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At least 343 records · Page 19Linked to original sources
USGS2022

Landsat Collection 2 Level-3 Burned Area science product

Accurate and complete data on fire locations and burned areas are needed to quantify trends and patterns of fire occurrence, characterize drivers of fire, project future fire pattern behavior, and help with assessments of fire effects on natural and social systems. The Landsat Collection 2 Level-3 Burned Area science product is designed to identify burned areas across all ecosystems (for example, forests, shrublands, and grasslands) for Landsat 4–9 data.

Fact Sheet↗
USGS2023

The incredible HALK: borrowing data for age assignment

Understanding age and growth are important for fisheries science and management; however, age data are not routinely collected for many populations. We propose and test a method of borrowing age–length data across increasingly broader spatiotemporal levels to create a hierarchical age–length key (HALK). We assessed this method by comparing growth and mortality metrics to those estimated from lake–year age–length keys ages using seven common freshwater fish species across the upper Midwestern United States. Levels used for data borrowing began most specifically by borrowing within lake across time and increased in breadth to include data within the Hydrologic Unit Code (HUC) 10 watershed, HUC8 watershed, Level III Ecoregion, and finally a species-wide data ALK using all available data with our study for a species. Median deviation in mean length of age-3 fish was within 1 cm for the most specific HALK levels, and median deviation in total annual mortality was close to 0 for most species when borrowing occurred within HUC10 and HUC8 watersheds. Percent error in growth curves increased with data borrowing, but plateaued—or even decreased—for some species when data borrowing expanded across spatial levels. We present the HALK as a method for gaining age information about a fishery when age data are unavailable.

Illinois, Indiana, Iowa, Michigan, Minnesota, Sout↗
USGS2026

Assessing the state of hydrologic science in the Upper Klamath Basin—A comprehensive review of data, tools, and models

Water demand in the Upper Klamath Basin (UKB) from various stakeholders and ecological needs often outstrips available supply, leading to persistent management challenges. This study reviews the state of hydrologic science within the UKB as of 2025—specifically, the tools, data, and models available for assessing five key components of the water system: (1) surface water; (2) precipitation; (3) evapotranspiration; (4) groundwater; and (5) water use. The UKB water supply is critical for Native American communities, regional agriculture, and federally listed fishes and faces challenges from competing needs, climate variability, and operational/regulatory requirements. We assess existing datasets, regional and national models, and historical studies to understand the available resources and identify gaps that may hinder integrated water assessments and management. Our findings indicate areas where improvements in data collection and model precision could improve the accuracy of water-availability forecasts and support water-management practices. This review can inform near-term forecasting, assist in optimizing water-resource data collection and management strategies, and support regional water-availability assessments of the basin.

Oregon↗
USGS2024

Using citizen scientists to collect oxygen and hydrogen isotope data in southern Nevada

What is Citizen Science? Citizen science programs provide a means for Federal and non-Federal government agencies to make science more engaging, transparent, and accessible by partnering with the public for the purpose of problem solving, data collection, and monitoring. Public volunteers become directly involved in local research, thereby engaging in scientific projects. The public has already been included in existing citizen science programs that cover a broad range of disciplines, such as ecology, hydrology, and tectonics. Citizen science advances research while simultaneously fostering a sense of involvement and interest from the public. Beginning in 2017, the U.S. Geological Survey (USGS), U.S. Forest Service, Bureau of Land Management, U.S. Fish and Wildlife Service, and National Park Service collaborated with private, non-profit partners to inventory, survey, and rehabilitate springs in Clark County, Nevada. The USGS maintains the National Water Information System (NWIS), a publicly available online database of water-resources data for the Nation, and the agency is interested in using citizen science to add geochemical data from springs in southern Nevada. From 2021 to 2023, the USGS directly worked with citizen science partners, including the Springs Stewardship Institute and the Friends of Nevada Wilderness, to collect stable isotope and tritium samples from southern Nevada springs. The citizen science volunteers were provided the training and supplies for proper sample collection by USGS staff. As the citizen science partners traveled and hiked to the remote spring sites to complete spring surveys and perform restoration activities, they collected stable isotope and tritium samples for the USGS. Samples were shipped to national USGS laboratories for analysis, and the results were uploaded to the NWIS database (U.S. Geological Survey, 2024).

