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At least 1,657 records · Page 92Linked to original sources
USGS2007

LiDAR-Derived Flood-Inundation Maps for Real-Time Flood-Mapping Applications, Tar River Basin, North Carolina

Flood-inundation maps were created for selected streamgage sites in the North Carolina Tar River basin. Light detection and ranging (LiDAR) data with a vertical accuracy of about 20 centimeters, provided by the Floodplain Mapping Information System of the North Carolina Floodplain Mapping Program, were processed to produce topographic data for the inundation maps. Bare-earth mass point LiDAR data were reprocessed into a digital elevation model with regularly spaced 1.5-meter by 1.5-meter cells. A tool was developed as part of this project to connect flow paths, or streams, that were inappropriately disconnected in the digital elevation model by such features as a bridge or road crossing. The Hydraulic Engineering Center-River Analysis System (HEC-RAS) model, developed by the U.S. Army Corps of Engineers, was used for hydraulic modeling at each of the study sites. Eleven individual hydraulic models were developed for the Tar River basin sites. Seven models were developed for reaches with a single gage, and four models were developed for reaches of the Tar River main stem that receive flow from major gaged tributaries, or reaches in which multiple gages were near one another. Combined, the Tar River hydraulic models included 272 kilometers of streams in the basin, including about 162 kilometers on the Tar River main stem. The hydraulic models were calibrated to the most current stage-discharge relations at 11 long-term streamgages where rating curves were available. Medium- to high-flow discharge measurements were made at some of the sites without rating curves, and high-water marks from Hurricanes Fran and Floyd were available for high-stage calibration. Simulated rating curves matched measured curves over the full range of flows. Differences between measured and simulated water levels for a specified flow were no more than 0.44 meter and typically were less. The calibrated models were used to generate a set of water-surface profiles for each of the 11 modeled reaches at 0.305-meter increments for water levels ranging from bankfull to approximately the highest recorded water level at the downstream-most gage in each modeled reach. Inundated areas were identified by subtracting the water-surface elevation in each 1.5-meter by 1.5-meter grid cell from the land-surface elevation in the cell through an automated routine that was developed to identify all inundated cells hydraulically connected to the cell at the downstream-most gage in the model domain. Inundation maps showing transportation networks and orthoimagery were prepared for display on the Internet. These maps also are linked to the U.S. Geological Survey North Carolina Water Science Center real-time streamflow website. Hence, a user can determine the near real-time stage and water-surface elevation at a U.S. Geological Survey streamgage site in the Tar River basin and link directly to the flood-inundation maps for a depiction of the estimated inundated area at the current water level. Although the flood-inundation maps represent distinct boundaries of inundated areas, some uncertainties are associated with these maps. These are uncertainties in the topographic data for the hydraulic model computational grid and inundation maps, effective friction values (Manning's n), model-validation data, and forecast hydrographs, if used. The Tar River flood-inundation maps were developed by using a steady-flow hydraulic model. This assumption clearly has less of an effect on inundation maps produced for low flows than for high flows when it typically takes more time to inundate areas. A flood in which water levels peak and fall slowly most likely will result in more inundation than a similar flood in which water levels peak and fall quickly. Limitations associated with the steady-flow assumption for hydraulic modeling vary from site to site. The one-dimensional modeling approach used in this study resulted in good agreement between measurements and simulations. T

North Carolina↗
USGS2016

Bedrock morphology and structure, upper Santa Cruz Basin, south-central Arizona, with transient electromagnetic survey data

