36 datasets found
  1. d

    Data from: Prospect- and Mine-Related Features from U.S. Geological Survey...

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    Updated Dec 14, 2017
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    Horton, John D.; San Juan, Carma A. (2017). Prospect- and Mine-Related Features from U.S. Geological Survey 7.5- and 15-Minute Topographic Quadrangle Maps of the United States [Dataset]. https://search.dataone.org/view/a9701210-a1d7-41b4-be00-f9843d2b3892
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    Dataset updated
    Dec 14, 2017
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Horton, John D.; San Juan, Carma A.
    Time period covered
    Jan 1, 1888 - Jan 1, 2006
    Area covered
    Variables measured
    State, County, GDA_ID, ScanID, Remarks, Ftr_Name, Ftr_Type, Topo_Date, Topo_Name, CompiledBy, and 2 more
    Description

    These data are part of a larger USGS project to develop an updated geospatial database of mines, mineral deposits and mineral regions in the United States. Mine and prospect-related symbols, such as those used to represent prospect pits, mines, adits, dumps, tailings, etc., hereafter referred to as “mine” symbols or features, are currently being digitized on a state-by-state basis from the 7.5-minute (1:24,000-scale) and the 15-minute (1:48,000 and 1:62,500-scale) archive of the USGS Historical Topographic Maps Collection, or acquired from available databases (California and Nevada, 1:24,000-scale only). Compilation of these features is the first phase in capturing accurate locations and general information about features related to mineral resource exploration and extraction across the U.S. To date, the compilation of 500,000-plus point and polygon mine symbols from approximately 67,000 maps of 22 western states has been completed: Arizona (AZ), Arkansas (AR), California (CA), Colorado (CO), Idaho (ID), Iowa (IA), Kansas (KS), Louisiana (LA), Minnesota (MN), Missouri (MO), Montana (MT), North Dakota (ND), Nebraska (NE), New Mexico (NM), Nevada (NV), Oklahoma (OK), Oregon (OR), South Dakota (SD), Texas (TX), Utah (UT), Washington (WA), and Wyoming (WY). The process renders not only a more complete picture of exploration and mining in the western U.S., but an approximate time line of when these activities occurred. The data may be used for land use planning, assessing abandoned mine lands and mine-related environmental impacts, assessing the value of mineral resources from Federal, State and private lands, and mapping mineralized areas and systems for input into the land management process. The data are presented as three groups of layers based on the scale of the source maps. No reconciliation between the data groups was done.

  2. u

    USGS Topographic Mine-related Symbols

    • colorado-river-portal.usgs.gov
    • hub.arcgis.com
    • +2more
    Updated Aug 4, 2016
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    U.S. Geological Survey (2016). USGS Topographic Mine-related Symbols [Dataset]. https://colorado-river-portal.usgs.gov/maps/USGS::usgs-topographic-mine-related-symbols/about
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    Dataset updated
    Aug 4, 2016
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey
    Area covered
    Description