Nevada↗
USGS2010

Impact of sampling techniques on measured stormwater quality data for small streams

Science-based sampling methodologies are needed to enhance water quality characterization for setting appropriate water quality standards, developing Total Maximum Daily Loads, and managing nonpoint source pollution. Storm event sampling, which is vital for adequate assessment of water quality in small (wadeable) streams, is typically conducted by manual grab or integrated sampling or with an automated sampler. Although it is typically assumed that samples from a single point adequately represent mean cross-sectional concentrations, especially for dissolved constituents, this assumption of well-mixed conditions has received limited evaluation. Similarly, the impact of temporal (within-storm) concentration variability is rarely considered. Therefore, this study evaluated differences in stormwater quality measured in small streams with several common sampling techniques, which in essence evaluated within-channel and within-storm concentration variability. Constituent concentrations from manual grab samples and from integrated samples were compared for 31 events, then concentrations were also compared for seven events with automated sample collection. Comparison of sampling techniques indicated varying degrees of concentration variability within channel cross sections for both dissolved and particulate constituents, which is contrary to common assumptions of substantial variability in particulate concentrations and of minimal variability in dissolved concentrations. Results also indicated the potential for substantial within-storm (temporal) concentration variability for both dissolved and particulate constituents. Thus, failing to account for potential cross-sectional and temporal concentration variability in stormwater monitoring projects can introduce additional uncertainty in measured water quality data. Copyright ?? 2010 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. All rights reserved.

Journal of Environmental Quality↗
USGS2018

A new Enceladus global control network, image mosaic, and updated pointing kernels from Cassini's thirteen-year mission

NASA's Cassini spacecraft spent 13 years exploring the Saturn system, including 23 targeted flybys of the small, geologically active moon Enceladus. These flybys provided a wealth of image data from Cassini's Imaging Science Subsystem. To improve the usability of the Enceladus data set, we created a new, global photogrammetric control network for Enceladus that enabled compilation of a versatile cartographic package to support geologic mapping and other investigations. The network used 586 images in four image filters with a pixel scale generally between 50 and 500 m per pixel and a phase angle less than 120° and consisted of 10,362 tie points and 173,704 individual image measures, averaging nearly 17 measures per tie point. Least squares bundle adjustment resulted in a root‐mean‐square residual of 0.45 pixel, corresponding to root‐mean‐square ground point uncertainties of 66, 51, and 46 m in latitude, longitude, and radius, respectively. Using our geodetic control network, we created new global image mosaics, coregistered flyby mosaics to support geologic mapping, and updated pointing kernels for every image used in the solution. These products, including the updated pointing kernels, are available to the community through NASA's Planetary Data System Imaging Annex. The bundle adjustment solution also yielded independently determined shape information, resulting in radii within the stated uncertainty of International Astronomical Union values. The challenges of the data set, and the technical methodology described here are applicable to bodies imaged during multiple flybys with variable viewing and illumination geometry, including other midsized satellites of Saturn, and the Europa Clipper mission.

Earth and Space Science↗
USGS2003

The U.S. Geological Survey land remote sensing program

The U.S. Geological Survey has been a provider of remotely sensed information for decades. As the availability and use of satellite data has grown, USGS has placed increasing emphasis on expanding the knowledge about the science of remote sensing and on making remotely sensed data more accessible. USGS encourages widespread availability and distribution of these data and through its programs, encourages and enables a variety of research activities and the development of useful applications of the data. The science of remote sensing has great potential for assisting in the monitoring and assessment of the impacts of natural disasters, management and analysis of environmental, biological, energy, and mineral investigations, and supporting informed public policy decisions. By establishing the Land Remote Sensing Program (LRS) as a major unit of the USGS Geography Program, USGS has taken the next step to further increase support for the accessibility, understanding, and use of remotely sensed data. This article describes the LRS Program, its mission and objectives, and how the program has been structured to accomplish its goals.

