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USGS2008

Geoinformatics 2008 - Data to Knowledge

Geoinformatics is the term used to describe a variety of efforts to promote collaboration between the computer sciences and the geosciences to solve complex scientific questions. It refers to the distributed, integrated digital information system and working environment that provides innovative means for the study of the Earth systems, as well as other planets, through use of advanced information technologies. Geoinformatics activities range from major research and development efforts creating new technologies to provide high-quality, sustained production-level services for data discovery, integration and analysis, to small, discipline-specific efforts that develop earth science data collections and data analysis tools serving the needs of individual communities. The ultimate vision of Geoinformatics is a highly interconnected data system populated with high quality, freely available data, as well as, a robust set of software for analysis, visualization, and modeling. This volume is a collection of extended abstracts for oral papers presented at the Geoinformatics 2008 conference, June 11 and 13, 2008, in Potsdam, Germany.

Scientific Investigations Report↗

USGS2020

Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2018

A potentiometric-surface map for spring 2018 was created for the Mississippi River Valley alluvial (MRVA) aquifer using available groundwater-altitude data from 1,126 wells completed in the MRVA aquifer and from the altitude of the top of the water surface in area rivers from 66 streamgages. Personnel from Arkansas Natural Resources Commission, Arkansas Department of Health, Arkansas Geological Survey, Illinois Department of Agriculture, Illinois State Water Survey, Louisiana Department of Natural Resources, Louisiana Department of Transportation and Development, Mississippi Department of Environmental Quality, Missouri Department of Natural Resources, Yazoo Mississippi Delta Joint Water Management District, U.S. Department of Agriculture-Natural Resources Conservation Service, and U.S. Geological Survey (USGS) routinely collect groundwater-level data from wells screened in the MRVA aquifer. The USGS and the U.S. Army Corps of Engineers routinely collect data on river stage and streamflow for the rivers overlying the MRVA aquifer area. The potentiometric-surface map for 2018 was created utilizing existing groundwater and surface-water altitudes to support investigations to characterize the MRVA aquifer as part of the USGS Water Availability and Use Science Program. Sufficient data were available to map the potentiometric surface of the MRVA aquifer for spring 2018 for about 87 percent of the aquifer area. The potentiometric contours ranged from 10 to 340 feet above North American Vertical Datum of 1988. The regional direction of groundwater flow was generally to the south-southwest, except in areas of groundwater-altitude depressions, where groundwater flowed into the depression, and near rivers, where flow can be from aquifer to the river or from the river into the aquifer. There are large depressions in the potentiometric-surface map in the lower one-half of the Cache region and in most of the Grand Prairie and Delta regions.

Mississippi River Valley alluvial aquifer↗

USGS2026

On-demand global Landsat evapotranspiration product: Development, evaluation, and dissemination

Global actual evapotranspiration (ET) is one of the essential climate variables needed to understand and manage the relationships among food, energy, and water resources. The U.S. Geological Survey Earth Resources Observation and Science (EROS) Center launched a provisional ET product in 2020, offering on-demand, field-scale global coverage derived from Landsat data through the EROS Science Processing Architecture (ESPA) platform. The ESPA interface provides ET data for cloud-free Landsat overpasses starting in 1982 with Landsat 4 through the current Landsat 9. The ET data are delivered as a Provisional Level-3 Science product created using the Operational Simplified Surface Energy Balance (SSEBop) model. Landsat surface temperature and reference ET are the main model drivers along with vegetation index and net radiation for model parameterization. A large volume of Landsat-based ET orders (e.g., over 1,200,000 images from June 2020 through December 2025) around the world indicate increasing awareness and application of the ET data. The ESPA platform enables land and water resource managers and researchers to access a first-order ET product without requiring advanced knowledge of remote sensing technology or evapotranspiration modeling. We present the methodology and workflow of the on-demand Landsat ET product and its performance evaluations over diverse hydro-climatic settings. The product can help estimate field-scale consumptive water use and thus quickly and consistently assess historical water use, allocation, and budget to inform water management under changing environments. Future ET data aggregated to monthly and seasonal time scales are expected to enhance integration with decision-making tools and procedures.

Remote Sensing of Environment↗

USGS2012

Sound data management as a foundation for natural resources management and science

Effective decision making is closely related to the quality and completeness of available data and information. Data management helps to ensure data quality in any discipline and supports decision making. Managing data as a long-term scientific asset helps to ensure that data will be usable beyond the original intended application. Emerging issues in water-resources management and climate variability require the ability to analyze change in the conditions of natural resources over time. The availability of quality, well-managed, and documented data from the past and present helps support this requirement.