    Version 10.0 (Alaska, Hawaii and Puerto Rico added) of these data are part of a larger U.S. Geological Survey (USGS) project to develop an updated geospatial database of mines, mineral deposits, and mineral regions in the United States. Mine and prospect-related symbols, such as those used to represent prospect pits, mines, adits, dumps, tailings, etc., hereafter referred to as “mine” symbols or features, have been digitized from the 7.5-minute (1:24,000, 1:25,000-scale; and 1:10,000, 1:20,000 and 1:30,000-scale in Puerto Rico only) and the 15-minute (1:48,000 and 1:62,500-scale; 1:63,360-scale in Alaska only) archive of the USGS Historical Topographic Map Collection (HTMC), or acquired from available databases (California and Nevada, 1:24,000-scale only). Compilation of these features is the first phase in capturing accurate locations and general information about features related to mineral resource exploration and extraction across the U.S. The compilation of 725,690 point and polygon mine symbols from approximately 106,350 maps across 50 states, the Commonwealth of Puerto Rico (PR) and the District of Columbia (DC) has been completed: Alabama (AL), Alaska (AK), Arizona (AZ), Arkansas (AR), California (CA), Colorado (CO), Connecticut (CT), Delaware (DE), Florida (FL), Georgia (GA), Hawaii (HI), Idaho (ID), Illinois (IL), Indiana (IN), Iowa (IA), Kansas (KS), Kentucky (KY), Louisiana (LA), Maine (ME), Maryland (MD), Massachusetts (MA), Michigan (MI), Minnesota (MN), Mississippi (MS), Missouri (MO), Montana (MT), Nebraska (NE), Nevada (NV), New Hampshire (NH), New Jersey (NJ), New Mexico (NM), New York (NY), North Carolina (NC), North Dakota (ND), Ohio (OH), Oklahoma (OK), Oregon (OR), Pennsylvania (PA), Rhode Island (RI), South Carolina (SC), South Dakota (SD), Tennessee (TN), Texas (TX), Utah (UT), Vermont (VT), Virginia (VA), Washington (WA), West Virginia (WV), Wisconsin (WI), and Wyoming (WY). The process renders not only a more complete picture of exploration and mining in the U.S., but an approximate timeline of when these activities occurred. These data may be used for land use planning, assessing abandoned mine lands and mine-related environmental impacts, assessing the value of mineral resources from Federal, State and private lands, and mapping mineralized areas and systems for input into the land management process. These data are presented as three groups of layers based on the scale of the source maps. No reconciliation between the data groups was done.Datasets were developed by the U.S. Geological Survey Geology, Geophysics, and Geochemistry Science Center (GGGSC). Compilation work was completed by USGS National Association of Geoscience Teachers (NAGT) interns: Emma L. Boardman-Larson, Grayce M. Gibbs, William R. Gnesda, Montana E. Hauke, Jacob D. Melendez, Amanda L. Ringer, and Alex J. Schwarz; USGS student contractors: Margaret B. Hammond, Germán Schmeda, Patrick C. Scott, Tyler Reyes, Morgan Mullins, Thomas Carroll, Margaret Brantley, and Logan Barrett; and by USGS personnel Virgil S. Alfred, Damon Bickerstaff, E.G. Boyce, Madelyn E. Eysel, Stuart A. Giles, Autumn L. Helfrich, Alan A. Hurlbert, Cheryl L. Novakovich, Sophia J. Pinter, and Andrew F. Smith.USMIN project website: https://www.usgs.gov/USMIN

  3. Southern Louisiana 1/3 arc-second NAVD 88 Coastal Digital Elevation Model

    • catalog.data.gov
    • datasets.ai
    • +2more
    Updated Oct 18, 2024
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    NOAA National Centers for Environmental Information (Point of Contact) (2024). Southern Louisiana 1/3 arc-second NAVD 88 Coastal Digital Elevation Model [Dataset]. https://catalog.data.gov/dataset/southern-louisiana-1-3-arc-second-navd-88-coastal-digital-elevation-model1
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    Dataset updated
    Oct 18, 2024
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    National Centers for Environmental Informationhttps://www.ncei.noaa.gov/
    Description

    Modeling and mapping of coastal processes (e.g. tsunamis, hurricane storm-surge, and sea-level rise) requires digital representations of Earth's solid surface, referred to as digital elevation models (DEMs). Some modeling utilizes structured, square-cell DEMs, while others utilize unstructured grids that have no regular cell size or pattern. Usually, these different DEM types are developed independently, even though they are built from the same source bathymetric and topographic datasets. The National Geophysical Data Center (NGDC), an office of the National Oceanic and Atmospheric Administration (NOAA), has developed two bathymetric-topographic square-celled DEMs and one bathymetric-topographic unstructured DEM of southern Louisiana. The DEMs were developed for the Hurricane Forecast Improvement Project (HFIP), with the purpose of developing a new methodology for unstructured grid production from structured square-celled grids. The 1/3 arc-second DEM referenced to North American Vertical Datum of 1988 (NAVD 88) was carefully developed and evaluated. A NAVD 88 to mean high water (MHW) 1/3 arc-second conversion grid derived from VDatum project areas was created to model the relationship between NAVD 88 and MHW in the southern Louisiana region. NGDC combined the NAVD 88 DEM and the conversion grid to develop a 1/3 arc-second MHW DEM. The NAVD 88 DEM was generated from diverse digital datasets in the region. The DEMs were developed to be used for storm surge inundation and sea level rise modeling. The source bathymetric and topographic datasets used in the development of the NAVD 88 DEM were utilized along with the NAVD 88 DEM and derivative grids to develop the NAVD 88 unstructured DEM.

