SEARCH · USGS Science

Results for “Scientific Data”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17Linked to original sources

USGS2022

Global food-security-support-analysis data at 30-m resolution (GFSAD30) cropland-extent products—Download Analysis

Introduction The global food-security-support-analysis data at 30-meter resolution (GFSAD30) cropland-extent product is a project to provide high-resolution global cropland-extent data relating to water use. It is the first global-land-cover map focusing exclusively on agriculture with a 30-meter spatial resolution. The overarching goal of the GFSAD30 project is to produce consistent and unbiased estimates of global agricultural cropland products such as cropland extent; cropland types; irrigated versus rainfed cropland; cropping intensities; and spatial and temporal (from 2000 to 2017) changes in cropland extent. The goal of this report is to assess and discuss the usage of the GFSAD30 project’s cropland-extent product. Since the public release of GFSAD30 in November 2017, the number of files downloaded has been tracked, as well as the total size of files downloaded, the country from which the GFSAD30 data were downloaded, and the user’s field of study. This report presents a monthly assessment of the usage of GFSAD30 from November 2017 through December 2019. During this period, about 1,900 gigabytes of data and about 225,000 files were downloaded by users in more than 100 countries. This report also includes how GFSAD30 has been cited in media, scientific journals, and other data products. The release of data was widely covered by the national and international press, and GFSAD30 products have been cited more than 200 times in scientific journals.

Open-File Report↗

USGS2012

Report on progress at the Center for Engineering Strong Motion Data (CESMD)

Strong-motion data of engineering and scientific importance from the United States and other seismically active countries are served through the Center for Engineering Strong Motion Data (CESMD) at www.strongmotioncenter.org. Recently, the CESMD staff, with cooperation from colleagues at international strong-motion seismic networks, has disseminated strong-motion data from significant earthquakes that occurred in Italy, Haiti, Mexico, New Zealand, Chile, Japan, Turkey, and the United States. The CESMD now automatically posts strong-motion data from an increasing number of seismic stations in California within a few minutes following an earthquake as an Internet Quick Report (IQR). As appropriate, IQRs are updated by more comprehensive Internet Data Reports that include reviewed versions of the data and maps showing, for example, the finite fault rupture along with the distribution of recording stations. Automated processing of strong-motion data will be extended to post the strong-motion records of the regional seismic networks of the Advanced National Seismic System (ANSS) outside California. Transfer of the operational and maintenance responsibilities for the Consortium of Organizations for Strong Motion Observation Systems (COSMOS) Virtual Data Center (VDC) from the University of California at Santa Barbara to the CESMD is nearing completion. The VDC Tagged Format (VTF) file format has been adopted by the CESMD as the standard for converting strong motion data to facilitate the process of uploading data into the VDC database. The CESMD now provides strong-motion records from lower magnitude (<M3.5) and smaller amplitude (<0.5%g) records for use in developing ground motion prediction equations in areas with less frequent earthquakes, such as the Central and Eastern US.

Conference Paper↗

USGS2017

Scientific monitoring plan in support of the selected alternative of the Glen Canyon Dam Long-Term Experimental and Management Plan

