Results for “Map” — Page 73

USGS2021

Extending the capture map concept to estimate discrete and risk-based streamflow depletion potential

A popular and contemporary use of numerical groundwater models is to estimate the discrete relation between groundwater extraction and surface-water/groundwater exchange. Previously, the concept of a “capture map” has been put forward as a means to effectively summarize this relation for decision-making consumption. While capture maps have enjoyed success in the environmental simulation industry, they are deterministic, ignoring uncertainty in the underlying model. Furthermore, capture maps are not typically calculated in a manner that facilitates analysis of varying combinations of extraction locations and/or reaches. That is, they are typically constructed with focus on a single reach or group of reaches. The former of these limitations is important for conveying risk to decision makers and stakeholders, while the latter is important for decision-making support related to surface-water management, where future foci may include reaches that were not the focus of the original capture analysis. Herein, we use the concept of a response matrix to generalize the theory of the capture-map approach to estimate spatially discrete streamflow depletion potential. We also use first-order, second-moment uncertainty estimation techniques with the concept of “risk shifting” to place capture maps and streamflow depletion potential in a stochastic, risk-based framework. Our approach is demonstrated for an integrated groundwater/surface-water model of the lower San Antonio River, Texas, USA.

Groundwater↗

USGS2013

Hydrography change detection: the usefulness of surface channels derived From LiDAR DEMs for updating mapped hydrography

The 1:24,000-scale high-resolution National Hydrography Dataset (NHD) mapped hydrography flow lines require regular updating because land surface conditions that affect surface channel drainage change over time. Historically, NHD flow lines were created by digitizing surface water information from aerial photography and paper maps. Using these same methods to update nationwide NHD flow lines is costly and inefficient; furthermore, these methods result in hydrography that lacks the horizontal and vertical accuracy needed for fully integrated datasets useful for mapping and scientific investigations. Effective methods for improving mapped hydrography employ change detection analysis of surface channels derived from light detection and ranging (LiDAR) digital elevation models (DEMs) and NHD flow lines. In this article, we describe the usefulness of surface channels derived from LiDAR DEMs for hydrography change detection to derive spatially accurate and time-relevant mapped hydrography. The methods employ analyses of horizontal and vertical differences between LiDAR-derived surface channels and NHD flow lines to define candidate locations of hydrography change. These methods alleviate the need to analyze and update the nationwide NHD for time relevant hydrography, and provide an avenue for updating the dataset where change has occurred.

Journal of the American Water Resources Associatio↗

USGS2012

Spectroscopic remote sensing for material identification, vegetation characterization, and mapping

Identifying materials by measuring and analyzing their reflectance spectra has been an important procedure in analytical chemistry for decades. Airborne and space-based imaging spectrometers allow materials to be mapped across the landscape. With many existing airborne sensors and new satellite-borne sensors planned for the future, robust methods are needed to fully exploit the information content of hyperspectral remote sensing data. A method of identifying and mapping materials using spectral feature analyses of reflectance data in an expert-system framework called MICA (Material Identification and Characterization Algorithm) is described. MICA is a module of the PRISM (Processing Routines in IDL for Spectroscopic Measurements) software, available to the public from the U.S. Geological Survey (USGS) at http://pubs.usgs.gov/of/2011/1155/. The core concepts of MICA include continuum removal and linear regression to compare key diagnostic absorption features in reference laboratory/field spectra and the spectra being analyzed. The reference spectra, diagnostic features, and threshold constraints are defined within a user-developed MICA command file (MCF). Building on several decades of experience in mineral mapping, a broadly-applicable MCF was developed to detect a set of minerals frequently occurring on the Earth's surface and applied to map minerals in the country-wide coverage of the 2007 Afghanistan HyMap data set. MICA has also been applied to detect sub-pixel oil contamination in marshes impacted by the Deepwater Horizon incident by discriminating the C-H absorption features in oil residues from background vegetation. These two recent examples demonstrate the utility of a spectroscopic approach to remote sensing for identifying and mapping the distributions of materials in imaging spectrometer data.