The upper Santa Cruz Basin is an important groundwater basin containing the regional aquifer for the city of Nogales, Arizona. This report provides data and interpretations of data aimed at better understanding the bedrock morphology and structure of the upper Santa Cruz Basin study area which encompasses the Rio Rico and Nogales 1:24,000-scale U.S. Geological Survey quadrangles. Data used in this report include the Arizona Aeromagnetic and Gravity Maps and Data referred to here as the 1996 Patagonia Aeromagnetic survey, Bouguer gravity anomaly data, and conductivity-depth transforms (CDTs) from the 1998 Santa Cruz transient electromagnetic survey (whose data are included in appendixes 1 and 2 of this report). Analyses based on magnetic gradients worked well to identify the range-front faults along the Mt. Benedict horst block, the location of possibly fault-controlled canyons to the west of Mt. Benedict, the edges of buried lava flows, and numerous other concealed faults and contacts. Applying the 1996 Patagonia aeromagnetic survey data using the horizontal gradient method produced results that were most closely correlated with the observed geology. The 1996 Patagonia aeromagnetic survey was used to estimate depth to bedrock in the upper Santa Cruz Basin study area. Three different depth estimation methods were applied to the data: Euler deconvolution, horizontal gradient magnitude, and analytic signal. The final depth to bedrock map was produced by choosing the maximum depth from each of the three methods at a given location and combining all maximum depths. In locations of rocks with a known reversed natural remanent magnetic field, gravity based depth estimates from Gettings and Houser (1997) were used. The depth to bedrock map was supported by modeling aeromagnetic anomaly data along six profiles. These cross sectional models demonstrated that by using the depth to bedrock map generated in this study, known and concealed faults, measured and estimated magnetic susceptibilities of rocks found in the study area, and estimated natural remanent magnetic intensities and directions, reasonable geologic models can be built. This indicates that the depth to bedrock map is reason-able and geologically possible. Finally, CDTs derived from the 1998 Santa Cruz Basin transient electromagnetic survey were used to help identify basin structure and some physical properties of the basin fill in the study area. The CDTs also helped to confirm depth to bedrock estimates in the Santa Cruz Basin, in particular a region of elevated bedrock in the area of Potrero Canyon, and a deep basin in the location of the Arizona State Highway 82 microbasin. The CDTs identified many concealed faults in the study area and possibly indicate deep water-saturated clay-rich sediments in the west-central portion of the study area. These sediments grade to more sand-rich saturated sediments to the south with relatively thick, possibly unsaturated, sediments at the surface. Also, the CDTs may indicate deep saturated clay-rich sediments in the Highway 82 microbasin and in the Mount Benedict horst block from Proto Canyon south to the international border.

Arizona↗
USGS2009

History of the topographic branch (division)

From a very early period of the world's existence, man has endeavored to represent the earth's surface in a graphic form for the information of his fellow men, realizing that no oral or written description is capable of setting forth topographic facts so vividly and so clearly as a map. Mapping of the areas of the United States began with the charting of portions of its coast line by early explorers; the need for topographic maps was first recognized during the war of the Colonies for independence from Great Britain. On July 22, 1777, Congress authorized General Washington to appoint: 'Mr. Robert Erskine, or any other person that he may think proper, geographer and surveyor of the roads, to take sketches of the country and the seat of war.' By several acts during the Revolutionary War, Congress provided 'geographers' for the armies of the United States, some of them with the pay of a colonel, amounting to $60 a month and allowances. At the end of the War, a resolution of May 27, 1785, continued in service the 'geographer of the United States' for a period of 3 years. The War Department recognized the necessity of 'geographical engineers' and requested Congress to authorize their appointment, but it was not until the next war that Congress authorized on March 3, 1813, the appointment of eight topographic engineers and eight assistant topographic engineers under the direction of the General Staff of the Army. These officers formed the nucleus of the first Corps of Topographic Engineers in the Army, and that Corps continued to function as an independent unit until it was absorbed by the Corps of Engineers in 1863, during the Civil War between the States. Between the Louisiana Purchase in 1803, and the outbreak of the Civil War, more than a hundred exploring and mapping expeditions were sent into the vast territory lying west of the Mississippi River to investigate the natural resources of this newly acquired country and to find possible locations for wagon roads to the Pacific Coast. These expeditions were sent out by the War Department and were in charge of Army officers. It is interesting to note that such generals as George G. Meade, J.C. Fremont, Joseph E. Johnston, W.F. Smith, John Pope, A.W. Whipple, J.G. Parke, G.K. Warren, and H.L. Abbott, all officers of the Corps of Topographic Engineers, had charge of expeditions and were among our earliest map makers. Unfortunately, the data obtained by these editions were not of sufficient accuracy to serve as a basis for topographic maps of value other than in illustrating their voluminous reports. During this early period, numerous surveys were undertaken within the original Thirteen States, by the Federal government and by the States. The most important were those carried on by the U.S. Coast and Geodetic Survey, which made an accurate survey of the Atlantic Coastline and established a triangulation system that was of so high a standard as to constitute the first and only accurate data for topographic mapping obtained before the Civil War. The Coast and Geodetic Survey, while charting the coast and rivers, also mapped a strip of country extending a few miles inland, the relief being shown by means of hachures, together with contour lines, until 1846 when the first government topographic map on which the relief was shown by contours alone was made, covering an area in the vicinity of Boston Harbor. In 1835, however, the Geological and Topographical Survey of Maryland had issued a map on which the relief was shown by contours, and this is believed to be the first contoured map issued in this country. The outbreak of the Civil War stopped all mapping activities other than those needed by the U.S. Army. During the war, topographic surveys were carried on throughout the war zone under the supervision of the Corps of Engineers, the topographers being civilian employees. After the war, the country west of the Mississippi again became the center of the mapping activities