Fact Sheet↗

USGS2025

Altitude of the potentiometric surface and depth to water in the Mississippi River Valley alluvial aquifer, spring 2022

Potentiometric-surface and depth-to-water maps for spring 2022 were created for the Mississippi River Valley alluvial aquifer (MRVA) using groundwater-altitude data from 1,136 wells completed in the MRVA and from the altitude of the top of the water surface in area rivers from 160 streamgages. The potentiometric-surface and depth-to-water maps for 2022 were created to support investigations to characterize the MRVA as part of the U.S. Geological Survey Water Availability and Use Science Program. Sufficient data were available to map the potentiometric surface and depth to water of the MRVA for spring 2022 for about 83 percent of the aquifer area. The potentiometric contours ranged from 0 to 340 feet (ft) above the North American Vertical Datum of 1988. The regional direction of groundwater gradient was generally to the south-southwest, except in areas of groundwater-altitude depressions, where the groundwater gradient was into the depression, and near rivers, where the groundwater gradient can be from aquifer to the river or from the river into the aquifer. There are large depressions in the potentiometric-surface map in the lower one-half of the Cache region and in much of the Grand Prairie and Delta regions. Depth to water in the MRVA, spring 2022, by well ranged from 5.00 ft above land surface to 145.66 ft below land surface.

Mississippi River Valley alluvial aquifer↗

USGS2013

Correlating multispectral imaging and compositional data from the Mars Exploration Rovers and implications for Mars Science Laboratory

In an effort to infer compositional information about distant targets based on multispectral imaging data, we investigated methods of relating Mars Exploration Rover (MER) Pancam multispectral remote sensing observations to in situ alpha particle X-ray spectrometer (APXS)-derived elemental abundances and Mössbauer (MB)-derived abundances of Fe-bearing phases at the MER field sites in Gusev crater and Meridiani Planum. The majority of the partial correlation coefficients between these data sets were not statistically significant. Restricting the targets to those that were abraded by the rock abrasion tool (RAT) led to improved Pearson’s correlations, most notably between the red–blue ratio (673 nm/434 nm) and Fe 3+ -bearing phases, but partial correlations were not statistically significant. Partial Least Squares (PLS) calculations relating Pancam 11-color visible to near-IR (VNIR; ∼400–1000 nm) “spectra” to APXS and Mössbauer element or mineral abundances showed generally poor performance, although the presence of compositional outliers led to improved PLS results for data from Meridiani. When the Meridiani PLS model for pyroxene was tested by predicting the pyroxene content of Gusev targets, the results were poor, indicating that the PLS models for Meridiani are not applicable to data from other sites. Soft Independent Modeling of Class Analogy (SIMCA) classification of Gusev crater data showed mixed results. Of the 24 Gusev test regions of interest (ROIs) with known classes, 11 had >30% of the pixels in the ROI classified correctly, while others were mis-classified or unclassified. k-Means clustering of APXS and Mössbauer data was used to assign Meridiani targets to compositional classes. The clustering-derived classes corresponded to meaningful geologic and/or color unit differences, and SIMCA classification using these classes was somewhat successful, with >30% of pixels correctly classified in 9 of the 11 ROIs with known classes. This work shows that the relationship between SWIR multispectral imaging data and APXS- and Mössbauer-derived composition/mineralogy is often weak, a perhaps not entirely unexpected result given the different surface sampling depths of SWIR imaging (uppermost few microns) vs. APXS (tens of μm) and MB measurements (hundreds of μm). Results from the upcoming Mars Science Laboratory (MSL) rover’s ChemCam Laser Induced Breakdown Spectroscopy (LIBS) instrument may show a closer relationship to Mastcam SWIR multispectral observations, however, because the initial laser shots onto a target will analyze only the upper few micrometers of the surface. The clustering and classification methods used in this study can be applied to any data set to formalize the definition of classes and identify targets that do not fit in previously defined classes.