  4. d

    ScienceBase Item Summary Page

    • datadiscoverystudio.org
    zip
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    U.S. Geological Survey, National Geospatial Technical Operations Center, ScienceBase Item Summary Page [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/cd80bf6d52f94f3083497d06adb18909/html
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    zipAvailable download formats
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Description

    Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

  5. d

    Topographic Lidar Survey of Dauphin Island, Alabama and Chandeleur, Stake,...

    • search.dataone.org
    • data.usgs.gov
    • +4more
    Updated Sep 14, 2017
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    U.S. Geological Survey (2017). Topographic Lidar Survey of Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana, July 12-14, 2013 -- Classified Point Data [Dataset]. https://search.dataone.org/view/d03b5731-20ed-4381-898e-f7beff92241e
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    Dataset updated
    Sep 14, 2017
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey
    Time period covered
    Jul 12, 2013 - Jul 14, 2013
    Area covered
    Variables measured
    X, Y, Z, GPS Time, Intensity, User Data, Return Number, Classification, Point Source ID, Scan Angle Rank, and 3 more
    Description

    A topographic lidar survey was conducted July 12-14, 2013 over Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana. Lidar data exchange format (LAS) 1.2 formatted classified point data files were generated based on these data. Photo Science, Inc. was contracted by the U.S. Geological Survey (USGS) to collect and process the lidar data. The lidar data were collected at a nominal pulse spacing (NPS) of 1.0 meter (m). The horizontal projection and datum of the data are Universe Transverse Mercator, zone 16N, North American Datum 1983 (UTM Zone 16N NAD83), meters. The vertical datum is North American Vertical Datum 1988, Geoid 2012a (NAVD88, GEOID12A), meters. Eighty-five LAS files, based on a 2-kilometer by 2-kilometer tiling scheme, cover the entire survey area. These lidar data are available to Federal, State and local governments, emergency-response officials, resource managers, and the general public. Lidar_Information Lidar_Collection_Information Lidar_Specification USGS-NGP Base Lidar Specification v1.0 Lidar_Sensor Leica ALS 70 Lidar_Maximum_Returns 4 Lidar_Pulse_Spacing 0.64 Lidar_Density 1.57 Lidar_Flight_Height 1524 Lidar_Flight_Speed 130 Lidar_Scan_Angle 20.0 Lidar_Scan_Frequency 29.6 Lidar_Pulse_Rate 178.4 Lidar_Pulse_Duration 4 Lidar_Pulse_Width 0.35 Lidar_Central_Wavelength 1064 Lidar_Multiple_Pulses_In_Air 0 Lidar_Beam_Divergence 0.22 Lidar_Swath_Width 1109.38 Lidar_Swath_Overlap 11.46% Lidar_Coordinate_Reference_System_Name NAD_1983_UTM_Zone_16N_Meters Lidar_Geoid National Geodetic Survey (NGS) Geoid03 Lidar_Accuracy_Information Lidar_Calculated_Horizontal_Accuracy 0.012 Lidar_Raw_Fundamental_Vertical_Accuracy 0.01 Lidar_LAS_Information Lidar_LAS_Version 1.2 Lidar_LAS_Point_Record_Format 1 Lidar_LAS_Witheld_Point_Identifier Withheld (ignore) points were identified in these files using the standard LAS Withheld bit. Lidar_LAS_Overage_Point_Identifier Swath "overage" points were identified in these files by adding 16 to the standard classification values. Lidar_LAS_Radiometric_Resolution 8 Lidar_LAS_Classification Lidar_LAS_Class_Code 1 Lidar_LAS_Class_Description Processed, but unclassified Lidar_LAS_Classification Lidar_LAS_Class_Code 2 Lidar_LAS_Class_Description Bare earth ground Lidar_LAS_Classification Lidar_LAS_Class_Code 7 Lidar_LAS_Class_Description Noise Lidar_LAS_Classification Lidar_LAS_Class_Code 9 Lidar_LAS_Class_Description Water Lidar_LAS_Classification Lidar_LAS_Class_Code 10 Lidar_LAS_Class_Description Ignored ground Lidar_LAS_Classification Lidar_LAS_Class_Code 17 Lidar_LAS_Class_Description Overlap default (unclassified) Lidar_LAS_Classification Lidar_LAS_Class_Code 18 Lidar_LAS_Class_Description Overlap bare-earth ground