Circular↗
USGS2018

Hydrogeophysics at societally relevant scales: Airborne electromagnetic applications and model structural uncertainty quantification

There is a critical and growing need for information about subsurface geological properties and processes over sufficiently large areas that can inform key scientific and societal studies. Airborne geophysical methods fill a unique role in Earth observation because of their ability to detect deep subsurface properties at regional scales and with high spatial resolution that cannot be achieved with groundbased measurements. Airborne electromagnetics, or AEM, is one technique that is rapidly emerging as a foundational tool for geological mapping, with widespread application to studies of water and mineral resources, geologic hazards, infrastructure, the cryosphere, and the environment. Applications of AEM are growing worldwide, with rapid developments in instrumentation and data analysis software. In this study, we summarize several recent hydrogeophysical applications of AEM, including examples drawn from a recent survey in the Mississippi Alluvial Plain (MAP). In addition, we discuss developments in computational methods for geophysical and geological model structural uncertainty quantification using AEM data, and how these results are used in a sequential hydrogeophysical approach to characterize hydrologic parameters and prediction uncertainty.

Conference Paper↗
USGS2001

National Atlas of the United States Maps

The "National Atlas of the United States of America ® ", published by the U.S. Geological Survey (USGS) in 1970, is out of print, but many of its maps can be purchased separately. Maps that span facing pages in the atlas are printed on one sheet. Maps dated after 1970 and before 1997 are either revisions of original atlas maps or new maps published in the original atlas format. The USGS and its partners in government and industry began work on a new "National Atlas" in 1997. Though most new atlas products are designed for the World Wide Web, we are continuing our tradition of printing high-quality maps of America. In 1998, the first completely redesigned maps of the "National Atlas of the United States ® " were published.

Fact Sheet↗
USGS2000

The National Atlas of the United States TM maps

The National Atlas of the United States of America™, published by the U.S. Geological Survey (USGS) in 1970, is out of print, but many of its maps can be purchased separately. Maps that span facing pages in the atlas are printed on one sheet. Maps dated after 1970 and before 1997 are either revisions of original atlas maps or new maps published in the original atlas format. The USGS and its partners in government and industry began work on a new National Atlas in 1997. Though most new atlas products are designed for the World Wide Web, we are continuing our tradition of printing highquality maps of America. In 1998, the first completely redesigned maps of the National Atlas of the United States™ were published. Refer to the USGS Maps Price List for the most recent prices of all USGS maps and the USGS Maps, Books, and Other Published Products Order Form for ordering instructions.