Conference Paper↗

USGS1949

Geologic mapping in the United States

An inventory of geologic mapping in the continental United States shows the areal extent of published geologic maps, differentiated by scales, and gives the results of calculations of the approximate number of square miles geologically mapped in each State on several scales, with separate figures for the maps published since 1919. Several graphs compare the progress of geologic mapping in the different States and in different countries.

GSA Bulletin↗

USGS1981

New maps of Federal coal

Compilation and analysis of publicly available data on Federal coal are resulting in voluminous map sets showing coal isopachs, structure contours, and overburden isopachs on each known minable coal bed. As of the spring of 1981, there are available from the U.S. Geological Survey Open-File Services Section in Denver map sets at 1:24,000 scale or microfiche sets covering approximately 470 of the ultimately 1,400 quadrangles in the program. Because Congress in 1976 mandated the prompt “inventorying” of all unleased Federal coal for Government land-use planning, and because dollars but not employee positions were provided for the work, the U.S. Geological Survey was obliged to contract for the compilations. A typical map set has a short text and about 20 plates, including a data sheet; a Federal mineral ownership map; and correlation charts. For each coal bed, there are isopachs, structure contours, stripping limits, and mining ratios extending as far as the data will permit, regardless of coal ownership. Reserve base tonnages and relative development potentials are calculated, but only for unleased Federal coal areas. Termed “minable” are coal beds at least 1.524 m (5 ft) thick and less than 914.4 m (3,000 ft) deep. For conventional underground mining methods, beds dipping more than 15° are excluded; also excluded are all but 3.66 m (12 ft) of thick beds. For in situ conversion methods, the minimum dip is 15° except for the deep thick beds in the Powder River Basin. Arbitrary parameters classify the development potential of each unleased 16.19-hectare (40-acre) tract as high, moderate, low, unknown, or negative. The former Secretary of the Interior announced his intention to restrict leasing in general to tracts classified as having high to moderate potential for development. Many geologists will find these systematic map compilations to be useful bases for adding new data points and making their own interpretations, correlations, extrapolations, and reserve estimates.

Geological Society of America Bulletin↗

USGS1974

Preparation and use of isopleth maps of landslide deposits

Isopleth maps derived from landslide inventory maps generalize and quantify the areal distribution of landslide deposits in contour form and may be uniquely useful for some types of regional planning. The isopleth format permits incorporation of landslide information with other quantified map data in the preparation of slope stability maps. The isopleth map of landslide deposits in San Mateo County, California (scale 1:300,000), serves as an example of this technique.

California↗

USGS2015

Karst mapping in the United States: Past, present and future

The earliest known comprehensive karst map of the entire USA was published by Stringfield and LeGrand (1969), based on compilations of William E. Davies of the U.S. Geological Survey (USGS). Various versions of essentially the same map have been published since. The USGS recently published new digital maps and databases depicting the extent of known karst, potential karst, and pseudokarst areas of the United States of America including Puerto Rico and the U.S. Virgin Islands (Weary and Doctor, 2014). These maps are based primarily on the extent of potentially karstic soluble rock types, and rocks with physical properties conducive to the formation of pseudokarst features. These data were compiled and refined from multiple sources at various spatial resolutions, mostly as digital data supplied by state geological surveys. The database includes polygons delineating areas with potential for karst and that are tagged with attributes intended to facilitate classification of karst regions. Approximately 18% of the surface of the fifty United States is underlain by significantly soluble bedrock. In the eastern United States the extent of outcrop of soluble rocks provides a good first-approximation of the distribution of karst and potential karst areas. In the arid western states, the extent of soluble rock outcrop tends to overestimate the extent of regions that might be considered as karst under current climatic conditions, but the new dataset encompasses those regions nonetheless. This database will be revised as needed, and the present map will be updated as new information is incorporated.

