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

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At least 271 records · Page 15Linked to original sources
USGS1992

Toward digital geologic map standards: a progress report

Establishing modern scientific and technical standards for geologic maps and their derivative map products is vital to both producers and users of such maps as we move into an age of digital cartography. Application of earth-science data in complex geographic information systems, acceleration of geologic map production, and reduction of population costs require that national standards be developed for digital geologic cartography and computer analysis. Since December 1988, under commission of the Chief Geologic of the U.S. Geological Survey and the mandate of the National Geologic Mapping Program (with added representation from the Association of American State Geologists), a committee has been designing a comprehensive set of scientific map standards. Three primary issues were: (1) selecting scientific symbology and its digital representation; (2) creating an appropriate digital coding system that characterizes geologic features with respect to their physical properties, stratigraphic and structural relations, spatial orientation, and interpreted mode of origin; and (3) developing mechanisms for reporting levels of certainty for descriptive as well as measured properties. Approximately 650 symbols for geoscience maps, including present usage of the U.S Geological Survey, state geological surveys, industry, and academia have been identified and tentatively adopted. A proposed coding system comprises four-character groupings of major and minor codes that can identify all attributes of a geologic feature. Such a coding system allows unique identification of as many as 105 geologic names and values on a given map. The new standard will track closely the latest developments of the Proposed Standard for Digital Cartographic Data soon to be submitted to the National Institute of Standards and Technology by the Federal Interagency Coordinating Committee on Digital Cartography. This standard will adhere generally to the accepted definitions and specifications for spatial data transfer. It will require separate specifications of digital cartographic quality relating to positional accuracy and ranges of measured and interpreted values such as geologic age and rock composition. Provisional digital geologic map standards will be published for trial implementation. After approximately two years, when comments on the proposed standards have been solicited and modifications made, formal adoption of the standards will be recommended. Widespread acceptance of the new standards will depend on their applicability to the broadest range of earth-science map products and their adaptability to changing cartographic technology.

Conference Paper↗
USGS2017

Sharing our data—An overview of current (2016) USGS policies and practices for publishing data on ScienceBase and an example interactive mapping application

This report provides an overview of current (2016) U.S. Geological Survey policies and practices related to publishing data on ScienceBase, and an example interactive mapping application to display those data. ScienceBase is an integrated data sharing platform managed by the U.S. Geological Survey. This report describes resources that U.S. Geological Survey Scientists can use for writing data management plans, formatting data, and creating metadata, as well as for data and metadata review, uploading data and metadata to ScienceBase, and sharing metadata through the U.S. Geological Survey Science Data Catalog. Because data publishing policies and practices are evolving, scientists should consult the resources cited in this paper for definitive policy information. An example is provided where, using the content of a published ScienceBase data release that is associated with an interpretive product, a simple user interface is constructed to demonstrate how the open source capabilities of the R programming language and environment can interact with the properties and objects of the ScienceBase item and be used to generate interactive maps.

Open-File Report↗
USGS2009

Vegetation classification and distribution mapping report: Mesa Verde National Park

The classification and distribution mapping of the vegetation of Mesa Verde National Park (MEVE) and surrounding environment was achieved through a multi-agency effort between 2004 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center, Fort Collins Research Center, and Rocky Mountain Geographic Science Center; Northern Arizona University; Prescott College; and NatureServe. The project team described 47 plant communities for MEVE, 34 of which were described from quantitative classification based on f eld-relevé data collected in 1993 and 2004. The team derived 13 additional plant communities from field observations during the photointerpretation phase of the project. The National Vegetation Classification Standard served as a framework for classifying these plant communities to the alliance and association level. Eleven of the 47 plant communities were classified as “park specials;” that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing MEVE, with three different map-class schemas: base, group, and management map classes. The base map classes represent the fi nest level of spatial detail. Initial polygons were developed using Definiens Professional (at the time of our use, this software was called eCognition), assisted by interpretation of 1:12,000 true-color digital orthophoto quarter quadrangles (DOQQs). These polygons (base map classes) were labeled using manual photo interpretation of the DOQQs and 1:12,000 true-color aerial photography. Field visits verified interpretation concepts. The vegetation map database includes 46 base map classes, which consist of associations, alliances, and park specials classified with quantitative analysis, additional associations and park specials noted during photointerpretation, and non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 5,007 polygons in the project area. A field-based accuracy assessment of the base map classes showed overall accuracy to be 43.5%. Seven map classes comprise 89.1% of the park vegetated land cover. The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, version 2 (Federal Geographic Data Committee 2007), and reflecting physiognomy and floristics. Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as the fi rst approximation of the group level. The project team identified 14 group map classes for this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 80.3%. In consultation with park staff , the team developed management map classes, consisting of park-defined groupings of base map classes intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 23 management map classes had an overall accuracy of 73.3%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary digital geographic information system and database products were also produced that can be used independently or to augment the main products. These products include shapefiles of the locations of field-collected data and relational databases of field-collected data.