Introduction The purpose of this document is to describe a strategy by which monitoring and research data in the natural and social sciences will be collected, analyzed, and provided to the U.S. Department of the Interior (DOI), its bureaus, and to the Glen Canyon Dam Adaptive Management Program (GCDAMP) in support of implementation of the Glen Canyon Dam Long-Term Experimental and Management Plan (LTEMP) (U.S. Department of the Interior, 2016a). The selected alternative identified in the LTEMP Record of Decision (ROD) (U.S. Department of the Interior, 2016b) describes various data collection, analysis, modeling, and interpretation efforts to be conducted by the U.S. Geological Survey’s (USGS) Grand Canyon Monitoring and Research Center (GCMRC), partner agencies, and cooperators that will inform decisions about operations of Glen Canyon Dam and management of downstream resources between 2017 and 2037, the performance period of the LTEMP. General data collection, analysis, modeling, and interpretation activities are described in this science plan, whereas specific monitoring and research activities and detailed study plans are to be described in the GCDAMP’s triennial work plans (TWPs) to be developed by the Bureau of Reclamation and GCMRC with input from partner agencies and cooperators during the LTEMP period, which are to be reviewed and recommended by the GCDAMP and approved by the Secretary of the Interior. The GCDAMP consists of several components, the primary committee being the Adaptive Management Work Group (AMWG). This Federal advisory committee is composed of 25 agencies and stakeholder groups and is chaired by the Secretary of the Interior’s designee. The AMWG makes recommendations to the Secretary of the Interior concerning operations of Glen Canyon Dam and other experimental management actions that are intended to fulfill some obligations of the Grand Canyon Protection Act of 1992. The Technical Work Group (TWG) is a subcommittee of the AMWG and provides technical advice to the AMWG. It is composed of technical and science representatives from the same agencies and stakeholder groups who serve on the AMWG. GCMRC is the primary science provider to the GCDAMP and also coordinates many aspects of the science performed by cooperators and partner agencies. The Science Advisors Program provides independent science reviews and advice at the request of the GCDAMP. The plan proposed here necessarily depends on (1) the protocol for decision-making and the requirements for scientific data reporting described in the LTEMP ROD, (2) the priorities of the GCDAMP as directed by the LTEMP ROD (see Department of the Interior, 2016b, section 6.1), (3) the priorities for monitoring and research in the conservation measures section of the Biological Opinion for the LTEMP (U.S. Department of the Interior, 2016b, LTEMP ROD attachment E), (4) the priorities for resource management and information needs established by Federal and State resource-management agencies within the GCDAMP, (5) scientific understanding about the linkage between the status of those resources and operations of Glen Canyon Dam, and (6) the need to resolve existing scientific uncertainties about the linkage between dam operations and the condition of resources. We note that resource-management prioritization is fundamentally a policy decision charged specifically to DOI for the Colorado River in Glen and Grand Canyons, as outlined most recently in the LTEMP ROD, and is not the responsibility of the GCMRC. However, it is the responsibility of the GCMRC to describe the nature of scientific understanding, the nature of scientific uncertainty, and the risk of making resourcemanagement decisions in the face of existing scientific uncertainty. The goals of science activities in the next 20 years are to inform operational decisions regarding Glen Canyon Dam operations described in the LTEMP ROD, resolve remaining scientific uncertainties, and to monitor resource trends that are affected entirely, or in part, by dam operations.

Open-File Report↗

USGS2018

Evaluation of key scientific issues in the report, “State of the mountain lion—A call to end trophy hunting of America’s lion”

In their recently published report, State of the Mountain Lion: A Call to End Trophy Hunting of America’s Lion , the Humane Society of the United States suggested that mountain lion ( Puma concolor ) hunting should be abolished in the United States. The report claims this recommendation is based on scientific arguments that demonstrate the overharvest of mountain lions throughout much of their current range in the United States. We reviewed the science presented by the Humane Society to support their call for the cessation of mountain lion hunting. Rather than provide a rigorous assessment of the peer-reviewed scientific literature and available data on mountain lion ecology, population dynamics and management, the report uses a fundamentally unscientific approach that starts with an a priori assumption that hunting is detrimental to the long-term persistence of mountain lion populations, then attempts to use scientific arguments to support this value-based position. The report frequently ignores or selectively interprets relevant peer-reviewed literature, weakening the scientific credibility of the report. The report relies on imprecise and inadequate demographic measures, questionable data, and simplistic methodologies to derive dubious estimates of potential lion densities; it compares these estimates to various measures produced by State agencies (which themselves vary in reliability as estimates of abundance) to purportedly illustrate the detrimental effects of hunting. The approach used in the report to support the predetermined supposition that mountain lion populations are over-hunted fails to serve as a scientifically defensible foundation for management recommendations range-wide or at the State level.