Fact Sheet↗
USGS2016

Optimizing selection of training and auxiliary data for operational land cover classification for the LCMAP initiative

The U.S. Geological Survey’s Land Change Monitoring, Assessment, and Projection (LCMAP) initiative is a new end-to-end capability to continuously track and characterize changes in land cover, use, and condition to better support research and applications relevant to resource management and environmental change. Among the LCMAP product suite are annual land cover maps that will be available to the public. This paper describes an approach to optimize the selection of training and auxiliary data for deriving the thematic land cover maps based on all available clear observations from Landsats 4–8. Training data were selected from map products of the U.S. Geological Survey’s Land Cover Trends project. The Random Forest classifier was applied for different classification scenarios based on the Continuous Change Detection and Classification (CCDC) algorithm. We found that extracting training data proportionally to the occurrence of land cover classes was superior to an equal distribution of training data per class, and suggest using a total of 20,000 training pixels to classify an area about the size of a Landsat scene. The problem of unbalanced training data was alleviated by extracting a minimum of 600 training pixels and a maximum of 8000 training pixels per class. We additionally explored removing outliers contained within the training data based on their spectral and spatial criteria, but observed no significant improvement in classification results. We also tested the importance of different types of auxiliary data that were available for the conterminous United States, including: (a) five variables used by the National Land Cover Database, (b) three variables from the cloud screening ‘‘Function of mask” (Fmask) statistics, and (c) two variables from the change detection results of CCDC. We found that auxiliary variables such as a Digital Elevation Model and its derivatives (aspect, position index, and slope), potential wetland index, water probability, snow probability, and cloud probability improved the accuracy of land cover classification. Compared to the original strategy of the CCDC algorithm (500 pixels per class), the use of the optimal strategy improved the classification accuracies substantially (15-percentage point increase in overall accuracy and 4-percentage point increase in minimum accuracy).

ISPRS Journal of Photogrammetry and Remote Sensing↗
USGS2026

A targeted approach for mapping groundwater discharge to surface water and fish thermal refuge in four Lake Ontario tributaries

The duration, magnitude, and frequency of heatwaves are predicted to increase in the coming decades, a combination that can reduce the survival of many fish species. Across the world, there is broad interest in identifying thermal refuge for heat-intolerant fish species and exploring opportunities to enhance or protect these areas. Because deeper groundwater maintains a relatively constant temperature, groundwater-influenced areas along streams can provide cool-water refuge for fish during periods of extreme heat. A targeted approach was developed for identifying existing cold-water zones and areas of substantial groundwater discharge in four high priority Lake Ontario tributaries. Our approach included: (1) predicting where groundwater discharge is most likely with a simple geospatial model and (2) using model predictions to select field sites for intensive high-resolution study, including ground-based mapping of groundwater features (springs, seeps, tributaries) as well as drone-based optical and thermal infrared surveys. Results from field sites were used to both verify model performance and map different types and aerial extents of thermal anomalies. Geospatial modelling successfully predicted regions of widespread groundwater upwelling, later verified and mapped by field and drone surveys. Comparison of model and field survey results further highlighted specific geospatial layers, such as soil/bedrock types and topographic wetness index, as being particularly useful for predicting groundwater influence on streams in the study area. In addition, a comparison of geospatial model results with a model of fish abundances along the studied streams showed significant positive correlations for many heat-intolerant fish species over a wide geographic area. The approach developed in this study can be applied to other watersheds to highlight areas of probable groundwater discharge and could be used by fishery and water resource managers to support cold-water fish habitat management decision-making and resource conservation.