Mesa Verde National Park↗
USGS2004

User's Guide for the MapImage Reprojection Software Package, Version 1.01

Scientists routinely accomplish small-scale geospatial modeling in the raster domain, using high-resolution datasets (such as 30-m data) for large parts of continents and low-resolution to high-resolution datasets for the entire globe. Recently, Usery and others (2003a) expanded on the previously limited empirical work with real geographic data by compiling and tabulating the accuracy of categorical areas in projected raster datasets of global extent. Geographers and applications programmers at the U.S. Geological Survey's (USGS) Mid-Continent Mapping Center (MCMC) undertook an effort to expand and evolve an internal USGS software package, MapImage, or mapimg, for raster map projection transformation (Usery and others, 2003a). Daniel R. Steinwand of Science Applications International Corporation, Earth Resources Observation Systems Data Center in Sioux Falls, S. Dak., originally developed mapimg for the USGS, basing it on the USGS's General Cartographic Transformation Package (GCTP). It operated as a command line program on the Unix operating system. Through efforts at MCMC, and in coordination with Mr. Steinwand, this program has been transformed from an application based on a command line into a software package based on a graphic user interface for Windows, Linux, and Unix machines. Usery and others (2003b) pointed out that many commercial software packages do not use exact projection equations and that even when exact projection equations are used, the software often results in error and sometimes does not complete the transformation for specific projections, at specific resampling resolutions, and for specific singularities. Direct implementation of point-to-point transformation with appropriate functions yields the variety of projections available in these software packages, but implementation with data other than points requires specific adaptation of the equations or prior preparation of the data to allow the transformation to succeed. Additional constraints apply to global raster data. It appears that some packages use the USGS's GCTP or similar point transformations without adaptation to the specific characteristics of raster data (Usery and others, 2003b). It is most common for programs to compute transformations of raster data in an inverse fashion. Such mapping can result in an erroneous position and replicate data or create pixels not in the original space. As Usery and others (2003a) indicated, mapimg performs a corresponding forward transformation to ensure the same location results from both methods. The primary benefit of this function is to mask cells outside the domain. MapImage 1.01 is now on the Web. You can download the User's Guide, source, and binaries from the following site: http://mcmcweb.er.usgs.gov/carto_research/projection/acc_proj_data.html

Open-File Report↗
USGS1999

Scientists in action!

News about careers in the natural sciences—from mapping the planets to sampling the ocean floor, from protecting wildlife to forecasting volcanic eruptions.

Report↗
USGS2005

Scientists in action

News about careers in the natural sciences -- from mapping the planets to sampling the ocean floor, from protecting wildlife to forecasting volcanic eruptions.

General Information Product↗
USGS2009

Science-Based Strategies for Sustaining Coral Ecosystems

Coral ecosystems and their natural capital are at risk. Greenhouse gas emissions, overfishing, and harmful land-use practices are damaging our coral reefs. Overwhelming scientific evidence indicates that the threats are serious, and if they are left unchecked, the ecological and social consequences will be significant and widespread. Although the primary stressors to coral ecosystems are known, science-based strategies are needed to more accurately explain natural processes and forecast human-induced change. Collaborations among managers and scientists and enhanced mapping, monitoring, research, and modeling can lead to effective mitigation plans. U.S. Geological Survey scientists and their partners assess coral ecosystem history, ecology, vulnerability, and resiliency and provide study results to decisionmakers who may devise policies to sustain coral resources and the essential goods and services they provide.