Open-File Report↗

USGS2009

The scientific assessment and strategy team contributions assessing the 1993 flood on the Mississippi and Missouri River basins

The Scientific Assessment and Strategy Team was formed to provide scientific advice and assistance to federal officials responsible for making decisions with respect to flood recovery in the Upper Mississippi River Basin (above Cairo, Illinois) as a result of the 1993 flooding. The team assembled data from a wide variety of sources within federal, state, and local governments, and the private sector. The huge volume of data (over 250 gigabytes) made analysis of all the data difficult. The locating, obtaining, and conversion of the data were extremely difficult leading to a recommendation for an on-line source or at least an on-line listing of available data. Parts of the data were analyzed and scientific bases were establishedfor discussions concerning levee effects on flood stages, effects of wetlands on flooding , effects of man 's increased intervention in the floodplains and uplands, and proposals regarding floodways on the nations rivers. The data collected indicated that the 1993 flooding could not be attributed to man's intervention on the floodplain but to the excessive amount of rainfall in the basin. The stormpatterns thatproduced the rainfall also moved south at about the same speed as the flood waters resulting in storms later in the summer reinforcing early floods. This resulted in a very long duration flood that overwhelmed existing flood reduction measures in the portions of the basin that were flooded.

Mississppi River basin, Missouri River basin↗

USGS2017

Synthesis centers as critical research infrastructure

Demand for the opportunity to participate in a synthesis-center activity has increased in the years since the US National Science Foundation (NSF)–funded National Center for Ecological Analysis and Synthesis (NCEAS) opened its doors in 1995 and as more scientists across a diversity of scientific disciplines have become aware of what synthesis centers provide. The NSF has funded four synthesis centers, and more than a dozen new synthesis centers have been established around the world, some following the NSF model and others following different models suited to their national funding environment ( http://synthesis-consortium.org ). Scientific synthesis integrates diverse data and knowledge to increase the scope and applicability of results and yield novel insights or explanations within and across disciplines (Pickett et al. 2007 , Carpenter et al. 2009 ). The demand for synthesis comes from the pressing societal need to address grand challenges related to global change and other issues that cut across multiple societal sectors and disciplines and from recognition that substantial added scientific value can be achieved through the synthesis-based analysis of existing data. Demand also comes from groups of scientists who see exciting opportunities to generate new knowledge from interdisciplinary and transdisciplinary collaboration, often capitalizing on the increasingly large volume and variety of available data (Kelling et al. 2009 , Bishop et al. 2014 , Specht et al. 2015b ). The ever-changing nature of societal challenges and the availability of data with which to address them suggest there will be an expanding need for synthesis. However, we are now entering a phase in which government support for some existing synthesis centers has ended or will be ending soon, forcing those centers to close or develop new operational models, approaches, and funding streams. We argue here that synthesis centers play such a unique role in science that continued long-term public investment to maximize benefits to science and society is justified. In particular, we argue that synthesis centers represent community infrastructure more akin to research vessels than to term-funded centers of science and technology (e.g., NSF Science and Technology Centers). Through our experience running synthesis centers and, in some cases, developing postfederal funding models, we offer our perspective on the purpose and value of synthesis centers. We present case studies of different outcomes of transition plans and argue for a fundamental shift in the conception of synthesis science and the strategic funding of these centers by government funding agencies.