  6. a

    USMIN 1:62,500

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • data-nbmg.opendata.arcgis.com
    • +1more
    Updated May 7, 2020
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    Nevada Bureau of Mines and Geology (2020). USMIN 1:62,500 [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/NBMG::usmin-162500
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    Dataset updated
    May 7, 2020
    Dataset authored and provided by
    Nevada Bureau of Mines and Geology
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    Citation: Horton, John D., and San Juan, Carma A., 2019, Prospect- and Mine-Related Features from U.S. Geological Survey 7.5- and 15-Minute Topographic Quadrangle Maps of the United States (ver. 4.0, November 2019): U.S. Geological Survey data release, https://doi.org/10.5066/F78W3CHG.Version 4.0 of these data are part of a larger USGS project to develop an updated geospatial database of mines, mineral deposits and mineral regions in the United States. Mine and prospect-related symbols, such as those used to represent prospect pits, mines, adits, dumps, tailings, etc., hereafter referred to as “mine” symbols or features, are currently being digitized on a state-by-state basis from the 7.5-minute (1:24,000-scale) and the 15-minute (1:48,000 and 1:62,500-scale) archive of the USGS Historical Topographic Maps Collection, or acquired from available databases (California and Nevada, 1:24,000-scale only). Compilation of these features is the first phase in capturing accurate locations and general information about features related to mineral resource exploration and extraction across the U.S. To date, the compilation of 637,000-plus point and polygon mine symbols from approximately 88,000 maps across 35 states has been completed: Alabama (AL), Arizona (AZ), Arkansas (AR), California (CA), Colorado (CO), Florida (FL), Georgia (GA), Idaho (ID), Iowa (IA), Illinois (IL), Indiana (IN), Kansas (KS), Kentucky (KY), Louisiana (LA), Michigan (MI), Minnesota (MN), Mississippi (MS), Missouri (MO), Montana (MT), North Carolina (NC), North Dakota (ND), Nebraska (NE), New Mexico (NM), Nevada (NV), Oklahoma (OK), Ohio (OH), Oregon (OR), South Carolina (SC), South Dakota (SD), Tennessee (TN), Texas (TX), Utah (UT), Washington (WA), Wisconsin (WI), and Wyoming (WY). The process renders not only a more complete picture of exploration and mining in the U.S., but an approximate time line of when these activities occurred. The data may be used for land use planning, assessing abandoned mine lands and mine-related environmental impacts, assessing the value of mineral resources from Federal, State and private lands, and mapping mineralized areas and systems for input into the land management process. The data are presented as three groups of layers based on the scale of the source maps. No reconciliation between the data groups was done. Datasets were developed by the U.S. Geological Survey Geology, Geophysics, and Geochemistry Science Center (GGGSC). Compilation work was completed by USGS student contractors: Germán Schmeda, Patrick C. Scott, William Gnesda, Margaret Hammond, Tyler Reyes, Morgan Mullins, Thomas Carroll, Margaret Brantley, and Logan Barrett; and by USGS personnel Damon Bickerstaff, Stuart A. Giles and E.G. Boyce. First release: August 4, 2016 Revised: December 1, 2017 (ver. 1.0) Revised: April 30, 2018 (ver. 2.0) Revised: April 10, 2019 (ver. 3.0) Revised: November 25, 2019 (ver.4.0)

  7. U

    Louisiana Barrier Island Comprehensive Monitoring Program – habitat mapping

    • data.usgs.gov
    • gimi9.com
    • +1more
    Updated Mar 26, 2018
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    Nicholas Enwright; William SooHoo; Jason Dugas; Darin Lee; Peggy Borrok (2018). Louisiana Barrier Island Comprehensive Monitoring Program – habitat mapping [Dataset]. http://doi.org/10.5066/F7XP7440
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    Dataset updated
    Mar 26, 2018
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Nicholas Enwright; William SooHoo; Jason Dugas; Darin Lee; Peggy Borrok
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Time period covered
    Oct 1, 2008 - Dec 5, 2016
    Area covered
    Louisiana
    Description

    The Barrier Island Comprehensive Monitoring (BICM) program was developed by Louisiana’s Coastal Protection Restoration Authority (CPRA) and is implemented as a component of the System Wide Assessment and Monitoring (SWAMP) program. The program uses both historical data and contemporary data collections to assess and monitor changes in the aerial and subaqueous extent of islands, habitat types, sediment texture and geotechnical properties, environmental processes, and vegetation composition. Examples of BICM datasets include still and video aerial photography for documenting shoreline changes, shoreline positions, habitat mapping, land change analyses, light detection and ranging (lidar) surveys for topographic elevations, single-beam and swath bathymetry, and sediment grab samples. For more information about the BICM program, see Kindinger and others (2013). The U.S. Geological Survey, Wetland and Aquatic Research Center provides support to the BICM program through the development ...