Cartography and Geographic Information Science↗
USGS2021

Nitrogen in the Chesapeake Bay watershed—A century of change, 1950–2050

Foreword Sustaining the quality of the Nation’s water resources and the health of our diverse ecosystems depends on the availability of sound water-resources data and information to develop effective, science-based policies. Effective management of water resources also brings more certainty and efficiency to important economic sectors. Taken together, these actions lead to immediate and long-term economic, social, and environmental benefits that will make a difference to the lives of the almost 400 million people projected to live in the United States by 2050. The Chesapeake Bay is the largest and most productive estuary in the United States and is a vital environmental and economic resource. Approximately half of the water volume of the Chesapeake Bay originates from streams and rivers that drain the 64,243 mi 2 Chesapeake Bay watershed. The Bay and its tributaries have been degraded by excessive nutrients, such as nitrogen, from contributing watersheds. Inputs of nitrogen to the Bay lead to increased algal growth, decreased dissolved oxygen, and declining fisheries. In 2000, the Chesapeake Bay was listed as impaired under the Clean Water Act and Total Maximum Daily Loads (TMDLs) for nutrients and sediment have been established to assist with management actions aimed at nutrient reductions. Effective nutrient management requires an understanding of past, present, and future nutrient sources, fate, and transport in the watershed. The Chesapeake Bay community has been a pioneer in science, management, and regulation to improve water quality. Factors like climate, hydrology, source inputs, and management controls play a vital role in determining the delivery and magnitude of nitrogen inputs to the Bay. Science in the form of monitoring data, predictive tools, and interpretive reports can help inform decisions to better balance the use and control of nitrogen in coastal areas. The findings in this report can contribute to effective management of the Bay and its watershed by providing a synthesis of the understanding of how human activities and environmental change in the watershed in the past, present, and future will influence the export of nitrogen to the Bay. We hope this publication will provide you with insights and information to meet your water resource needs and will foster increased civilian awareness and involvement in the protection and restoration of our Nation’s waters. The information in this report is intended primarily for those interested or involved in resource management and protection, conservation, regulation, and policymaking at the regional and national levels.

Chesapeake Bay watershed↗
USGS2015

Colored shaded-relief bathymetry, acoustic backscatter, and selected perspective views of the Inner Continental Borderland, southern California

In late 2013, Scripps Institution of Oceanography collected multibeam bathymetry and acoustic-backscatter data of the Inner Continental Borderland Region, Southern California. The U.S. Geological Survey Pacific Coastal and Marine Science Center processed these data, and this report provides the data in a number of different formats in addition to a set of map sheets. The data catalog provides the new bathymetry and acoustic-backscatter data, collected mainly in the Gulf of Santa Catalina and San Diego Trough, as well as this new bathymetry data merged with other publicly available bathymetry data from the region. Sheet 1 displays a colored shaded-relief bathymetry map of the Inner Continental Borderland generated from the merged bathymetry data. Sheet 2 displays the new acoustic-backscatter data along with other available backscatter data in the region. Sheet 3 displays selected perspective views of the bathymetry data highlighting submarine canyon and channel systems, knolls, and tectonic features.

California↗
USGS1993

Availability of Earth observations data from the U.S. Geological Survey's EROS data center

For decades federal and state agencies have been collecting regional, continental, and global Earth observations data acquired by satellites, aircraft, and other information-gathering systems. These data include photographic and digital remotely sensed images of the Earth's surface, as well as earth science, cartographic, and geographic data. Since 1973, the U.S. Geological Survey's Earth Resources Observation Systems (EROS) Data Center (EDC) in Sioux Falls, South Dakota, has been a data management, production, dissemination, and research center for these data. Currently, the Data Center holds over 10 million satellite images and aerial photographs, in photographic and digital formats. Users are able to place inquiries and orders for these holdings via a nationwide computer network. In addition to cataloging the data stored in its archives, the Data Center provides users with rapid access to information on many data collections held by other facilities.

Pecora 12 Symposium↗
USGS2022

Lake Tahoe clarity and associated conditions, 2022

Lake Tahoe’s clarity remains a key indicator of overall ecosystem status, and scientific understanding about factors affecting lake clarity continues to evolve. The purpose of this briefing memorandum is to summarize the status of clarity metrics and drivers of change discussed in the 2022 TSAC Data Synthesis and Analysis report. Consistent with the Lake Tahoe Total Maximum Daily Load analyses, the concentrations of fine particles remain important to lake clarity. These include fine sediment particles from the watershed as well as small phytoplankton cells produced within the lake. This year, in addition to the analysis of Secchi depth clarity response to fine particle and small phytoplankton concentrations, we reviewed available data on fine sediment particles from streams and urban runoff. Information summarized here is discussed further in the Tahoe Science Advisory Council (TSAC) Data Synthesis and Analysis reports (2022, 2021), the TSAC Lake Tahoe Seasonal and Long-Term Clarity Trend Analysis report (2020), and in annual State of the Lake reports produced by UC Davis Tahoe Environmental Research Center.