BioScience↗

USGS2009

Optical satellite data volcano monitoring: a multi-sensor rapid response system

In this chapter, the use of satellite remote sensing to monitor active geological processes is described. Specifically, threats posed by volcanic eruptions are briefly outlined, and essential monitoring requirements are discussed. As an application example, a collaborative, multi-agency operational volcano monitoring system in the north Pacific is highlighted with a focus on the 2007 eruption of Kliuchevskoi volcano, Russia. The data from this system have been used since 2004 to detect the onset of volcanic activity, support the emergency response to large eruptions, and assess the volcanic products produced following the eruption. The overall utility of such integrative assessments is also summarized. The work described in this chapter was originally funded through two National Aeronautics and Space Administration (NASA) Earth System Science research grants that focused on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument. A skilled team of volcanologists, geologists, satellite tasking experts, satellite ground system experts, system engineers and software developers collaborated to accomplish the objectives. The first project, Automation of the ASTER Emergency Data Acquisition Protocol for Scientific Analysis, Disaster Monitoring, and Preparedness , established the original collaborative research and monitoring program between the University of Pittsburgh (UP), the Alaska Volcano Observatory (AVO), the NASA Land Processes Distributed Active Archive Center (LP DAAC) at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, and affiliates on the ASTER Science Team at the Jet Propulsion Laboratory (JPL) as well as associates at the Earth Remote Sensing Data Analysis Center (ERSDAC) in Japan. This grant, completed in 2008, also allowed for detailed volcanic analyses and data validation during three separate summer field campaigns to Kamchatka Russia. The second project, Expansion and synergistic use of the ASTER Urgent Request Protocol (URP) for natural disaster monitoring and scientific analysis , has expanded the project to other volcanoes around the world and is in progress through 2011. The focus on ASTER data is due to the suitability of the sensor for natural disaster monitoring and the availability of data. The instrument has several unique facets that make it especially attractive for volcanic observations (Ramsey and Dehn, 2004). Specifically, ASTER routinely collects data at night, it has the ability to generate digital elevation models using stereo imaging, it can collect data in various gain states to minimize data saturation, it has a cross-track pointing capability for faster targeting, and it collects data up to ±85° latitude for better global coverage. As with any optical imaging-based remote sensing, the viewing conditions can negatively impact the data quality. This impact varies across the optical and thermal infrared wavelengths as well as being a function of the specific atmospheric window within a given wavelength region. Water vapor and cloud formation can obscure surface data in the visible and near infrared (VNIR)/shortwave infrared (SWIR) region due mainly to non-selective scattering of the incident photons. In the longer wavelengths of the thermal infrared (TIR), scattering is less of an issue, but heavy cloud cover can still obscure the ground due to atmospheric absorption. Thin clouds can be optically-transparent in the VNIR and TIR regions, but can cause errors in the extracted surface reflectance or derived surface temperatures. In regions prone to heavy cloud cover, optical remote sensing can be improved through increased temporal resolution. As more images are acquired in a given time period the chances of a clear image improve dramatically. The Advanced Very High Resolution Radiometer (AVHRR) routine monitoring, which commonly collects 4-6 images per day of any north Pacific volcano, takes advantage of this fact. The rapid response program described in this chapter also improves the temporal resolution of the ASTER instrument. ASTER has been acquiring images of volcanic eruptions since soon after its launch in December 1999. An early example included the observations of the large pyroclastic flow deposit emplaced at Bezymianny volcano in Kamchatka, Russia. The first images in March 2000, just weeks after the eruption, revealed the extent, composition, and cooling history of this large deposit and of the active lava dome (Ramsey and Dehn, 2004). The initial results from these early datasets spurred interest in using ASTER data for expanded volcano monitoring in the north Pacific. It also gave rise to the multi-year NASA-funded programs of rapid response scheduling and imaging throughout the Aleutian, Kamchatka and Kurile arcs. Since the formal establishment of the programs, the data have provided detailed descriptions of the eruptions of Augustine, Bezymianny, Kliuchevskoi and Sheveluch volcanoes over the past nine years (Wessels et al., in press; Carter et al., 2007, 2008; Ramsey et al., 2008; Rose and Ramsey, 2009). The initial research focus of this rapid response program was specifically on automating the ASTER sensor’s ability for targeted observational scheduling using the expedited data system. This urgent request protocol is one of the unique characteristics of ASTER. It provides a limited number of emergency observations, typically at a much-improved temporal resolution and quicker turnaround with data processing in the United States rather than in Japan. This can speed the reception of the processed data by several days to a week. The ongoing multi-agency research and operational collaboration has been highly successful. AVO serves as the primary source for status information on volcanic activity, working closely with the National Weather Service (NWS), Federal Aviation Administration (FAA), military and other state and federal emergency services. Collaboration with the Russian Institute of Volcanology and Seismology (IVS)/Kamchatka Volcanic Eruption Response Team (KVERT) is also maintained. Once a volcano is identified as having increased thermal output, ASTER is automatically tasked and the volcano is targeted at the next available opportunity. After the data are acquired, scientists at all the agencies have access to the images, with the primary science analysis carried out at the University of Pittsburgh and AVO. Results are disseminated to the responsible monitoring agencies and the global community through e-mail mailing lists.