Icarus↗

USGS2026

Altitude of the potentiometric surface and depth to water in the Mississippi River Valley alluvial aquifer, spring 2024

Potentiometric-surface and depth-to-water maps for spring 2024 were created for the Mississippi River Valley alluvial aquifer using groundwater-altitude data from 1,151 wells completed in the Mississippi River Valley alluvial aquifer and from the altitude of the top of the water surface in area rivers from 160 U.S. Geological Survey and U.S. Army Corps of Engineers streamgages. The potentiometric-surface and depth-to-water maps for 2024 were created to support investigations to characterize the Mississippi River Valley alluvial aquifer as part of the U.S. Geological Survey Water Availability and Use Science Program. Sufficient data were available to map the potentiometric surface and depth to water of the Mississippi River Valley alluvial aquifer for spring 2024 for about 83 percent of the aquifer area. The potentiometric contours ranged from 0 to 330 feet (ft) above the North American Vertical Datum of 1988. The regional direction of the groundwater gradient was generally to the south-southwest, except in areas of groundwater-altitude depressions, where the groundwater gradient direction was into the depression, and near rivers, where the groundwater gradient direction was either from the aquifer to the river or from the river into the aquifer. Groundwater depressions in the potentiometric-surface map are in the lower one-half of the Cache region and in most of the Grand Prairie and Delta regions. Depth to water by well in the Mississippi River Valley alluvial aquifer in spring 2024 ranged from 0.27 ft above land surface to 145.65 ft below land surface.

Arkansas, Illinois, Kentucky, Louisiana, Mississip↗

USGS2024

North Central Climate Adaptation Science Center regional science plan—2023–28

The U.S. Geological Survey North Central Climate Adaptation Science Center (NC CASC), established in 2012, is part of a national network supporting climate-informed decisions that benefit wildlife and habitats. The NC CASC provides climate science for the U.S. Department of the Interior, State agencies, and Tribal nations to support effective resource management. Collaborating with the National and Regional Climate Adaptation Science Center network, the NC CASC addresses multiregion challenges through a partnership involving the U.S. Geological Survey and additional regional partners. Input is collected from an Advisory Committee of State, Federal, and Tribal Government representatives. The center hosts Tribal Climate Resilience Liaisons, which are funded by the Bureau of Indian Affairs Branch of Tribal Climate Resilience and aligned with a Tribal Engagement Strategy. Positioned at the meeting point of scientists and managers and guided by core values, the NC CASC studies diverse ecosystems affected by climate change and empowers resource managers with actionable data and innovative science. This report outlines the 5-year Science Plan (hereafter “the Plan”) for the NC CASC. The center uses stakeholder engagement and coproduction of knowledge for effective collaboration, including engagement of Advisory Committee members and other management partners in the development of the Plan. The Plan provides a high-level overview of the NC CASC, covering the center’s geographical scope, key collaborators, stakeholders, and the strategic framework guiding the application of climate science to make informed management decisions. The Plan also summarizes management challenges and scientific objectives related to the impact of climate change on habitat, ecological drought, wildlife disease, invasives and encroachment, fire, and phenology.

Colorado, Kansas, Montana, North Dakota, Nebraska,↗

USGS2012

Expanded stream gauging includes groundwater data and trends

Population growth has increased water scarcity to the point that documenting current amounts of worldwide water resources is now as critical as any data collection in the Earth sciences. As a key element of this data collection, stream gauges yield continuous hydrologic information and document long-term trends, recording high-frequency hydrologic information over decadal to centennial time frames.

Eos, Transactions, American Geophysical Union↗

USGS2022

WHISPers—Providing situational awareness of wildlife disease threats to the Nation—A fact sheet for the biosurveillance community

Solutions for emerging infectious disease and bioterror threats can be improved by incorporating integrated biodefense strategies, including improved surveillance for animal and zoonotic diseases, strong national leadership, and effective management tools. Active biosurveillance for disease events is key to early detection, warning, and overall situational awareness and enables better communication, coordination, decision making, and data-driven responses. The national biosurveillance infrastructure has well-established channels for human and domestic animal health data through the Centers for Disease Control and Prevention and U.S. Department of Agriculture, and State, county, and local authorities. Wildlife disease information, however, has been more challenging to acquire and access, in part, due to the comparatively small infrastructure and resources dedicated to wildlife health and also because regulatory authority for wildlife and wildlife health is split among Federal, State, Tribal, and indigenous natural resource authorities. To address these issues, the Wildlife Health Information Sharing Partnership-event reporting system (WHISPers; https://whispers.usgs.gov ) was developed by the U.S. Geological Survey National Wildlife Health Center to promote collaboration and sharing of wildlife health information and to provide situational awareness and timely information about wildlife disease threats. WHISPers is a free science gateway and data portal that provides interactive query, display, reporting, and export capabilities for wildlife health event summary information.