California, Nevada↗
USGS2019

South Atlantic Water Science Center Strategic Science Plan: 2019–23

Executive Summary The South Atlantic Water Science Center Strategic Science Planning Team has developed a unified strategic science plan to guide the science vision of the South Atlantic Water Science Center (SAWSC) in response to the merging of the Georgia, North Carolina, and South Carolina Water Science Centers. This plan proposes a path forward to keep SAWSC science activities relevant to the many diverse needs of stakeholders in the South Atlantic region (Georgia, North Carolina, and South Carolina) and considers the hydrologic setting and issues of the region. This plan advises the creation of five working groups to address five priority science topics for the period 2019–23 and beyond. The five priority science topics are (1) Foundational Data, (2) Effects of Land-Use Change, (3) Coastal Plain Science, (4) Water Availability, and (5) Hazards. From the goals laid forth in this plan for each priority science topic, the working groups plan to devise a set of strategic actions and milestones to be achieved by the SAWSC to provide valuable and relevant data, research, and assessments in the South Atlantic region. In this report, the “South Atlantic region” is used to describe the area encompassed by the States of North Carolina, South Carolina, and Georgia.

Open-File Report↗
USGS2022

Landsat Collection 2 Level-3 Dynamic Surface Water Extent science product

The Landsat Collection 2 Level-3 Dynamic Surface Water Extent science product provides raster data that represent surface water inundation per pixel in Landsat 4–9 imagery. The Collection 2 Dynamic Surface Water Extent science product contains six acquisition-based raster products relating to surface water. Surface water extent is modulated by weather and climate, stream network hydrology, and geological processes such as isostatic rebound. Land use, ecosystem and service management, and overall water management also are affected by changes in surface water extent.

Fact Sheet↗
USGS2015

Community for Data Integration 2013 Annual Report

The U.S. Geological Survey (USGS) conducts earth science to help address complex issues affecting society and the environment. In 2006, the USGS held the first Scientific Information Management Workshop to bring together staff from across the organization to discuss the data and information management issues affecting the integration and delivery of earth science research and investigate the use of “communities of practice” as mechanisms to share expertise about these issues. Out of this effort emerged the Council for Data Integration, which was conceived as an official organizational function that would help guide data integration activities and formalize communities of practice into working groups. However by 2009, it became apparent that many members of the council had an interest in developing data integration solutions and sharing expertise in a less formal grassroots perspective, thus transforming the “Council” into a “Community” for Data Integration (CDI). Today, the CDI represents a dynamic community of practice focused on advancing science data and information management and integration capabilities across the USGS and the CDI community. The CDI fosters an environment for collaboration and sharing by bringing together expertise from external partners and representatives across USGS who are involved in research, data management, and information technology. Membership is voluntary and open to USGS employees and other individuals and organizations willing to contribute to the community (if interested, contact cdi@usgs.gov). The purpose of the CDI is to advance understanding of Earth systems through enhanced use of data and information including associated tools and techniques provide a forum for people doing work with data integration to come together to share ideas as well as learn new skills and techniques, and grow overall USGS capabilities with data and information by increasing visibility of the work of many people throughout the USGS and the CDI community. To achieve these goals, the CDI operates within four applied areas: monthly forums, annual workshop/webinar series, working groups, and projects. The monthly forums, also known as the Opportunity/Challenge of the Month, provide an open dialogue to share and learn about data integration efforts or to present problems that invite the Community to offer solutions, advice, and support. Since 2010, the CDI has also sponsored annual workshops/webinar series to encourage the exchange of ideas, sharing of activities, presentations of current projects, and networking among members. Stemming from common interests, the working groups are focused on efforts to address data management and technical 2 challenges, including the development of standards and tools, improving interoperability and information infrastructure, and data preservation within USGS and its partners. The growing support for the activities of the working groups led to the CDI’s first formal request for proposals (RFP) process in 2013 to fund projects that produced tangible products. Today the CDI continues to hold an annual RFP that create data management tools and practices, collaboration tools, and training in support of data integration and delivery.

