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At least 829 records · Page 46Linked to original sources

Alaska Science Center: Providing Timely, Relevant, and Impartial Study of the Landscape, Natural Resources, and Natural Hazards for Alaska and Our Nation

The U.S. Geological Survey (USGS), the Nation's largest water, earth, and biological science and civilian mapping agency, has studied the natural features of Alaska since its earliest geologic expeditions in the 1800s. The USGS Alaska Science Center (ASC), with headquarters in Anchorage, Alaska, studies the complex natural science phenomena of Alaska to provide scientific products and results to a wide variety of partners. The complexity of Alaska's unique landscapes and ecosystems requires USGS expertise from many science disciplines to conduct thorough, integrated research.

Fact Sheet↗

Space acquired photography

Interested in a photograph of the first space walk by an American astronaut, or the first photograph from space of a solar eclipse? Or maybe your interest is in a specific geologic, oceanic, or meteorological phenomenon? The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center is making photographs of the Earth taken from space available for search, download, and ordering. These photographs were taken by Gemini mission astronauts with handheld cameras or by the Large Format Camera that flew on space shuttle Challenger in October 1984. Space photographs are distributed by EROS only as high-resolution scanned or medium-resolution digital products.

Fact Sheet↗

Enhanced canopy fuel mapping by integrating lidar data

Background The Wildfire Sciences Team at the U.S. Geological Survey’s Earth Resources Observation and Science Center produces vegetation type, vegetation structure, and fuel products for the United States, primarily through the Landscape Fire and Resource Management Planning Tools (LANDFIRE) program. LANDFIRE products are used across disciplines for a variety of applications. The LANDFIRE data retain their currency and relevancy through periodic updating or remapping. These updating and remapping efforts provide opportunities to improve the LANDFIRE product suite by incorporating data from other sources. Light detection and ranging (lidar) is uniquely suitable for gathering information on vegetation structure and spatial arrangement because it can collect data in three dimensions. The Wildfire Sciences Team has several completed and ongoing studies focused on integrating lidar into vegetation and fuels mapping.

Fact Sheet↗

GeoAI for spatial image processing

The development of digital image processing, as a subset of digital signal processing, depended upon the maturity of photography and image science, introduction of computers, discovery and advancement of digital recording devices, and the capture of digital images. In addition, government and industry applications in the Earth and medical sciences were paramount to the growth of the technology. From the early days when photography was first introduced to science to today, artificial intelligence and deep learning technologies have been intensively used to analyze imagery. Spatial image processing has experienced breakthroughs and evolutions. This chapter presents an overview of the history of image processing, GeoAI-based image processing applications, and the role of GeoAI in advancing image processing methods and research. We also discussed the remaining challenges to using GeoAI for image processing regarding training data annotation, the issues of scale, resolution, and change in space over time.

Book chapter↗

Archiving and access systems for remote sensing: Chapter 6

Focuses on major developments inaugurated by the Committee on Earth Observation Satellites, the Group on Earth Observations System of Systems, and the International Council for Science World Data System at the global level; initiatives at national levels to create data centers (e.g. the National Aeronautics and Space Administration (NASA) Distributed Active Archive Centers and other international space agency counterparts), and non-government systems (e.g. Center for International Earth Science Information Network). Other major elements focus on emerging tool sets, requirements for metadata, data storage and refresh methods, the rise of cloud computing, and questions about what and how much data should be saved. The sub-sections of the chapter address topics relevant to the science, engineering and standards used for state-of-the-art operational and experimental systems.

Book chapter↗

System characterization report on the Environmental Mapping and Analysis Program (EnMAP)

This report addresses system characterization of the Environmental Mapping and Analysis Program hyperspectral sensor by the DLR (German Aerospace Center, ground segment project management), GFZ (Deutsches Geoforschungszentrum, science lead) 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 and detail the methodology and procedures for characterization; present technical and operational information about the EnMAP hyperspectral sensor; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), and radiometric performances of the EnMAP hyperspectral sensor. Results of these analyses indicate that the Environmental Mapping and Analysis Program has a band-to-band geometric performance in the range of −0.135 to 0.15 pixel, geometric performance relative to the Operational Land Imager in the range of −27.716 meters (−0.92 pixel) to 32.892 meters (1.09 pixels) offset in comparison to Landsat 8 Operational Land Imager, offset of a radiometric comparison in the range of −0.012 to 0.020, slope of a radiometric comparison in the range of 0.947 to 1.031.