  8. d

    Topographic Lidar Survey of Dauphin Island, Alabama and Chandeleur, Stake,...

    • search.dataone.org
    • data.usgs.gov
    • +3more
    Updated Sep 14, 2017
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    U.S. Geological Survey (2017). Topographic Lidar Survey of Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana, July 12-14, 2013 -- Bare Earth Digital Elevation Models (DEMs) [Dataset]. https://search.dataone.org/view/36938b9c-7833-40c3-ab3a-c7767d45dcd0
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    Dataset updated
    Sep 14, 2017
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey
    Time period covered
    Jul 12, 2013 - Jul 14, 2013
    Area covered
    Description

    A topographic lidar survey was conducted on July 12-14, 2013 over Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana. The data were collected at a nominal pulse space of 1 meter (m) and processed to identify bare earth elevations. Bare earth Digital Elevation Models (DEMs) were generated based on these data. Photo Science, Inc., was contracted by the U.S. Geological Survey (USGS) to collect and process the lidar data. The bare earth DEMs are 32-bit floating point ERDAS Imagine (IMG) files with a horizontal spatial resolution of 1-m by 1-m. They are projected to Universal Transverse Mercator (UTM), Zone 16, North American Datum (NAD) 1983, meters (m) coordinates. Their vertical datum is NAVD88 (GEOID12A) meters. Eighty-five DEMs, based on a 2-kilometer (km) by 2-km tiling scheme, cover the entire survey area. These lidar data are available to Federal, State and local governments, emergency-response officials, resource managers, and the general public.

  9. d

    Topographic Lidar Survey of the Chandeleur Islands, Louisiana, February 6,...

    • search.dataone.org
    • data.usgs.gov
    • +3more
    Updated Sep 14, 2017
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    U.S. Geological Survey (2017). Topographic Lidar Survey of the Chandeleur Islands, Louisiana, February 6, 2012 -- Bare Earth DEMs [Dataset]. https://search.dataone.org/view/db966a26-9228-4880-a947-448a552fcd48
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    Dataset updated
    Sep 14, 2017
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey
    Area covered
    Description

    A topographic Lidar survey was conducted on February 6, 2012, over the Chandeleur Islands, Louisiana. The data were collected at a nominal pulse space of 0.5-meter (m) and processed to identify bare earth elevations. Bare earth digital elevation models (DEMs) were generated based on these data. Digital Aerial Solutions, LLC, was contracted by the U.S. Geological Survey (USGS) to collect and process the lidar data. The bare earth DEMs are 32-bit floating point ERDAS Imagine (IMG) files with a horizontal spatial resolution of 1-m by 1-m. They are in decimal degree geographic coordinates, North American Datum 1983, National Spatial Reference System 2007 (NAD83 NSRS2007)). Their vertical datum is North American Vertical Datum 1988, Geoid 2009, Geodetic Reference System 1980 (NAVD88 GEOID09 GRS80) in meters. Thirty-three DEMs, based on a 2-kilometer (km) by 2-km tiling scheme, cover the entire survey area. These lidar data are available to Federal, State and local governments, emergency-response officials, resource managers, and the general public.

  10. d

    ATM Coastal Topography--Louisiana, 2001: UTM Zone 15 (Part 1 of 2)

    • search.dataone.org
    • data.doi.gov
    Updated Sep 14, 2017
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    U.S. Geological Survey (2017). ATM Coastal Topography--Louisiana, 2001: UTM Zone 15 (Part 1 of 2) [Dataset]. https://search.dataone.org/view/76bba21d-2746-4fb0-8b15-a6ebf0cdc708
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    Dataset updated
    Sep 14, 2017
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey
    Area covered
    Description

    A first-surface elevation map was produced cooperatively from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS) and National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Airborne Topographic Mapper (ATM), a scanning lidar system that measures high-resolution topography of the land surface. The ATM system is deployed on a Twin Otter or P-3 Orion aircraft and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters.

    For more information on Lidar science and the Experimental Advanced Airborne Research Lidar (EAARL) system and surveys, see http://ngom.usgs.gov/dsp/overview/index.php and http://ngom.usgs.gov/dsp/tech/eaarl/index.php .

