservation problems.

Gulf of Mexico↗

IPOD-USGS multichannel seismic reflection profile from Cape Hatteras to the Mid-Atlantic Ridge

A 3,400-km-long multichannel seismic-reflection profile from Cape Hatteras to the Mid-Atlantic Ridge was acquired commercially under contract to the National Science Foundation and the U.S. Geological Survey. These data show evidence for massive erosion of the continental slope, diapirs at the base of the continental slope, and mantle reflections beneath the Hatteras Abyssal Plain.

Geology↗

Reply to: Turner, R.E., 2014. Discussion of: Olea, R.A. and Coleman, J.L., Jr., 2014. A synoptic examination of causes of land loss in southern Louisiana as related to the exploitation of subsurface geologic resources, Journal of Coastal Research, 30(5), 1025–1044; Journal of Coastal Research, 30(6), 1330–1334.

To a large extent, geology is a science of solving inverse problems based on some data and scientific principles. Solutions to these types of problems are not unique, especially when using different data, invoking different principles, or both. It is not surprising that the discussant and we have reached different conclusions on the same specific issue of land loss along the coast of Louisiana because we use different observations and view those observations in a different context. The objective of this reply is to orient the reader, who then can decide which approach is more likely to be the correct analysis.

Journal of Coastal Research↗