Fact Sheet↗
USGS2024

System characterization report on the Gaofen-6

Executive Summary Gaofen-6 represents a series of Chinese high-resolution Earth observation satellites. More than 12 satellites have been launched in the Gaofen series, beginning with Gaofen-1 in 2013. Satellites within the series have varying infrared, radar, and optical imaging capabilities. The primary goal for the satellites in this series is to provide near real-time observations for climate change monitoring, geographical mapping, precision agriculture support, environmental and resource surveying, and disaster prevention. More information on Chinese satellites and sensors is available in the “2022 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium.” 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 of Gaofen-6. Results of these analyses indicate that Gaofen-6 has an interior geometric performance root mean square error ranging from 2.84 meters (m; 0.18 pixel) to 7.42 m (0.46 pixel) in easting and from 2.84 m (0.18 pixel) to 11.57 m (0.72 pixel) in northing in band-to-band registration, an exterior geometric performance root mean square error ranging from 154.50 m (8.80 pixels) in easting to 14.65 m (0.80 pixel) in northing in comparison to a corresponding Sentinel-2 scene, a radiometric performance ranging from 0.018 to 0.055 (in offset) and from 0.620 to 0.858 (in slope), and a spatial performance ranging from 2.10 to 2.30 pixels at full width at half maximum, with a modulation transfer function at a Nyquist frequency ranging from 0.040 to 0.055.

Open-File Report↗
USGS2000

Finding your way with map and compass

A topographic map tells you where things are and how to get to them, whether you're hiking, biking, hunting, fishing, or just interested in the world around you. These maps describe the shape of the land. They define and locate natural and manmade features like woodlands, waterways, important buildings, and bridges. They show the distance between any two places, and they also show the direction from one point to another. Distances and directions take a bit of figuring, but the topography and features of the land are easy to determine. The topography is shown by contours. These are imaginary lines that follow the ground surface at a constant elevation; they are usually printed in brown, in two thicknesses. The heavier lines are called index contours, and they are usually marked with numbers that give the height in feet or meters. The contour interval, a set difference in elevation between the brown lines, varies from map to map; its value is given in the margin of each map. Contour lines that are close together represent steep slopes. Natural and manmade features are represented by colored areas and by a set of standard symbols on all U.S . Geological Survey (USGS) topographic maps. Woodlands, for instance, are shown in a green tint; waterways, in blue. Buildings may be shown on the map as black squares or outlines. Recent changes in an area may be shown by a purple overprint. A road may be printed in red or black solid or dashed lines, depending on its size and surface. A list of symbols is available from the Earth Science Information Center (ESIC).

Fact Sheet↗
USGS2016

Get your science used—Six guidelines to improve your products

Introduction Natural scientists, like many other experts, face challenges when communicating to people outside their fields of expertise. This is especially true when they try to communicate to those whose background, knowledge, and experience are far distant from that field of expertise. At a recent workshop, experts in risk communication offered insights into the communication challenges of probabilistic hazard products, suggested tips, and shared their strategies for making products that a targeted audience can understand and use. Although the workshop was held to broaden the understanding and use of the U.S. Geological Survey (USGS) National Seismic Hazard Maps (NSHM), the workshop outcomes presented in this report can benefit anyone who develops products based on technical information. On the basis of research and practice into how people think, use tools, make decisions, and understand scientific/technical information, the social and behavioral scientists, marketers, and social-impact designers at the NSHM workshop provided remarkably consistent guidelines to develop successful science products, such as text, maps, and other products. In this report the guidelines are numbered for clarity, but they can be applied repeatedly, piecemeal, or out of order to fit each project and your resources.

Circular↗
USGS2010

Vegetation classification and distribution mapping report: Canyon de Chelly National Monument

Executive Summary: The classification and distribution mapping of the vegetation of Canyon de Chelly National Monument (CACH) and surrounding environment was accomplished through a multi-agency effort between 2003 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center and Fort Collins Science Center, Navajo Natural Heritage Program, Northern Arizona University, and NatureServe. The project team described 48 plant communities for CACH—35 of which were described from quantitative classification based on field-relevé data collected in 2004. Five additional plant communities were based on field relevés collected in a previous study. The team derived four additional plant communities from field observations during the photointerpretation phase of the project, and field documented them during accuracy assessment. The National Vegetation Classification Standard served as a conceptual framework for assigning these plant communities to the alliance and association level. Ten of the 48 plant communities were designated “park specials”, that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing CACH, with three different map-class schemas: base, group, and management map classes. The base map classes represented the finest level of spatial detail. Photointerpreters delineated initial polygons through manual interpretation of 2003/2004 1:12,000-scale true color aerial photography supplemented by occasional computer screen digitizing on a mosaic of digitized aerial photos. These polygons were labeled with base map classes during photointerpretation. Field visits verified interpretation concepts. The vegetation map database includes • ? 53 base map classes, which consist of associations and park specials classified with the quantitative analysis • ? additional associations noted during photointerpretation • ? non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 4,718 polygons in the project area. A field-based accuracy assessment of the base map classes showed the overall accuracy to be 50.8% The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, Version 2 (Federal Geographic Data Committee 2008). Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as a first approximation of the group level. The project team identified 16 group map classes in this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 79.9%. In consultation with park staff, the team developed management map classes that consisted of park-defined groupings of base map classes and were intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 28 management map classes have an overall accuracy of 77.1%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary geographic information system and digital database products were also produced that can be used independently, or to augment the main products. These products include shapefiles of the location of field-collected data and relational databases of field-collected data.