Open-File Report↗

System characterization of Earth observation sensors

This U.S. Geological Survey Open-File Report provides information from assessments of Earth observation sensors completed by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports are provided as independent measures of basic system performance by the Earth Resources Observation and Science Cal/Val Center of Excellence team by completing the geometric, radiometric, and spatial characterization. The results of these assessments are a snapshot in time.

Open-File Report↗

Landsat Science Team meeting: Winter 2015

The summer meeting of the joint U.S. Geological Survey (USGS)–NASA Landsat Science Team (LST) was held at the USGS’s Earth Resources Observation and Science (EROS) Center July 7-9, 2015, in Sioux Falls, SD. The LST co-chairs, Tom Loveland [EROS—Senior Scientist] and Jim Irons [NASA’s Goddard Space Flight Center (GSFC)—Landsat 8 Project Scientist], opened the three-day meeting on an upbeat note following the recent successful launch of the European Space Agency’s Sentinel-2 mission on June 23, 2015 (see image on page 14), and the news that work on Landsat 9 has begun, with a projected launch date of 2023. With over 60 participants in attendance, this was the largest LST meeting ever held. Meeting topics on the first day included Sustainable Land Imaging and Landsat 9 development, Landsat 7 and 8 operations and data archiving, the Landsat 8 Thermal Infrared Sensor (TIRS) stray-light issue, and the successful Sentinel-2 launch. In addition, on days two and three the LST members presented updates on their Landsat science and applications research. All presentations are available at landsat.usgs.gov/science_LST_Team_ Meetings.php.

The Earth Observer↗

An overview of USGS-NASA Landsat Science activities during 2018

Two meetings of the U.S. Geological Survey (USGS)-NASA Landsat Science Team (LST) took place in 2018. The USGS Earth Resources Observation and Science (EROS) Center hosted the winter meeting, which took place February 21-22 in Sioux Falls, SD. The University of Colorado-Boulder hosted the summer meeting, which was held August 8-10 in Boulder, CO.

The Earth Observer↗

Using Landsat imagery to detect, monitor, and project net landscape change

Detailed landscape information is a necessary component to bird habitat conservation planning. The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center has been providing information on the Earth’s surface for over 40 years via the continuous series of Landsat satellites. In addition to operating, processing, and disseminating satellite images, EROS is the home to nationwide and global landscape mapping, monitoring, and projection products, including: National Land Cover Database (NLCD) – the definitive land cover dataset for the U.S., with updates occurring at five-year intervals; Global Land Cover Monitoring – producing 30m resolution global land cover; LANDFIRE – Landscape Fire and Resource Management Planning Tools–EROS is a partner in this joint program between U.S. Department of Agriculture and Department of Interior that produces consistent, comprehensive, geospatial data and databases that describe vegetation, wildland fuel, and fire regimes across the U.S.; Land Cover Trends – a landscape monitoring and assessment effort to understand the rates, trends, causes, and consequences of contemporary U.S. land use and land cover change; and Land Use and Land Cover (LULC) Modeling – a project extending contemporary databases of landscape change forward and backward in time through moderate-resolution land cover projections.

All Bird Bulletin↗

Capacity assessment for Earth Monitoring, Analysis, and Prediction (EarthMAP) and future integrated monitoring and predictive science at the U.S. Geological Survey