Book chapter↗

USGS1985

Water Resources Division in the 1980's : a summary of activities and programs of the U.S. Geological Survey's Water Resources Division

The Water Resources Division of the U.S. Geological Survey has the principal responsibility within the Federal government for providing hydrologic information and appraising the Nation's water resounds. The Geological Survey is unique among government organizations because it has neither regulatory nor developmental authority--its sole product is information that is made available equally to all interested parties. This report describes the Water Resources Division's mission, organization, source of funds, and major programs. Three types of programs are described: long-term programs, which include the Federal-State cooperative program, coordination of Federal water-data acquisition, assistance to other Federal agencies, the national research program, the national water-data exchange, the water resources scientific information center, the national water-use information program, hydrologic-data collection, and international hydrology activities; topical programs, which include hazardous waste hydrology, coal and oil-shale hydrology, regional aquifer system analyses, acid rain, volcano hazards, and national water-resources conditions; and technical-assistance programs. Emphasis is on programs that will contribute to identifying, mitigating, or solving nationwide water-resources problems in the 1980's. A discussion of how the data and information axe disseminated and a selected list of references complete the report.

Circular↗

USGS1983

Water Resources Division in the 1980's

Circular↗

USGS2018

Generating community-built tools for data sharing and analysis in environmental networks

Rapid data growth in many environmental sectors has necessitated tools to manage and analyze these data. The development of tools often lags behind the proliferation of data, however, which may slow exploratory opportunities and scientific progress. The Global Lake Ecological Observatory Network (GLEON) collaborative model supports an efficient and comprehensive data–analysis–insight life cycle, including implementations of data quality control checks, statistical calculations/derivations, models, and data visualizations. These tools are community-built and openly shared. We discuss the network structure that enables tool development and a culture of sharing, leading to optimized output from limited resources. Specifically, data sharing and a flat collaborative structure encourage the development of tools that enable scientific insights from these data. Here we provide a cross-section of scientific advances derived from global-scale analyses in GLEON. We document enhancements to science capabilities made possible by the development of analytical tools and highlight opportunities to expand this framework to benefit other environmental networks.

Inland Waters↗

USGS1999

Managing data from multiple disciplines, scales, and sites to support synthesis and modeling

The synthesis and modeling of ecological processes at multiple spatial and temporal scales involves bringing together and sharing data from numerous sources. This article describes a data and information system model that facilitates assembling, managing, and sharing diverse data from multiple disciplines, scales, and sites to support integrated ecological studies. Cross-site scientific-domain working groups coordinate the development of data associated with their particular scientific working group, including decisions about data requirements, data to be compiled, data formats, derived data products, and schedules across the sites. The Web-based data and information system consists of nodes for each working group plus a central node that provides data access, project information, data query, and other functionality. The approach incorporates scientists and computer experts in the working groups and provides incentives for individuals to submit documented data to the data and information system.

Remote Sensing of Environment↗

USGS2001

A comparison of U.S. geological survey seamless elevation models with shuttle radar topography mission data

Elevation models produced from Shuttle Radar Topography Mission (SRTM) data will be the most comprehensive, consistently processed, highest resolution topographic dataset ever produced for the Earth's land surface. Many applications that currently use elevation data will benefit from the increased availability of data with higher accuracy, quality, and resolution, especially in poorly mapped areas of the globe. SRTM data will be produced as seamless data, thereby avoiding many of the problems inherent in existing multi-source topographic databases. Serving as precursors to SRTM datasets, the U.S. Geological Survey (USGS) has produced and is distributing seamless elevation datasets that facilitate scientific use of elevation data over large areas. GTOPO30 is a global elevation model with a 30 arc-second resolution (approximately 1-kilometer). The National Elevation Dataset (NED) covers the United States at a resolution of 1 arc-second (approximately 30-meters). Due to their seamless format and broad area coverage, both GTOPO30 and NED represent an advance in the usability of elevation data, but each still includes artifacts from the highly variable source data used to produce them. The consistent source data and processing approach for SRTM data will result in elevation products that will be a significant addition to the current availability of seamless datasets, specifically for many areas outside the U.S. One application that demonstrates some advantages that may be realized with SRTM data is delineation of land surface drainage features (watersheds and stream channels). Seamless distribution of elevation data in which a user interactively specifies the area of interest and order parameters via a map server is already being successfully demonstrated with existing USGS datasets. Such an approach for distributing SRTM data is ideal for a dataset that undoubtedly will be of very high interest to the spatial data user community.