GSA Special Papers↗

USGS2009

Mapping potentialy asbestos-bearing rocks using imaging spectroscopy

Rock and soil that may contain naturally occurring asbestos (NOA), a known human carcinogen, were mapped in the Sierra Nevada, California, using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) to determine if these materials could be uniquely identified with spectroscopy. Such information can be used to prepare or refine maps of areas that may contain minerals that can be asbestiform, such as serpentine and tremolite-actinolite, which were the focus of this study. Although thick vegetation can conceal underlying rock and soil, use of linear-mixture spectra calculated from spectra of dry grass and serpentine allowed detection of serpentine in some parts of the study area with up to ~80% dry-grass cover. Chaparral vegetation, which was dominantly, but not exclusively, found in areas underlain by serpentinized ultramafic rocks, was also mapped. Overall, field checking at 201 sites indicated highly accurate identification by AVIRIS of mineral (94%) and vegetation (89%) categories. Practical applications of AVIRIS to mapping areas that may contain NOA include locating roads that are surfaced with serpentine aggregate, identifying sites that may require enhanced dust control or other safety measures, and filling gaps in geologic mapping where field access is limited.

Geology↗

USGS2019

A federal-state partnership for mapping Florida's coast and seafloor

The Florida Coastal Mapping Program, a partnership of state and federal agencies, has a goal of having modern, consistent, high- resolution sea-floor data for all of Florida’s coastal zone in the next decade to support a myriad of coastal zone science and management applications. One of the early steps in the implementation process is to prioritize and justify mapping needs. This is accomplished by holding six regional workshops across the state during which stakeholders and partners are introduced to a newly developed geospatial prioritization tool. Users independently utilize the tool to populate grid cells for a given region, and the result is a cumulative perspective on sea floor mapping priorities to inform future mapping initiatives. The tool also allows participants to indicate their primary use of sea floor mapping data and types of additional data required for their science or management need.

Florida↗

USGS1989

A terracing operator for physical property mapping with potential field data

The terracing operator works iteratively on gravity or magnetic data, using the sense of the measured field's local curvature, to produce a field comprised of uniform domains separated by abrupt domain boundaries. The result is crudely proportional to a physical-property function defined in one (profile case) or two (map case) horizontal dimensions. This result can be extended to a physical-property model if its behavior in the third (vertical) dimension is defined, either arbitrarily or on the basis of the local geologic situation. The terracing algorithm is computationally fast and appropriate to use with very large digital data sets. Where gravity and magnetic data are both available, terracing provides an effective means by which the two data sets can be compared directly. Results of the terracing operation somewhat resemble those of conventional susceptibility (or density) mapping. In contrast with conventional susceptibility mapping, however, the terraced function is a true step function, which cannot be depicted by means of contour lines. Magnetic or gravity fields calculated from the physical-property model do not, in general, produce an exact fit to the observed data. By intent, the terraced map is more closely analogous to a geologic map in that domains are separated by hard-edged domain boundaries and minor within-domain variation is neglected. The terracing operator was applied separately to aeromagnetic and gravity data from a 136 km X 123 km area in eastern Kansas. Results provide a reasonably good physical representation of both the gravity and the aeromagnetic data. Superposition of the results from the two data sets shows many areas of agreement that can be referenced to geologic features within the buried Precambrian crystalline basement. The emerging picture of basement geology is much better resolved than that obtained either from the scanty available drill data or from interpretation of the geophysical data by inspection.

Geophysics↗

USGS2012

History of land cover mapping

The historical roots of land-cover mapping reside in the early history of aerial photography and applications spanning forestry, agriculture, urban planning, and water-resources management. Considering this long span of mapping, any attempt to provide an exhaustive treatment of the full history of land-cover mapping will necessarily be incomplete. For that reason, this chapter on the history of land-cover mapping emphasizes the “modern” era of land-cover mapping, which has been arbitrarily defined to begin in the early 1970s. This was when civil space-based remote sensing came of age, and intellectual efforts focused on strategies for using new observations in understanding the characteristics of, and the changes in, land use and land cover.