Report↗
USGS2013

Geodatabase compilation of hydrogeologic, remote sensing, and water-budget-component data for the High Plains aquifer, 2011

The High Plains aquifer underlies almost 112 million acres in the central United States. It is one of the largest aquifers in the Nation in terms of annual groundwater withdrawals and provides drinking water for 2.3 million people. The High Plains aquifer has gained national and international attention as a highly stressed groundwater supply primarily because it has been appreciably depleted in some areas. The U.S. Geological Survey has an active program to monitor the changes in groundwater levels for the High Plains aquifer and has documented substantial water-level changes since predevelopment: the High Plains Groundwater Availability Study is part of a series of regional groundwater availability studies conducted to evaluate the availability and sustainability of major aquifers across the Nation. The goals of the regional groundwater studies are to quantify current groundwater resources in an aquifer system, evaluate how these resources have changed over time, and provide tools to better understand a systems response to future demands and environmental stresses. The purpose of this report is to present selected data developed and synthesized for the High Plains aquifer as part of the High Plains Groundwater Availability Study. The High Plains Groundwater Availability Study includes the development of a water-budget-component analysis for the High Plains completed in 2011 and development of a groundwater-flow model for the northern High Plains aquifer. Both of these tasks require large amounts of data about the High Plains aquifer. Data pertaining to the High Plains aquifer were collected, synthesized, and then organized into digital data containers called geodatabases. There are 8 geodatabases, 1 file geodatabase and 7 personal geodatabases, that have been grouped in three categories: hydrogeologic data, remote sensing data, and water-budget-component data. The hydrogeologic data pertaining to the northern High Plains aquifer is included in three separate geodatabases: (1) base data from a groundwater-flow model; (2) hydrogeology and hydraulic properties data; and (3) groundwater-flow model data to be used as calibration targets. The remote sensing data for this study were developed by the U. S. Geological Survey Earth Resources Observation and Science Center and include historical and predicted land-use/land-cover data and actual evapotranspiration data by using remotely sensed temperature data. The water-budget-component data contains selected raster data from maps in the “Selected Approaches to Estimate Water-Budget Components of the High Plains, 1940 Through 1949 and 2000 Through 2009” report completed in 2011 ( http://pubs.usgs.gov/sir/2011/5183/ ). Federal Geographic Data Committee compliant metadata were created for each spatial and tabular data layer in the geodatabases.

Colorado, Kansas, Nebraska, New Mexico, Oklahoma, ↗
USGS2023

Winter distribution of golden eagles in the Eastern USA

Golden Eagles ( Aquila chrysaetos ) have a Holarctic distribution, but some details of that overall distribution are poorly understood, including parts of the range in eastern North America. Recent studies in the region suggest that Golden Eagles may be more widely distributed than previously recognized. For species specific conservation efforts to be effective, an understanding of the distribution of the species is essential. Thus, the goal of this study was to map the winter distribution of Golden Eagles in the eastern half of the USA. To accomplish this, we reviewed and compiled 11,981 Golden Eagle records from eight data sources, including literature and ornithology records, community science data, survey data, and telemetry data. We found that Golden Eagles were observed in winter in each of the 31 states that lie completely east of the 100th meridian and in 1244 of the 2045 counties (61%) in those states. The proportion of counties with records varied by physiographic province, with higher proportions in physiographic provinces with more rugged terrain and greater forest cover. Our study shows that Golden Eagles are more widely distributed during winter in eastern USA states than was previously recognized. This work provides an important foundation for future management and research at a time when threats to this species are expanding rapidly on the landscape.