Conference Paper↗

USGS2021

Modeling at-sea density of marine birds to support renewable energy planning on the Pacific outer continental shelf of the contiguous United States

This report describes the at-sea spatial distributions of marine birds in Pacific OCS waters off the contiguous U.S. (Figure 1.1) to inform marine spatial planning in the region. The goal was to estimate long-term average spatial distributions for marine bird species using all available science-quality transect survey data and numerous bathymetric, oceanographic, and atmospheric predictor variables. We developed seasonal habitat-based spatial models of the at-sea distribution for 33 individual species and 13 taxonomic groups of marine birds throughout the study region. A statistical modeling framework was used to estimate numerical relationships between bird sighting data (i.e., standardized counts) and a range of temporal (e.g., Pacific Decadal Oscillation [PDO] index), spatially static (e.g., depth), and spatially dynamic (e.g., sea surface chlorophyll-a concentration) environmental variables. The estimated relationships were then used to predict spatially explicit long-term average density (individuals per km 2 ) throughout the study area for each species/group in each of four seasons. Bird sighting data came from multiple scientific survey programs and consisted of at-sea counts of birds collected between 1980 and 2017 using boat-based and fixed-wing aerial transect survey methods. Spatial environmental variables were derived from remote sensing satellite data and an ocean dynamics model.

California, Oregon, Washington↗

USGS2003

Preliminary publications book 2 from project on mineral resources, metallogenesis, and tectonics of northeast Asia

This is the Web version of a CD-ROM publication. This report consists of summary major compilations and syntheses accomplished in the six-year project through April 2003 for the study on the Mineral Resources, Metallogenesis, and Tectonics of Northeast Asia (Eastern and Southern Siberia, Mongolia, Northeastern China, South Korea, and Japan). The major scientific goals and benefits of the project are to: (1) provide a comprehensive international data base on the mineral resources of the region that is the first, extensive knowledge available in English; (2) provide major new interpretations of the origin and crustal evolution of mineralizing systems and their host rocks, thereby enabling enhanced, broad-scale tectonic reconstructions and interpretations; and (3) promote trade and scientific and technical exchanges between the North America and Northeast Asia. Data from the project are providing sound scientific data and interpretations for commercial firms, governmental agencies, universities, and individuals that are developing new ventures and studies in the project area, and for land-use planning studies that deal with both mineral potential issues. Northeast Asia has vast potential for known and undiscovered mineral deposits; however, little information existed in English in the West until publication of products from this project. Consequently, data and interpretations from the project are providing basic knowledge for major scientific, commercial, national, and international endeavors by other interested individuals and groups.

Siberia↗

USGS2025

Scaling from microsite to landscape to resolve litter decomposition dynamics in globally extensive drylands

1. Decomposition controls the release of carbon and nutrients from decaying plant litter into soils or the atmosphere. In most biomes decomposition rates can be accurately predicted with simple mathematical models, but these models have long under-predicted decomposition in globally- extensive drylands. 2. We posit that the exposed surface conditions characteristic of drylands makes litter decomposition uniquely subject to microsite-specific environmental controls and spatially-variable microbial communities. As such, decomposition in dryland ecosystems – which are characterized by extremes in temporal heterogeneity of climate conditions and spatial heterogeneity of vegetation cover with corresponding microclimate variability – is a prime example of a macrosystems process that can be addressed by merging field data with new predictive models operating across a hierarchical continuum of spatial scales and process resolutions. 3. A macrosystems approach offers promise to reconcile model-measurement discrepancies by integrating observations and experiments across multiple scales, from microsites (e.g., shrub sub-canopy or intercanopy) to regions (e.g., across a 100s of km2 study site with complex topography, precipitation, and temperature) and ultimately to a continental perspective (e.g., North American drylands). 4. Recent developments in technology and data availability position the scientific community to integrate lab, field, modeling, and remote sensing approaches across a hierarchical range of scales to capture the spatiotemporal distribution of litter and environmental conditions needed to predict decay dynamics at the micro-to-macroscale. This multi-scale approach promises a path forward to resolving a longstanding disconnect between measured and modeled data in dryland litter decomposition. 5. Dryland litter decomposition presents an excellent case study for resolving spatially and temporally complex biogeochemical dynamics through a hierarchical, multidisciplinary macrosystems approach. 6. We focus on dryland litter decomposition, but the hierarchical, multidisciplinary macrosystems approach we outline shows great potential for resolving other spatially and temporally complex biogeochemical processes across a wide range of ecosystems.