Book chapter↗

USGS2006

Evaluation of eelgrass beds mapping using a high-resolution airborne multispectral scanner

Eelgrass ( Zostera marina ) can provide vital ecological functions in stabilizing sediments, influencing current dynamics, and contributing significant amounts of biomass to numerous food webs in coastal ecosystems. Mapping eelgrass beds is important for coastal water and nearshore estuarine monitoring, management, and planning. This study demonstrated the possible use of high spatial (approximately 5 m) and temporal (maximum low tide) resolution airborne multispectral scanner on mapping eelgrass beds in Northern Puget Sound, Washington. A combination of supervised and unsupervised classification approaches were performed on the multispectral scanner imagery. A normalized difference vegetation index (NDVI) derived from the red and near-infrared bands and ancillary spatial information, were used to extract and mask eelgrass beds and other submerged aquatic vegetation (SAV) in the study area. We evaluated the resulting thematic map (geocoded, classified image) against a conventional aerial photograph interpretation using 260 point locations randomly stratified over five defined classes from the thematic map. We achieved an overall accuracy of 92 percent with 0.92 Kappa Coefficient in the study area. This study demonstrates that the airborne multispectral scanner can be useful for mapping eelgrass beds in a local or regional scale, especially in regions for which optical remote sensing from space is constrained by climatic and tidal conditions.

Photogrammetric Engineering and Remote Sensing↗

USGS2017

Operational shoreline mapping with high spatial resolution radar and geographic processing

A comprehensive mapping technology was developed utilizing standard image processing and available GIS procedures to automate shoreline identification and mapping from 2 m synthetic aperture radar ( SAR ) HH amplitude data. The development used four NASA Uninhabited Aerial Vehicle SAR ( UAVSAR ) data collections between summer 2009 and 2012 and a fall 2012 collection of wetlands dominantly fronted by vegetated shorelines along the Mississippi River Delta that are beset by severe storms, toxic releases, and relative sea-level rise. In comparison to shorelines interpreted from 0.3 m and 1 m orthophotography, the automated GIS 10 m alongshore sampling found SAR shoreline mapping accuracy to be ±2 m, well within the lower range of reported shoreline mapping accuracies. The high comparability was obtained even though water levels differed between the SAR and photography image pairs and included all shorelines regardless of complexity. The SAR mapping technology is highly repeatable and extendable to other SAR instruments with similar operational functionality.

Photogrammetric Engineering and Remote Sensing↗

USGS2010

Comparing maps of mean monthly surface temperature and precipitation for Alaska and adjacent areas of Canada produced by two different methods

Maps of mean monthly surface temperature and precipitation for Alaska and adjacent areas of Canada, produced by Oregon State University's Spatial Climate Analysis Service (SCAS) and the Alaska Geospatial Data Clearinghouse (AGDC), were analyzed. Because both sets of maps are generally available and in use by the community, there is a need to document differences between the processes and input data sets used by the two groups to produce their respective set of maps and to identify similarities and differences between the two sets of maps and possible reasons for the differences. These differences do not affect the observed large-scale patterns of seasonal and annual variability. Alaska is divided into interior and coastal zones, with consistent but different variability, separated by a transition region. The transition region has high interannual variability but low long-term mean variability. Both data sets support the four major ecosystems and ecosystem transition zone identified in our earlier work. Differences between the two sets of maps do occur, however, on the regional scale; they reflect differences in physiographic domains and in the treatment of these domains by the two groups (AGDC, SCAS). These differences also provide guidance for an improved observational network for Alaska. On the basis of validation with independent in situ data, we conclude that the data set produced by SCAS provides the best spatial coverage of Alaskan long-term mean monthly surface temperature and precipitation currently available.