Journal of Raptor Research↗
USGS2016

Flood- and drought-related natural hazards activities of the U.S. Geological Survey in New England

The U.S. Geological Survey (USGS) has many ongoing and recent water-related natural hazard activities in New England that can be used to help mitigate the effects of natural hazards in cooperation with other agencies. The themes related to potential hazards and the tools and science to better understand and address them include the following: Erosion and landslides • Fluvial erosion (sediment transport, bridge scour, and bankfull channel geometry characterization) • Current and historic landslide mapping Flood documentation and assessment • Flood high-water marks • Flood modeling and frequency analysis • Flood inundation mapping • Peak-flow regression equations Drought documentation and assessment • Drought frequency analysis • Low-flow frequency and flow duration statistics • Water use and availability during drought Hydrologic monitoring • Streamflow monitoring network • Groundwater monitoring network • Tidal monitoring network • Snow surveys and ice jam monitoring Tools for natural hazard assessment and mitigation • Light detection and ranging (lidar) remote sensing technology • StreamStats Web-based tool for streamflow statistics • Flood inundation mapper

New England↗
USGS2025

U.S. Geological Survey—Department of the Interior, Region 11, Alaska—2023–24 biennial science report

Introduction U.S. Geological Survey (USGS) Mission—The USGS national mission is to monitor, analyze, and predict the current and evolving dynamics of complex human and natural Earth-system interactions and to deliver actionable information at scales and timeframes relevant to decision makers. Consistent with the national mission, the USGS in Alaska provides timely and objective scientific information to help address issues and inform management decisions across five interconnected focus areas: Energy and Minerals; Geospatial Mapping; Natural Hazards; Water Quality, Streamflow, and Ice Dynamics; and Ecosystems. The USGS in Alaska consists of approximately 350 scientists and support staff working in 3 Alaska-based science centers. USGS science activities are also initiated by the Cooperative Research Unit and USGS centers outside Alaska. In the last 5 years, USGS research in Alaska has produced many scientific benefits resulting from more than 900 publications. Publications relevant to Alaska can be conveniently searched by keyword through the USGS Publications Warehouse at https://pubs.usgs.gov/.

Alaska↗
USGS2021

U.S. Geological Survey—Department of the Interior Region 11, Alaska —2020 annual science report

U.S. Geological Survey (USGS) Mission: The USGS national mission is to monitor, analyze, and predict current and evolving dynamics of complex human and natural Earth-system interactions and to deliver actionable information at scales and timeframes relevant to decision-makers. Consistent with the national mission, the USGS in Alaska provides timely and objective scientific information to help address issues and inform management decisions across five inter-connected themes: Energy and Minerals; Geospatial Mapping; Natural Hazards; Water Quality, Streamflow, and Ice Dynamics; and Ecosystems. The USGS in Alaska consists of approximately 350 scientists and support staff working in three Alaska-based science centers, a Cooperative Research Unit, and USGS centers outside Alaska, with a combined annual science budget of about $60 million. In the last 5 years, USGS research in Alaska has produced many scientific benefits resulting from more than 1,100 publications. Publications relevant to Alaska can be conveniently searched by keyword through the USGS Publications Warehouse at https://pubs.er.usgs.gov/search?q=Alaska .

Alaska↗
USGS2012

Digital database architecture and delineation methodology for deriving drainage basins, and a comparison of digitally and non-digitally derived numeric drainage areas

The drainage basin is a fundamental hydrologic entity used for studies of surface-water resources and during planning of water-related projects. Numeric drainage areas published by the U.S. Geological Survey water science centers in Annual Water Data Reports and on the National Water Information Systems (NWIS) Web site are still primarily derived from hard-copy sources and by manual delineation of polygonal basin areas on paper topographic map sheets. To expedite numeric drainage area determinations, the Colorado Water Science Center developed a digital database structure and a delineation methodology based on the hydrologic unit boundaries in the National Watershed Boundary Dataset. This report describes the digital database architecture and delineation methodology and also presents the results of a comparison of the numeric drainage areas derived using this digital methodology with those derived using traditional, non-digital methods. (Please see report for full Abstract)

Techniques and Methods↗
USGS2012

United States Geological Survey fire science: Fire danger monitoring and forecasting

Each day, the U.S. Geological Survey produces 7-day forecasts for all Federal lands of the distributions of number of ignitions, number of fires above a given size, and conditional probabilities of fires growing larger than a specified size. The large fire probability map is an estimate of the likelihood that ignitions will become large fires. The large fire forecast map is a probability estimate of the number of fires on federal lands exceeding 100 acres in the forthcoming week. The ignition forecast map is a probability estimate of the number of fires on Federal land greater than 1 acre in the forthcoming week. The extreme event forecast is the probability estimate of the number of fires on Federal land that may exceed 5,000 acres in the forthcoming week.

Fact Sheet↗