Open-File Report↗
USGS2017

The U.S. Geological Survey Peak-Flow File Data Verification Project, 2008–16

Annual peak streamflow (peak flow) at a streamgage is defined as the maximum instantaneous flow in a water year. A water year begins on October 1 and continues through September 30 of the following year; for example, water year 2015 extends from October 1, 2014, through September 30, 2015. The accuracy, characterization, and completeness of the peak streamflow data are critical in determining flood-frequency estimates that are used daily to design water and transportation infrastructure, delineate flood-plain boundaries, and regulate development and utilization of lands throughout the United States and are essential to understanding the implications of climate and land-use change on flooding and high-flow conditions. As of November 14, 2016, peak-flow data existed for 27,240 unique streamgages in the United States and its territories. The data, collectively referred to as the “peak-flow file,” are available as part of the U.S. Geological Survey (USGS) public web interface, the National Water Information System, at https://nwis.waterdata.usgs.gov/usa/nwis/peak . Although the data have been routinely subjected to periodic review by the USGS Office of Surface Water and screening at the USGS Water Science Center level, these data were not reviewed in a national, systematic manner until 2008 when automated scripts were developed and applied to detect potential errors in peak-flow values and their associated dates, gage heights, and peak-flow qualification codes, as well as qualification codes associated with the gage heights. USGS scientists and hydrographers studied the resulting output, accessed basic records and field notes, and corrected observed errors or, more commonly, confirmed existing data as correct. This report summarizes the changes in peak-flow file data at a national level, illustrates their nature and causation, and identifies the streamgages affected by these changes. Specifically, the peak-flow data were compared for streamgages with peak flow measured as of November 19, 2008 (before the automated scripts were widely applied) and on November 14, 2016 (after several rounds of corrections). There were 659,332 peak-flow values in the 2008 dataset and 731,965 peak-flow values in the 2016 dataset. When compared to the 2016 dataset, 5,179 (0.79 percent) peak-flow values had changed; 36,506 (5.54 percent) of the peak-flow qualification codes had changed; 1,938 (0.29 percent) peak-flow dates had changed; 18,599 (2.82 percent) of the peak-flow gage heights had changed; and 20,683 (3.14 percent) of the gage-height qualification codes had changed—most as a direct result of the peak-flow file data verification effort led by USGS personnel. The various types of changes are summarized and mapped in this report. In addition to this report, a corresponding USGS data release is provided to identify changes in peak flows at individual streamgages. The data release and the procedures to access the data release are described in this report.

Scientific Investigations Report↗
USGS2015

Community for Data Integration 2014 annual report

The U.S. Geological Survey (USGS) researches Earth science to help address complex issues affecting society and the environment. In 2006, the USGS held the first Scientific Information Management Workshop to bring together staff from across the organization to discuss the data and information management issues affecting the integration and delivery of Earth science research and investigate the use of “communities of practice” as mechanisms to share expertise about these issues. Out of this effort emerged the Council for Data Integration, which was conceived as an official organizational function that would help guide data integration activities and formalize communities of practice into working groups; however, by 2009 it became evident that many members of the Council for Data Integration had an interest in developing data integration solutions and sharing expertise in a less formal, grassroots manner, which transformed the Council into a Community for Data Integration (CDI). As of 2014, the CDI represents a dynamic community of practice focused on advancing science data and information management and integration capabilities across the USGS and the CDI community. The CDI fosters an environment for collaboration and sharing by bringing together expertise from external partners and representatives across the USGS who are involved in research, data management, and information technology. Membership is voluntary and open to USGS employees and other individuals and organizations willing to contribute to the community (if interested, contact cdi@usgs.gov). The purpose of the CDI is to do the following: • advance understanding of Earth systems through enhanced use of data and information including associated tools and techniques, • provide a forum for people doing work with data integration to come together to share ideas and learn new skills and techniques, and • grow overall USGS capabilities with data and information by increasing visibility of the work of many people throughout the USGS and the CDI community. To achieve these goals, the CDI operates within four applied areas: monthly forums, annual workshop/webinar series, working groups, and projects. The monthly forums, also known as the Opportunity/Challenge of the Month, provide an open dialogue to share and learn about data integration efforts or to present problems that invite the community to offer solutions, advice, and support. Since 2010, the CDI has also sponsored annual workshops/webinar series to encourage the exchange of ideas, sharing of activities, presentations of current projects, and networking among members. Stemming from common interests, the working groups are focused on efforts to address data management and technical challenges including the development of standards and tools, improving interoperability and information infrastructure, and data preservation within USGS and its partners. The growing support for the activities of the working groups led to the CDI’s first formal request for proposals (RFP) process in 2013 to fund projects that produced tangible products. As of 2014, the CDI continues to hold an annual RFP that creates data management tools and practices, collaboration tools, and training in support of data integration and delivery.