  11. U

    1 meter Digital Elevation Models (DEMs) - USGS National Map 3DEP...

    • data.usgs.gov
    • s.cnmilf.com
    • +4more
    Updated Feb 14, 2025
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    U.S. Geological Survey (2025). 1 meter Digital Elevation Models (DEMs) - USGS National Map 3DEP Downloadable Data Collection [Dataset]. https://data.usgs.gov/datacatalog/data/USGS:77ae0551-c61e-4979-aedd-d797abdcde0e
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    Dataset updated
    Feb 14, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    This is a tiled collection of the 3D Elevation Program (3DEP) and is one meter resolution. The 3DEP data holdings serve as the elevation layer of The National Map, and provide foundational elevation information for earth science studies and mapping applications in the United States. Scientists and resource managers use 3DEP data for hydrologic modeling, resource monitoring, mapping and visualization, and many other applications. The elevations in this DEM represent the topographic bare-earth surface. USGS standard one-meter DEMs are produced exclusively from high resolution light detection and ranging (lidar) source data of one-meter or higher resolution. One-meter DEM surfaces are seamless within collection projects, but, not necessarily seamless across projects. The spatial reference used for tiles of the one-meter DEM within the conterminous United States (CONUS) is Universal Transverse Mercator (UTM) in units of meters, and in conformance with the North American Datum of 1983 ...

  12. d

    Louisiana Parishes, Geographic NAD83, USGS (1998) [parishes_USGS_1998].

    • datadiscoverystudio.org
    • data.wu.ac.at
    zip
    Updated Apr 9, 2015
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    (2015). Louisiana Parishes, Geographic NAD83, USGS (1998) [parishes_USGS_1998]. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/38e572345e424e739d683d60aaa85b1f/html
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    zipAvailable download formats
    Dataset updated
    Apr 9, 2015
    Area covered
    Louisiana
    Description

    description: This data set contains vector line map information. The vector data contain selected base categories of geographic features, and characteristics of these features, in digital form. The information was collected by digitizing Digital Raster Graphic Maps (DRGs) of 7.5 Minute Topographic Quadrangles and Louisiana territorial waters from the Louisiana Oil Spill Contingency Plan Map CD to create a digitized overlay of Louisiana highlighting the political boundaries for all parishes.; abstract: This data set contains vector line map information. The vector data contain selected base categories of geographic features, and characteristics of these features, in digital form. The information was collected by digitizing Digital Raster Graphic Maps (DRGs) of 7.5 Minute Topographic Quadrangles and Louisiana territorial waters from the Louisiana Oil Spill Contingency Plan Map CD to create a digitized overlay of Louisiana highlighting the political boundaries for all parishes.

  13. a

    Northern Gulf of Mexico Coast Digital Elevation Model (GCOOS)