Fact Sheet↗

USGS2023

Ten best practices for effective phenological research

The number and diversity of phenological studies has increased rapidly in recent years. Innovative experiments, field studies, citizen science projects, and analyses of newly available historical data are contributing insights that advance our understanding of ecological and evolutionary responses to the environment, particularly climate change. However, many phenological data sets have peculiarities that are not immediately obvious and can lead to mistakes in analyses and interpretation of results. This paper aims to help researchers, especially those new to the field of phenology, understand challenges and practices that are crucial for effective studies. For example, researchers may fail to account for sampling biases in phenological data, struggle to choose or design a volunteer data collection strategy that adequately fits their project’s needs, or combine data sets in inappropriate ways. We describe ten best practices for designing studies of plant and animal phenology, evaluating data quality, and analyzing data. Practices include accounting for common biases in data, using effective citizen or community science methods, and employing appropriate data when investigating phenological mismatches. We present these best practices to help researchers entering the field take full advantage of the wealth of available data and approaches to advance our understanding of phenology and its implications for ecology.

International Journal of Biometeorology↗

USGS2005

Water resources data, Colorado, water year 2004

Water-resources data for Colorado for the 2004 water year (WY) in this report consist of records of stage and discharge of streams; and stage and contents of one reservoir. This report contains discharge records for 312 gaging stations, stage and contents of 1 lake and reservoir, discharge measurements for 1 partial-record low-flow station and 1 miscellaneous site, and peak-flow information for 22 crest-stage partial-record stations. Three pertinent stations operated by bordering states, and 34 stations operated by the Colorado Division of Water Resources are included in this report. All records (except as just noted) were collected and computed by the Water Resources Discipline of the U.S. Geological Survey under the direction of J.E. Kircher, Director, USGS Colorado Water Science Center. These data represent that part of the National Water Information System collected by the U.S. Geological Survey and cooperating State and Federal agencies.

Water Data Report↗

USGS2010

Seabird databases and the new paradigm for scientific publication and attribution

For more than 300 years, the peer-reviewed journal article has been the principal medium for packaging and delivering scientific data. With new tools for managing digital data, a new paradigm is emerging—one that demands open and direct access to data and that enables and rewards a broad-based approach to scientific questions. Ground-breaking papers in the future will increasingly be those that creatively mine and synthesize vast stores of data available on the Internet. This is especially true for conservation science, in which essential data can be readily captured in standard record formats. For seabird professionals, a number of globally shared databases are in the offing, or should be. These databases will capture the salient results of inventories and monitoring, pelagic surveys, diet studies, and telemetry. A number of real or perceived barriers to data sharing exist, but none is insurmountable. Our discipline should take an important stride now by adopting a specially designed markup language for annotating and sharing seabird data.

Marine Ornithology: Journal of Seabird Research an↗

USGS2022

Landsat data ecosystem case study: Actor perceptions of the use and value of landsat

It is well-known that Earth observation (EO) data plays a critical role in scientific understanding about the global environment. There is also growing support for the use of EO data to provide context-specific insights, with significant implications for their use in decision support systems. Technological development over recent years, including cloud computing infrastructure, machine learning techniques, and rapid expansion of the velocity, volume, and variety of space-borne data sources, offer huge potential to provide solutions to the myriad environmental problems facing society and the planet. The USGS/NASA Landsat Program, the longest continuously gathered source of land surface data, has played a central role in our understanding of environmental change, particularly for its contribution of longitudinal products that offer greater context for present research and decision support activities. The challenge facing the Landsat and EO data community, however, now lies in moving beyond context-specific knowledge generation to translating such knowledge into tangible value for society. Drawing from an open data ecosystem framework and qualitative social science methods, we map the Landsat data ecosystem (LDE) and the relationships linking multiple actors responsible for processing, indexing, analyzing, synthesizing, and translating raw Landsat data into information that is useful, useable, and used by end users in particular social-environmental contexts. Both the role of Big Data and associated technologies are discussed as they relate to the ultimate use of Landsat-derived information products to guide decision-making, and key data ecosystem characteristics that shape the likelihood of these products’ use are highlighted.

Frontiers in Environmental Science↗

USGS2003

Selected applications of hydrologic science and research in Maryland, Delaware, and Washington, D.C., 2001-2003

One of the roles of the U.S. Geological Survey (USGS) is to provide reliable water data and unbiased water science needed to describe and understand the Nation?s water resources. This fact sheet describes selected techniques that were used by the USGS to collect, transmit, evaluate, or interpret data, in support of investigations that describe the quantity and quality of water resources in Maryland (MD), Delaware (DE), and the District of Columbia (D.C.). These hydrologic investigations generally were performed in cooperation with universities, research centers, and other Federal, State, and local Government agencies. The applications of hydrologic science and research that were selected for this fact sheet were used or tested in the MD-DE-DC District from 2001 through 2003, and include established methods, new approaches, and preliminary research. The USGS usually relies on standard methods or protocols when conducting water-resources research. Occasionally, traditional methods must be modified to address difficult environmental questions or challenging sampling conditions. Technologies developed for other purposes can sometimes be successfully applied to the collection or dissemination of water-resources data. The USGS is continually exploring new ways to collect, transmit, evaluate, and interpret data. The following applications of hydrologic science and research illustrate a few of the recent advances made by scientists working for and with the USGS.