Executive Summary Managers of our Nation’s resources face unprecedented challenges driven by the convergence of increasing, competing societal demands and a changing climate that affects the stability, vulnerability, and predictability of those resources. To help meet these challenges, the scientific community must take advantage of all available technologies, data, and integrative Earth systems modeling capacity to better inform resource and risk management decisions. This is the overarching goal of the U.S. Geological Survey (USGS) Earth Monitoring, Analysis, and Prediction (EarthMAP) vision: “By 2030, the USGS will deliver well integrated observations and predictions of the future state of natural systems—water, ecosystems, energy, minerals, hazards—at regional and national scales, working primarily with federal, state, and academic partners to develop and operate the capability” (U.S. Geological Survey, 2021). Providing more integrated Earth systems science and actionable information to decision makers, stakeholders, and the public requires a better understanding of the depth and distribution of existing capacity (capabilities, tools, and techniques) across the Bureau. Identifying existing capacity is also a critical first step toward gap analysis and targeted investments to increase capacity over time. The USGS formed a Capacity Assessment Team (CAT) and charged it with (1) conducting a Request for Information (RFI) to identify existing USGS expertise and activities supportive of integrated and predictive science to inform decision making, (2) developing a strategy and proof-of-concept for a continuously updated capacity assessment capability, and (3) identifying lessons learned to inform development of best practices for future capacity assessment efforts. The RFI took the form of a survey, with content guided by the science and technology needs identified in a USGS report titled “Grand Challenges for Integrated U.S. Geological Survey Science—A Workshop Report” (Jenni and others, 2017). The 44-question survey provided respondents the ability to rate their level of experience with a suite of priority disciplines, analysis and modeling approaches, technologies, and stakeholder engagement strategies and to enter optional narrative text for supporting context. An introductory portion focused on general science capacity assessment, followed by three sections targeting capabilities related to the foundational components of EarthMAP: (1) data and information integration, (2) integrated predictive science, and (3) actionable information. The survey results provided a high-level snapshot of USGS capacity in the targeted areas. Respondents (1,035 individuals) represented approximately 13 percent of the USGS across all mission areas and regions. Seventy-four percent of the respondents held a science-focused position title and the remainder had position titles in information technology, computer science, management, administrative, or other (contractors, volunteers, emeritus, and unknown). To provide greater insight into respondent capabilities and activities, information from the U.S. Department of the Interior and USGS enterprise information systems were used to further characterize topical expertise and organizational associations of survey respondents. To address the ongoing need to assess the Bureau’s capacity to address integrated predictive science priorities, the CAT developed a software-based proof-of-concept called the Integrated Science Assessment Information Database (iSAID) for assembling various information sources together toward making the full extent of USGS capabilities and scientific assets available for routine capacity assessment. This proof-of-concept is intended to serve as a catalyst for further development. The process of implementing the EarthMAP capacity assessment survey, analyzing survey responses, and developing the proof-of-concept resulted in lessons learned, findings, and recommendations. Example scenarios throughout the report demonstrate how capacity assessment data can inform science planning. Three overarching findings and recommendations are: (1) Finding: Capacity is limited in some critical disciplines, skills, and technology applications, but “sufficient” depends on the question and the need relative to availability at a given point in time. Recommendation: Develop an on-demand capacity assessment framework that enables rapid identification and evaluation of existing and available expertise to support decision needs as they arise. (2) Finding: Institutional barriers and lack of awareness constrain the ability of USGS staff to adopt new technologies, collaborate across administrative boundaries, and deliver actionable information to stakeholders in a timely manner. However, these barriers are not universally experienced. Recommendation: Pursue more targeted inquiries to clarify which institutional barriers are obstructing the adoption of new technologies and approaches or the sharing of expertise and equipment across organizational and regional boundaries. These inquiries should inform USGS leadership, mission areas, and regions whether policies can be revised or whether a lack of understanding is creating perceived obstacles. Highlight cases when staff have successfully adopted new technologies and approaches to advance EarthMAP priorities and provide actionable information in a timely manner to spread awareness of how perceived obstacles can be navigated and overcome when appropriate. (3) Finding: Examples of people and projects integrating across disciplines and scales and applying advanced approaches to meet complex stakeholder needs exist. Such examples provide transfer value across the spectrum from approach to decision making. Many projects, already underway, appear to meet elements of the EarthMAP vision, and the USGS has people who can provide leadership in multiple types of specific integrated science efforts. Recommendation: Use these findings as a starting point for near-term strategic planning for integrated science. Highlight, incentivize, and build on existing interdisciplinary predictive science and information delivery activities across the USGS to advance toward further realization of an EarthMAP capacity. The CAT efforts to develop and assess existing USGS capacity to advance the EarthMAP vision revealed a fundamental challenge for not only this effort but any effort to assess existing capacity: A considerable amount of thought, time, and effort is required to survey and assess capabilities and tools available to support a given need, yet best results are still likely to provide an incomplete assessment. To better meet the frequent need to assess capabilities, tools, products, and projects that address an expressed strategic priority, the CAT proposes the concept of an on-demand capacity assessment framework supported by a software package that dynamically pulls and integrates information from existing USGS information systems and public domain registries. Although existing USGS enterprise information systems currently lack the structure, cross-system consistency, interoperability, and stability to support a continuously updated capacity assessment capability, we identify reasonable near-term steps to improve the utility of information gathered on expertise and project capacity and to improve the consistency and completeness of information and the ability of USGS systems to share that information. The ability to search and characterize this information will make future assessments of capacity faster, more complete, more efficient, and more targeted. This approach would grow the Bureau’s capacity knowledge over time, iteratively improving the ability to access, leverage, and synthesize existing capabilities and assets as well as identify and fill critical gaps. The greatest promise for developing integrated science could lie in linking across existing projects and expertise to create a multi-project capacity for addressing large, complex environmental issues.