Functional Ecology↗

USGS1997

The International Geosphere Biosphere Programme Data and Information System global land cover data set (DISCover)

The International Geosphere Biosphere Programme Data and Information System (IGBP-DIS), through the mapping expertise of the U.S. Geological Survey and the European Commission's Joint Research Centre, recently guided the completion of a 1-km resolution global land cover data set from advanced very high resolution radiometer (AVHRR) data. The 1-km resolution land cover product, “DISCover,” was based on monthly normalized difference vegetation index composites from 1992 and 1993. The development of DISCover was coordinated by the IGBP-DIS Land Cover Working Group as part of the IGBP-DIS Focus 1 activity. DISCover is a 17-class land cover data set based on the scientific requirements of IGBP elements. The mapping used unsupervised classification and postclassification refinement using ancillary data. The development of this data set was motivated by the need for global land cover data with higher spatial resolution, unproved temporal specificity, and known classification accuracy. The completed DISCover data set will soon be validated to determine the accuracy of the global classification.

Acta Astronautica↗

USGS2021

System characterization report on the German Aerospace Center (DLR) Earth Sensing Imaging Spectrometer (DESIS)

Executive Summary This report addresses system characterization of the German Aerospace Center (DLR) Earth Sensing Imaging Spectrometer (DESIS) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present the methodology and procedures for characterization and the technical and operational information about the specific sensing system being evaluated. These reports also provide a description of data measurements, data retention practices, and data analysis results and provide system characterization conclusions. In partnership with Teledyne Brown Engineering, DLR built the DESIS hyperspectral instrument, which Teledyne Brown Engineering then integrated onto its International Space Station-based imaging platform, the Multi-User System for Earth Sensing. DLR developed the processing software and, together with Innovative Imaging and Research, completes the validation and calibration of the data products. DESIS was launched in 2018, and the data are used for scientific research in atmospheric physics and Earth sciences. The DESIS sensor contributes to the scientific and commercial utilization of the International Space Station and helps to further hyperspectral remote sensing technologies for future satellites. More information on DLR satellites and sensors is included within the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and at https://www.dlr.de/DE/Home/home_node.html . The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that DESIS has an interior geometric performance of less than a 3.30-meter (less than 0.11 pixel) root mean square error in band-to-band registration, an exterior geometric performance in the range of a 2.40- (0.08 pixel) to 17.40-meter (0.58 pixel) offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of −0.013 to 1.011 (offset and slope), and a spatial performance for band 130 of 1.5 pixels at full width at half maximum, with a modulation transfer function at a Nyquist frequency of 0.167.

Open-File Report↗

USGS2017

Functional traits and ecological affinities of riparian plants along the Colorado River in Grand Canyon

Trait-based approaches to vegetation analyses are becoming more prevalent in studies of riparian vegetation dynamics, including responses to flow regulation, groundwater pumping, and climate change. These analyses require species trait data compiled from the literature and floras or original field measurements. Gathering such data makes trait-based research time intensive at best and impracticable in some cases. To support trait-based analysis of vegetation along the Colorado River through Grand Canyon, a data set of 20 biological traits and ecological affinities for 179 species occurring in that study area was compiled. This diverse flora shares species with many riparian areas in the western USA and includes species that occur across a wide moisture gradient. Data were compiled from published scientific papers, unpublished reports, plant fact sheets, existing trait databases, regional floras, and plant guides. Data for ordinal environmental tolerances were more readily available than were quantitative traits. More publicly available data are needed for traits of both common and rare southwestern U.S. plant species to facilitate comprehensive, trait-based research. The trait data set is free to use and can be downloaded from ScienceBase: https://www.sciencebase.gov/catalog/item/58af41dee4b01ccd54f9f2ff and https://dx.doi.org/10.5066/F7QV3JN1

Arizona↗