Fact Sheet↗

USGS2002

Effects of a coastal golf complex on water quality, periphyton, and seagrass

The objective of this study was to provide baseline information on the effects of a golf course complex on water quality, colonized periphyton, and seagrass meadows in adjacent freshwater, near-coastal, and wetland areas. The chemical and biological impacts of the recreational facility, which uses reclaimed municipal wastewater for irrigation, were limited usually to near-field areas and decreased seaward during the 2-year study. Concentrations of chromium, copper, and organochlorine pesticides were below detection in surface water, whereas mercury, lead, arsenic, and atrazine commonly occurred at all locations. Only mercury and lead exceeded water quality criteria. Concentrations of nutrients and chlorophyll a were greater in fairway ponds and some adjacent coastal areas relative to reference locations and Florida estuaries. Periphyton ash free dry weight and pigment concentrations statistically differed but not between reference and non-reference coastal areas. Biomass of Thalassia testudinum (turtle grass) was approximately 43% less in a meadow located adjacent to the golf complex (P < 0.05). The results of the study suggest that the effects of coastal golf courses on water quality may be primarily localized and limited to peripheral near-coastal areas. However, this preliminary conclusion needs additional supporting data. ?? 2002 Elsevier Science (USA).

Florida↗

USGS2006

Balancing data sharing requirements for analyses with data sensitivity

Data sensitivity can pose a formidable barrier to data sharing. Knowledge of species current distributions from data sharing is critical for the creation of watch lists and an early warning/rapid response system and for model generation for the spread of invasive species. We have created an on-line system to synthesize disparate datasets of non-native species locations that includes a mechanism to account for data sensitivity. Data contributors are able to mark their data as sensitive. This data is then 'fuzzed' in mapping applications and downloaded files to quarter-quadrangle grid cells, but the actual locations are available for analyses. We propose that this system overcomes the hurdles to data sharing posed by sensitive data. ?? 2006 Springer Science+Business Media B.V.

Biological Invasions↗

USGS2007

Application of two tests of multivariate discordancy to fisheries data sets

The generalized (Mahalanobis) distance and multivariate kurtosis are two powerful tests of multivariate discordancies (outliers). Unlike the generalized distance test, the multivariate kurtosis test has not been applied as a test of discordancy to fisheries data heretofore. We applied both tests, along with published algorithms for identifying suspected causal variable(s) of discordant observations, to two fisheries data sets from Lake Erie: total length, mass, and age from 1,234 burbot, Lota lota; and 22 combinations of unique subsets of 10 morphometrics taken from 119 yellow perch, Perca flavescens. For the burbot data set, the generalized distance test identified six discordant observations and the multivariate kurtosis test identified 24 discordant observations. In contrast with the multivariate tests, the univariate generalized distance test identified no discordancies when applied separately to each variable. Removing discordancies had a substantial effect on length-versus-mass regression equations. For 500-mm burbot, the percent difference in estimated mass after removing discordancies in our study was greater than the percent difference in masses estimated for burbot of the same length in lakes that differed substantially in productivity. The number of discordant yellow perch detected ranged from 0 to 2 with the multivariate generalized distance test and from 6 to 11 with the multivariate kurtosis test. With the kurtosis test, 108 yellow perch (90.7%) were identified as discordant in zero to two combinations, and five (4.2%) were identified as discordant in either all or 21 of the 22 combinations. The relationship among the variables included in each combination determined which variables were identified as causal. The generalized distance test identified between zero and six discordancies when applied separately to each variable. Removing the discordancies found in at least one-half of the combinations (k=5) had a marked effect on a principal components analysis. In particular, the percent of the total variation explained by second and third principal components, which explain shape, increased by 52 and 44% respectively when the discordancies were removed. Multivariate applications of the tests have numerous ecological advantages over univariate applications, including improved management of fish stocks and interpretation of multivariate morphometric data. ?? 2007 Springer Science+Business Media B.V.

Environmental Biology of Fishes↗