Open-File Report↗
USGS2026

Origins, evolutions, and future directions of Landsat science products for advancing global inland water and coastal ocean observations

In April 2020, the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center introduced a Level 2 provisional Aquatic Reflectance (AR) product for the Landsat 8 Operational Land Imager (OLI), marking the initial phase in developing a standardized global product for Landsat-derived surface water measurements. The goal of USGS EROS aquatic product research and development is to prepare for an operational processing architecture for Landsat Collection 3 in the late 2020s that will enable use of quality-controlled data for emerging Landsat aquatic science applications. To achieve this, we released a subset of the Landsat 8/9 provisional AR products (Crawford et al., 2025, https://doi.org/10.5066/P14MBBRM) and examined its general performance through the Science Algorithms to Operations (SATO) framework alongside quantitative assessment using community made inland water data records (GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments, GLORIA) and radiometric coastal validation platforms (NASA’s Ocean Color component of the Aerosol Robotic Network, AERONET-OC). Variability within the validation datasets indicate that the performance of the Landsat 8/9 provisional AR retrieval is highly context-dependent; errors are minimal in optically simple waters (e.g., clear to moderately turbid coastal waters) but increase considerably in optically complex waters where factors such as elevated levels of turbidity, chlorophyll (Chl a ) concentrations, or colored dissolved organic matter (CDOM) dominate the water column. Additionally, this paper examines key algorithmic considerations for atmospheric correction, highlighting factors that influence accuracy, scalability, and computational efficiency necessary for collection processing in the operational Landsat Product Generation System (LPGS). This paper is intended to communicate with aquatic scientists, satellite oceanographers, and the broader Earth observation community on the origins, requirements, challenges, successes, and future objectives for operationalizing global AR data products for Landsat satellite missions.

Earth System Science Data↗
USGS2016

Combining citizen science species distribution models and stable isotopes reveals migratory connectivity in the secretive Virginia rail

Stable hydrogen isotope (δD) methods for tracking animal movement are widely used yet often produce low resolution assignments. Incorporating prior knowledge of abundance, distribution or movement patterns can ameliorate this limitation, but data are lacking for most species. We demonstrate how observations reported by citizen scientists can be used to develop robust estimates of species distributions and to constrain δD assignments. We developed a Bayesian framework to refine isotopic estimates of migrant animal origins conditional on species distribution models constructed from citizen scientist observations. To illustrate this approach, we analysed the migratory connectivity of the Virginia rail Rallus limicola , a secretive and declining migratory game bird in North America. Citizen science observations enabled both estimation of sampling bias and construction of bias-corrected species distribution models. Conditioning δD assignments on these species distribution models yielded comparably high-resolution assignments. Most Virginia rails wintering across five Gulf Coast sites spent the previous summer near the Great Lakes, although a considerable minority originated from the Chesapeake Bay watershed or Prairie Pothole region of North Dakota. Conversely, the majority of migrating Virginia rails from a site in the Great Lakes most likely spent the previous winter on the Gulf Coast between Texas and Louisiana. Synthesis and applications . In this analysis, Virginia rail migratory connectivity does not fully correspond to the administrative flyways used to manage migratory birds. This example demonstrates that with the increasing availability of citizen science data to create species distribution models, our framework can produce high-resolution estimates of migratory connectivity for many animals, including cryptic species. Empirical evidence of links between seasonal habitats will help enable effective habitat management, hunting quotas and population monitoring and also highlight critical knowledge gaps.

Journal of Applied Ecology↗