Alaska, British Columbia, Northwest Territories, Y↗

USGS1975

Radiometric age map of southeast Alaska

This map includes published, thesis, and open-file radiometric data available to us as of June, 1975. Some dates are not plotted because of inadequate location data in the original references. The map is divided into five sections, based on 1:1,000,000 scale enlargements of the National Atlas maps of Alaska. Within each section (e.g., southeastern Alaska), radiometric dates are plotted and keyed to 1:250,000 scale quadrangles. Accompanying each map section is table 1, listing map numbers and the sample identification numbers used in DGGS Special Report 10: Radiometric Dates from Alaska-A 1975 Compilation”. The reader is referred to Special Report 10 for more complete information on location, rock type, dating method, and literature references for each age entry. A listing of dates in Special Report lo which require correction or deletion is included S table 2. Corrected and additional entries are listed in table 3. The listings in tables 2 and 3 follow the format of Special Report 10. Table 4 is a glossary of abbreviations used for quadrangle name, rock type, mineral dated, and type of dating method used.

Alaska↗

USGS1975

Radiometric age map of Aleutian Islands

This map includes published, thesis, and open-file radiometric data available to us as of June, 1975. Some dates are not plotted because of inadequate location data in the original references. The map is divided into five sections, based on 1:1,000,000 scale enlargements of the National Atlas maps of Alaska. Within each section (e.g., southeastern Alaska), radiometric dates are plotted and keyed to 1:250,000 scale quadrangles. Accompanying each map section is table 1, listing map numbers and the sample identification numbers used in DGGS Special Report 10: Radiometric Dates from Alaska-A 1975 Compilation”. The reader is referred to Special Report 10 for more complete information on location, rock type, dating method, and literature references for each age entry. A listing of dates in Special Report lo which require correction or deletion is included S table 2. Corrected and additional entries are listed in table 3. The listings in tables 2 and 3 follow the format of Special Report 10. Table 4 is a glossary of abbreviations used for quadrangle name, rock type, mineral dated, and type of dating method used.

Alaska↗

USGS1975

Radiometric age map of southwest Alaska

This map includes published, thesis, and open-file radiometric data available to us as of June, 1975. Some dates are not plotted because of inadequate location data in the original references. The map is divided into five sections, based on 1:1,000,000 scale enlargements of the National Atlas maps of Alaska. Within each section (e.g., southeastern Alaska), radiometric dates are plotted and keyed to 1:250,000 scale quadrangles. Accompanying each map section is table 1, listing map numbers and the sample identification numbers used in DGGS Special Report 10: Radiometric Dates from Alaska-A 1975 Compilation”. The reader is referred to Special Report 10 for more complete information on location, rock type, dating method, and literature references for each age entry. A listing of dates in Special Report lo which require correction or deletion is included S table 2. Corrected and additional entries are listed in table 3. The listings in tables 2 and 3 follow the format of Special Report 10. Table 4 is a glossary of abbreviations used for quadrangle name, rock type, mineral dated, and type of dating method used.

Alaska↗

USGS1975

Radiometric age map of southcentral Alaska

This map includes published, thesis, and open-file radiometric data available to us as of June, 1975. Some dates are not plotted because of inadequate location data in the original references. The map is divided into five sections, based on 1:1,000,000 scale enlargements of the National Atlas maps of Alaska. Within each section (e.g., southeastern Alaska), radiometric dates are plotted and keyed to 1:250,000 scale quadrangles. Accompanying each map section is table 1, listing map numbers and the sample identification numbers used in DGGS Special Report 10: Radiometric Dates from Alaska-A 1975 Compilation”. The reader is referred to Special Report 10 for more complete information on location, rock type, dating method, and literature references for each age entry. A listing of dates in Special Report lo which require correction or deletion is included S table 2. Corrected and additional entries are listed in table 3. The listings in tables 2 and 3 follow the format of Special Report 10. Table 4 is a glossary of abbreviations used for quadrangle name, rock type, mineral dated, and type of dating method used.

Alaska↗