Open-File Report↗

Statistical analysis of water-quality data containing multiple detection limits II: S-language software for nonparametric distribution modeling and hypothesis testing

Analysis of low concentrations of trace contaminants in environmental media often results in left-censored data that are below some limit of analytical precision. Interpretation of values becomes complicated when there are multiple detection limits in the data-perhaps as a result of changing analytical precision over time. Parametric and semi-parametric methods, such as maximum likelihood estimation and robust regression on order statistics, can be employed to model distributions of multiply censored data and provide estimates of summary statistics. However, these methods are based on assumptions about the underlying distribution of data. Nonparametric methods provide an alternative that does not require such assumptions. A standard nonparametric method for estimating summary statistics of multiply-censored data is the Kaplan-Meier (K-M) method. This method has seen widespread usage in the medical sciences within a general framework termed "survival analysis" where it is employed with right-censored time-to-failure data. However, K-M methods are equally valid for the left-censored data common in the geosciences. Our S-language software provides an analytical framework based on K-M methods that is tailored to the needs of the earth and environmental sciences community. This includes routines for the generation of empirical cumulative distribution functions, prediction or exceedance probabilities, and related confidence limits computation. Additionally, our software contains K-M-based routines for nonparametric hypothesis testing among an unlimited number of grouping variables. A primary characteristic of K-M methods is that they do not perform extrapolation and interpolation. Thus, these routines cannot be used to model statistics beyond the observed data range or when linear interpolation is desired. For such applications, the aforementioned parametric and semi-parametric methods must be used.

Computers & Geosciences↗

Introduction to the special issue on ‘Frontiers in gas geochemistry’

The study of the geochemistry of gases pervades the Earth and Environmental Sciences. This is due in no small measure to the well-established thermodynamic properties of gases which allow their application to a variety of processes occurring over a wide spectrum of natural conditions. In this respect, both major and associated minor gases have been proven useful: indeed, the trace gases have been particularly important given their role as sensitive geochemical tracers. Examples where gas geochemistry places key constraints on geochemical processes include the degassing history of the solid Earth to form the atmosphere and oceans, the origin and migration characteristics of hydrocarbon deposits, the scale of climate variability, the P–T characteristics of geothermal reservoirs, and the dynamics of the earthquake cycle and volcanic activity, to name but a few. This volume continues this rich tradition with an eclectic selection of papers aimed at exploring and exploiting gas geochemistry over a myriad set of research themes.

Chemical Geology↗

U.S. Geological Survey activities related to American Indians and Alaska Natives: Fiscal years 2009 and 2010

The U.S. Geological Survey is the earth and natural science bureau within the U.S. Department of the Interior. The U.S. Geological Survey provides impartial information on the health of our ecosystems and environment, the natural hazards that threaten us, the natural resources we rely on, the negative effects of climate and land-use change, and the core science systems that help us provide timely, relevant, and usable information. The U.S. Geological Survey is not responsible for regulations or land management. In the late 1800s, John Wesley Powell the second director of the U.S. Geological Survey, followed his interest in the Tribes of the Great Basin and Colorado Plateau and studied their cultures, languages, and surroundings. From that early time, the U.S. Geological Survey has recognized the importance of Native knowledge as a complement to the U.S. Geological Survey mission to better understand the Earth and its systems. Collaboration allows the U.S. Geological Survey and Native American governments, organizations, and peoples to increase their mutual understanding of the increasing challenges facing our natural world. Although this report uses the term “resources,” the U.S. Geological Survey, through its interdisciplinary research, acknowledges the interconnectedness of the Earth and all the life forms that live upon it.