    • hub.arcgis.com
    • gisdata.gcoos.org
    Updated Oct 1, 2019
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    jeradk18@tamu.edu_tamu (2019). Northern Gulf of Mexico Coast Digital Elevation Model (GCOOS) [Dataset]. https://hub.arcgis.com/maps/be72a98729934f9fa3970b460ad5ce82
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    Dataset updated
    Oct 1, 2019
    Dataset authored and provided by
    jeradk18@tamu.edu_tamu
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    This dataset is the bathymetry Digital Elevation Model for the northern Gulf of Mexico coast including most or portions of the southeastern parishes of Louisiana, the coastal counties of Mississippi and Alabama, and the western counties of the Florida panhandle. The dataset includes offshore data extending, in some places, to a distance of ~200 km from the coast.NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions in the Gulf of Mexico. These integrated bathymetric-topographic DEMs were developed for NOAA Coastal Survey Development Laboratory (CSDL) through the American Recovery and Reinvestment Act (ARRA) of 2009 to evaluate the utility of the Vertical Datum Transformation tool (VDatum), developed jointly by NOAA's Office of Coast Survey (OCS), National Geodetic Survey (NGS), and Center for Operational Oceanographic Products and Services (CO-OPS).Bathymetric, topographic, and shoreline data used in DEM compilation are obtained from various sources, including NGDC, the U.S. Coastal Services Center (CSC), the U.S. Office of Coast Survey (OCS), the U.S. Army Corps of Engineers (USACE), and other federal, state, and local government agencies, academic institutions, and private companies.DEMs are referenced to the vertical tidal datum of North American Vertical Datum of 1988 (MHW), Mean High Water (MHW) or Mean Lower Low Water (MLLW) and horizontal datum of North American Datum of 1983 (NAD 83). Cell size ranges from 1/3 arc-second (~10 meters) to 1 arc-second (~30 meters). The NOAA VDatum DEM Project was funded by the American Recovery and Reinvestment Act (ARRA) of 2009 (http://www.recovery.gov/).The horizontal accuracy of bathymetric and topographic features in the DEM is dependent upon the accuracy of the input datasets used to determine corresponding cell values. Topography: 10 meters due to cell size. Lidar: less than 5 meters. DEM cell-value relative-contribution factors: Louisiana Lidar, Mississippi Lidar, CSC Lidar: 100, Mississippi Merged Lidar: 80, Digitzed features: 1, Bathymetry: 5 to several tens of meters. Positional accuracy of input bathymetric datasets limits accuracy of corresponding cell values in DEM. CSC Lidar: 0.75 meters. Early 20th-century NOS hydrographic soundings are limited by sparseness of deep-water soundings, and potentially large position accuracy of pre-satellite (i.e., GPS) navigation: tens to several tens of meters. Morphologic change in inland rivers and along the coast also degrades the positional accuracy of DEM features. DEM cell-value relative-contribution factors: CSC Coastal Lidar: 100, USACE hydrographic survey data: 5, NOS hydrographic soundings: 5, Digitized features: 1.The vertical accuracy of bathymetric and topographic features in the DEM is dependent upon the accuracy of the input datasets used to determine corresponding cell values. Topography: 1 to 16 meters. Vertical accuracy of input topographic datasets limits accuracy of corresponding cells in DEM. Lidar: less than 1 meter. DEM cell relative-contribution factors: Louisiana Lidar, Mississippi Lidar, CSC Lidar: 100, Digitized features: 10. Bathymetry: 0.1 meters to 5% of water depth. Vertical accuracy of input bathymetric datasets limits accuracy of corresponding cells in DEM. Early 20th-century NOS hydrographic soundings are limited by sparseness of deep-water soundings, and potentially large position accuracy of pre-satellite (i.e., GPS) navigation: several meters. DEM cell relative-contribution factors: CSC Coastal Lidar: 100, USACE hydrographic survey data: 5, NOS hydrographic soundings: 5, Digitized features: 1. Gridding interpolation to determine cell values between sparse NOS hydrographic soundings in deep water degrades the vertical accuracy of deep-water elevations.

  14. d

    Data from: EAARL Coastal Topography--North Shore, Lake Pontchartrain,...

    • datadiscoverystudio.org
    Updated Feb 23, 2018
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    (2018). EAARL Coastal Topography--North Shore, Lake Pontchartrain, Louisiana, 2010. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/7b7feb4c3041499f9e66cd919e3accc9/html
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    Dataset updated
    Feb 23, 2018
    Description

    description: A digital elevation model (DEM) of a portion of the north shore of Lake Pontchartrain, Louisiana, was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area on February 28, March 1, and March 5, 2010, using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 50 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 2-3 meters. The EAARL, developed originally by the National Aeronautics and Space Administration (NASA) at Wallops Flight Facility in Virginia, measures ground elevation with a vertical resolution of +/-15 centimeters. A sampling rate of 3 kilohertz or higher results in an extremely dense spatial elevation dataset. Over 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development. The data provided represent the last return pulses and were processed and filtered for bare-earth topography. However, in low-lying and emerging vegetation environments, bare-earth topography is not necessarily discernible from the last-return pulses. The difference in water levels between data collections on February 28, March 1, and March 5 resulted in elevation variations in the merged data.; abstract: A digital elevation model (DEM) of a portion of the north shore of Lake Pontchartrain, Louisiana, was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area on February 28, March 1, and March 5, 2010, using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 50 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 2-3 meters. The EAARL, developed originally by the National Aeronautics and Space Administration (NASA) at Wallops Flight Facility in Virginia, measures ground elevation with a vertical resolution of +/-15 centimeters. A sampling rate of 3 kilohertz or higher results in an extremely dense spatial elevation dataset. Over 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development. The data provided represent the last return pulses and were processed and filtered for bare-earth topography. However, in low-lying and emerging vegetation environments, bare-earth topography is not necessarily discernible from the last-return pulses. The difference in water levels between data collections on February 28, March 1, and March 5 resulted in elevation variations in the merged data.

  15. d

    EAARL Coastal Topography €“Eastern Louisiana Barrier Islands, 09 March 2008:...