New York↗
USGS2013

Flood-inundation maps for the Elkhart River at Goshen, Indiana

The U.S. Geological Survey (USGS), in cooperation with the Indiana Office of Community and Rural Affairs, created digital flood-inundation maps for an 8.3-mile reach of the Elkhart River at Goshen, Indiana, extending from downstream of the Goshen Dam to downstream from County Road 17. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to nine selected water levels (stages) at the USGS streamgage at Elkhart River at Goshen (station number 04100500). Current conditions for the USGS streamgages in Indiana may be obtained on the Internet at http://waterdata.usgs.gov/ . In addition, stream stage data have been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http://water.weather.gov/ahps/) . The NWS forecasts flood hydrographs at many places that are often colocated with USGS streamgages. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated using the most current stage-discharge relation at the Elkhart River at Goshen streamgage. The hydraulic model was then used to compute nine water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from approximately bankfull (5 ft) to greater than the highest recorded water level (13 ft). The simulated water-surface profiles were then combined with a geographic information system (GIS) digital-elevation model (DEM), derived from Light Detection and Ranging (LiDAR) data having a 0.37-ft vertical accuracy and 3.9-ft horizontal resolution in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from USGS streamgages and forecasted stream stages from the NWS, provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for postflood recovery efforts.

Indiana↗
USGS2006

Database for the east half of "Preliminary Geologic Map of the Blythe 30' by 60' quadrangle, California and Arizona"

This digital map database was prepared from the published Preliminary Geologic Map of the Blythe 30' by 60' Quadrangle, California and Arizona (U.S. Geological Survey Open-File Report 90-497). This database represents the east half of the original published map. The database contains exactly the same scientific content as the original map; no data have been added to, subtracted from, or modified from the original map. Like the original paper map, this database represents the general distribution of bedrock and surficial deposits in the mapped area. It provides information on the geologic structure and stratigraphy of the area covered. The database delineates map units that are identified by general age and lithology following the stratigraphic nomenclature of the U.S. Geological Survey. The scale of the original published map limits the spatial resolution (scale) of the database to 1:100,000 or smaller.

Arizona, California↗
USGS2008

A Vegetation Database for the Colorado River Ecosystem from Glen Canyon Dam to the Western Boundary of Grand Canyon National Park, Arizona

A vegetation database of the riparian vegetation located within the Colorado River ecosystem (CRE), a subsection of the Colorado River between Glen Canyon Dam and the western boundary of Grand Canyon National Park, was constructed using four-band image mosaics acquired in May 2002. A digital line scanner was flown over the Colorado River corridor in Arizona by ISTAR Americas, using a Leica ADS-40 digital camera to acquire a digital surface model and four-band image mosaics (blue, green, red, and near-infrared) for vegetation mapping. The primary objective of this mapping project was to develop a digital inventory map of vegetation to enable patch- and landscape-scale change detection, and to establish randomized sampling points for ground surveys of terrestrial fauna (principally, but not exclusively, birds). The vegetation base map was constructed through a combination of ground surveys to identify vegetation classes, image processing, and automated supervised classification procedures. Analysis of the imagery and subsequent supervised classification involved multiple steps to evaluate band quality, band ratios, and vegetation texture and density. Identification of vegetation classes involved collection of cover data throughout the river corridor and subsequent analysis using two-way indicator species analysis (TWINSPAN). Vegetation was classified into six vegetation classes, following the National Vegetation Classification Standard, based on cover dominance. This analysis indicated that total area covered by all vegetation within the CRE was 3,346 ha. Considering the six vegetation classes, the sparse shrub (SS) class accounted for the greatest amount of vegetation (627 ha) followed by Pluchea (PLSE) and Tamarix (TARA) at 494 and 366 ha, respectively. The wetland (WTLD) and Prosopis-Acacia (PRGL) classes both had similar areal cover values (227 and 213 ha, respectively). Baccharis-Salix (BAXX) was the least represented at 94 ha. Accuracy assessment of the supervised classification determined that accuracies varied among vegetation classes from 90% to 49%. Causes for low accuracies were similar spectral signatures among vegetation classes. Fuzzy accuracy assessment improved classification accuracies such that Federal mapping standards of 80% accuracies for all classes were met. The scale used to quantify vegetation adequately meets the needs of the stakeholder group. Increasing the scale to meet the U.S. Geological Survey (USGS)-National Park Service (NPS)National Mapping Program's minimum mapping unit of 0.5 ha is unwarranted because this scale would reduce the resolution of some classes (e.g., seep willow/coyote willow would likely be combined with tamarisk). While this would undoubtedly improve classification accuracies, it would not provide the community-level information about vegetation change that would benefit stakeholders. The identification of vegetation classes should follow NPS mapping approaches to complement the national effort and should incorporate the alternative analysis for community identification that is being incorporated into newer NPS mapping efforts. National Vegetation Classification is followed in this report for association- to formation-level categories. Accuracies could be improved by including more environmental variables such as stage elevation in the classification process and incorporating object-based classification methods. Another approach that may address the heterogeneous species issue and classification is to use spectral mixing analysis to estimate the fractional cover of species within each pixel and better quantify the cover of individual species that compose a cover class. Varying flights to capture vegetation at different times of the year might also help separate some vegetation classes, though the cost may be prohibitive. Lastly, photointerpretation instead of automated mapping could be tried. Photointerpretation would likely not improve accuracies in this case, howev