Circular↗

Wyoming Landscape Conservation Initiative—A case study in partnership development

The Wyoming Landscape Conservation Initiative (WLCI) is a successful example of collaboration between science and natural resource management at the landscape scale. In southwestern Wyoming, expanding energy and mineral development, urban growth, and other changes in land use over recent decades, combined with landscape-scale drivers such as climate change and invasive species, have presented compelling challenges to resource managers and a diverse group of Federal, State, industry, and non-governmental organizations, as well as citizen stakeholders. To address these challenges, the WLCI was established as a collaborative forum and interagency partnership to develop and implement science-based conservation actions. About a decade after being established, this report documents the establishment and history of the WLCI, focusing on the path to success of the initiative and providing insights and details that may be useful in developing similar partnerships in other locations. Not merely retrospective, the elements of the WLCI that are presented herein are still in play, still evolving, and still contributing to the resolution of compelling conservation challenges in the Western United States. The U.S. Geological Survey has developed many successful longstanding partnerships, of which the WLCI is one example. “As the Nation’s largest water, earth, and biological science and civilian mapping agency, the U.S. Geological Survey collects, monitors, analyzes, and provides scientific understanding about natural resource conditions, issues, and problems. The diversity of our scientific expertise enables us to carry out large-scale, multi-disciplinary investigations and provide impartial scientific information to resource managers, planners, and other customers” (U.S. Geological Survey, 2016).

Wyoming↗

On-orbit performance of the Landsat 8 Operational Land Imager

The Landsat 8 satellite was launched on February 11, 2013, to systematically collect multispectral images for detection and quantitative analysis of changes on the Earth’s surface. The collected data are stored at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and continue the longest archive of medium resolution Earth images. There are two imaging instruments onboard the satellite: the Operational Land Imager (OLI) and the Thermal InfraRed Sensor (TIRS). This paper summarizes radiometric performance of the OLI including the bias stability, the system noise, saturation and other artifacts observed in its data during the first 1.5 years on orbit. Detector noise levels remain low and Signal-To-Noise Ratio high, largely exceeding the requirements. Impulse noise and saturation are present in imagery, but have negligible effect on Landsat 8 products. Oversaturation happens occasionally, but the affected detectors quickly restore their nominal responsivity. Overall, the OLI performs very well on orbit and provides high quality products to the user community. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Conference Paper↗

Data management and digital delivery of analog data

The U.S. Geological Survey's (USGS) data archive at the Earth Resources Observation and Science (EROS) Center is a comprehensive and impartial record of the Earth's changing land surface. USGS/EROS has been archiving and preserving land remote sensing data for over 35 years. This remote sensing archive continues to grow as aircraft and satellites acquire more imagery. As a world leader in preserving data, USGS/EROS has a reputation as a technological innovator in solving challenges and ensuring that access to these collections is available. Other agencies also call on the USGS to consider their collections for long-term archive support. To improve access to the USGS film archive, each frame on every roll of film is being digitized by automated high performance digital camera systems. The system robotically captures a digital image from each film frame for the creation of browse and medium resolution image files. Single frame metadata records are also created to improve access that otherwise involves interpreting flight indexes. USGS/EROS is responsible for over 8.6 million frames of aerial photographs and 27.7 million satellite images.

Conference Paper↗

ECCOE Landsat quarterly Calibration and Validation report—Quarter 4, 2024

Executive Summary The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The Earth Resources Observation and Science Cal/Val Center of Excellence Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level. This report provides observed geometric and radiometric analysis results for Landsats 8 and 9 for quarter 4 (October–December) of 2024. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov .

Open-File Report↗