Open-File Report↗
USGS2015

Geological sampling data and benthic biota classification: Buzzards Bay and Vineyard Sound, Massachusetts

Sea-floor sample collection is an important component of a statewide cooperative mapping effort between the U.S. Geological Survey (USGS) and the Massachusetts Office of Coastal Zone Management (CZM). Sediment grab samples, bottom photographs, and video transects were collected within Vineyard Sound and Buzzards Bay in 2010 aboard the research vessel Connecticut . This report contains sample data and related information, including analyses of surficial-sediment grab samples, locations and images of sea-floor photography, survey lines along which sea-floor video was collected, and a classification of benthic biota observed in sea-floor photographs and based on the Coastal and Marine Ecological Classification Standard (CMECS). These sample data and analyses information are used to verify interpretations of geophysical data and are an essential part of geologic maps of the sea floor. These data also provide a valuable inventory of benthic habitat and resources. Geographic information system (GIS) data, maps, and interpretations, produced through the USGS and CZM mapping cooperative, are intended to aid efforts to manage coastal and marine resources and to provide baseline information for research focused on coastal evolution and environmental change.

Massachusetts↗
USGS2012

Bathymetry and digital elevation models of Coyote Creek and Alviso Slough, South San Francisco Bay, California

In 2010, the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center completed three cruises to map the bathymetry of the main channel and shallow intertidal mudflats in the southernmost part of south San Francisco Bay. The three surveys were merged to generate comprehensive maps of Coyote Creek (from Calaveras Point east to the railroad bridge) and Alviso Slough (from the bay to the town of Alviso) to establish baseline bathymetry prior to the breaching of levees adjacent to Alviso and Guadalupe Sloughs as part of the South Bay Salt Pond Restoration Project ( http://www.southbayrestoration.org ). Since 2010, the USGS has conducted fourteen additional surveys to monitor bathymetric change in this region as restoration progresses. The bathymetric surveys were conducted using the state-of-the-art research vessel R/V Parke Snavely outfitted with an interferometric sidescan sonar for swath mapping in extremely shallow water. This publication provides high-resolution bathymetric data collected by the USGS. For the 2010 baseline survey we have merged the bathymetry with aerial lidar data that were collected for the USGS during the same time period to create a seamless, high-resolution digital elevation model (DEM) of the study area. The series of bathymetric datasets are provided at 1 m resolution and the 2010 bathymetric/topographic DEM at 2 m resolution. The data are formatted as both X, Y, Z text files and ESRI Arc ASCII files that are accompanied by Federal Geographic Data Committee (FGDC) compliant metadata.

California↗
USGS2020

Combining fisheries surveys to inform marine species distribution modelling

Ecosystem-scale examination of fish communities typically involves creating spatio-temporally explicit relative abundance distribution maps using data from multiple fishery-independent surveys. However, sampling performance varies by vessel and sampling gear, which may influence estimated species distribution patterns. Using GAMMs, the effect of different gear–vessel combinations on relative abundance estimates at length was investigated using European fisheries-independent groundfish survey data. We constructed a modelling framework for evaluating relative efficiency of multiple gear–vessel combinations. 19 northeast Atlantic surveys for 254 species-length combinations were examined. Space-time variables explained most of the variation in catches for 181/254 species-length cases, indicating that for many species, models successfully characterized distribution patterns when combining data from disparate surveys. Variables controlling for gear efficiency explained substantial variation in catches for 127/254 species-length data sets. Models that fail to control for gear efficiencies across surveys can mask changes in the spatial distribution of species. Estimated relative differences in catch efficiencies grouped strongly by gear type, but did not exhibit a clear pattern across species’ functional forms, suggesting difficulty in predicting the potential impact of gear efficiency differences when combining survey data to assess species’ distributions and highlighting the importance of modelling approaches that can control for gear differences.

ICES Journal of Marine Science↗
USGS2016

A multiagency and multijurisdictional approach to mapping the glacial deposits of the Great Lakes region in three dimensions

The Great Lakes Geologic Mapping Coalition (GLGMC), consisting of state geological surveys from all eight Great Lakes states, the Ontario Geological Survey, and the U.S. Geological Survey, was conceived out of a societal need for unbiased and scientifically defensible geologic information on the shallow subsurface, particularly the delineation, interpretation, and viability of groundwater resources. Only a small percentage (<10%) of the region had been mapped in the subsurface, and there was recognition that no single agency had the financial, intellectual, or physical resources to conduct such a massive geologic mapping effort at a detailed scale over a wide jurisdiction. The GLGMC provides a strategy for generating financial and stakeholder support for three-dimensional (3-D) geologic mapping, pooling of physical and personnel resources, and sharing of mapping and technological expertise to characterize the thick cover of glacial sediments. Since its inception in 1997, the GLGMC partners have conducted detailed surficial and 3-D geologic mapping within all jurisdictions, and concurrent significant scientific advancements have been made to increase understanding of the history and framework of geologic processes. More importantly, scientific information has been provided to public policymakers in understandable formats, emphasis has been placed on training early-career scientists in new mapping techniques and emerging technologies, and a successful model has been developed of state/provincial and federal collaboration focused on geologic mapping, as evidenced by this program's unprecedented and long-term successful experiment of 10 geological surveys working together to address common issues.

GSA Special Papers↗
USGS1970

Tectonic map of Indonesia: A progress report

Orogeny, volcanism, and seismicity are now intensely active in Indonesia. Many Dutch tectonists--Brouwer, Umbgrove, van Bemifielen, Smit4Sibinga, Vening Meinesz, Westerveld, and others--recognized that this complex cluster of islands represents an early stage in the evolution of orogenic belts. Not until Indonesia is understood can we comprehend the Alps. This report summarizes some aspects of work to date on the Tectonic Map of Indonesia. The preparation of this map is a joint project of the Geological Survey of Indonesia and the United States Geological Survey, sponsored by the Government of Indonesia and the United States Agency for International Development. The Tectonic Map of Indonesia will be published at a scale of 1:5,000,000. Adjacent regions in other countries will be included to provide a broader context. The map limits presently envisaged are the parallels of 12° N. and 15° S., and the meridians of 91° and 148° E. Tectonic features will be shown in many colors and patterns. Bathymetry is being newly compiled, and will be shown with contours and shades of blue. Figure 1 shows the islands of Indonesia.

Open-File Report↗
USGS1996

National Seismic-Hazard Maps: Documentation June 1996

In this release of hazard maps we present numerous maps and data with varying parameters. The computations for these maps and data used 50 year return periods on firm rock at 760 m/sec. All of the maps were prepared by combining hazard derived from spatially- smoothed historic seismicity with hazard from fault-specific sources. For more information please read our full documentation. Although these maps have been used by the U.S. Geological Survey, no warranty, expressed or implied is made by the USGS as to the accuracy of the maps and related material nor shall the fact of distribution constitute any such warranty, and no responsibility is assumed by the USGS in connection therewith.

Open-File Report↗