    • datadiscoverystudio.org
    zip
    Updated Dec 13, 2017
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    (2017). EAARL Coastal Topography €“Eastern Louisiana Barrier Islands, 09 March 2008: Bare Earth. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/07fb3c608e0f46febfadf5983f57a5e4/html
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    zipAvailable download formats
    Dataset updated
    Dec 13, 2017
    Area covered
    Earth
    Description

    description: ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over some of the eastern Louisiana barrier islands in cooperation with the National Park Service (NPS), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 60 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 2-3 meters. The EAARL, developed originally by NASA at Wallops Flight Facility in Virginia, measures ground elevation with a vertical resolution of 3 centimeters. A sampling rate of 3 kilohertz or higher results in an extremely dense spatial elevation dataset. Over 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development.; abstract: ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over some of the eastern Louisiana barrier islands in cooperation with the National Park Service (NPS), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 60 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 2-3 meters. The EAARL, developed originally by NASA at Wallops Flight Facility in Virginia, measures ground elevation with a vertical resolution of 3 centimeters. A sampling rate of 3 kilohertz or higher results in an extremely dense spatial elevation dataset. Over 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development.

  16. d

    Data from: Topobathymetric Lidar Survey of Breton and Gosier Islands,...

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    Updated Sep 14, 2017
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    U.S. Geological Survey (2017). Topobathymetric Lidar Survey of Breton and Gosier Islands, Louisiana, January 16 and 18, 2014 [Dataset]. https://search.dataone.org/view/339c8cca-d1af-4898-af82-5c6441788b58
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    Dataset updated
    Sep 14, 2017
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    U.S. Geological Survey
    Area covered
    Description

    This dataset contains binary point-cloud data, produced from remotely sensed, geographically referenced topobathymetric measurements collected by Photo Science, Inc., encompassing the Breton and Gosier Island, LA study areas. The original area of interest was buffered by 100 meters to ensure complete coverage, resulting in approximately 75 square miles of lidar data. The Breton Island Lidar project called for the planning, acquisition, processing, and derivative products of topobathymetric lidar data, collected at a nominal pulse spacing (NPS) of 0.5-0.45 meters (4-5 points/square meter). Lidar acquisition was prioritized to coincide with the lowest tide possible. Water clarity was also assessed and deemed acceptable prior to acquisition flights. The data, in meters, are projected to UTM Zone 16 North and referenced horizontally to the NAD83 (2011) datum and vertically to the NAVD88 (GEOID12A) datum. The classified point-cloud data were delivered in LAS v1.2 format and the merged DEM was converted to a GeoTIFF file. Each LAS file contains data in a 1-kilometer by 1-kilometer tile named according to the US National Grid conventions. The final product was a LAZ file for Breton Island and another for Gosier Islands.

  17. d

    Data from: Louisiana Barrier Island Comprehensive Monitoring Program – 2021...

    • catalog.data.gov
    • data.usgs.gov
    Updated Sep 17, 2025
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    U.S. Geological Survey (2025). Louisiana Barrier Island Comprehensive Monitoring Program – 2021 habitat map, West Chenier Region [Dataset]. https://catalog.data.gov/dataset/louisiana-barrier-island-comprehensive-monitoring-program-2021-habitat-map-west-chenier-re
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    Dataset updated
    Sep 17, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Louisiana
    Description

    The Barrier Island Comprehensive Monitoring (BICM) program was developed by Louisiana’s Coastal Protection and Restoration Authority (CPRA) and is implemented as a component of the System Wide Assessment and Monitoring Program (SWAMP). The program uses both historical data and contemporary data collections to assess and monitor changes in the aerial and subaqueous extent of islands, habitat types, sediment texture and geotechnical properties, environmental processes, and vegetation composition. Examples of BICM datasets include still and video aerial photography for documenting shoreline changes, shoreline positions, habitat mapping, land change analyses, light detection and ranging (lidar) surveys for topographic elevations, single-beam and swath bathymetry, and sediment grab samples. For more information about the BICM program, see Kindinger and others (2013). The U.S. Geological Survey, Wetland and Aquatic Research Center provides support to the BICM program through the development of habitat map products using aerial imagery and lidar elevation data and assessing change in habitats over time. These data provide a snapshot of barrier island habitats and can be combined with other past and/or future maps to monitor these valuable natural resources over time. Previous efforts of this habitat mapping program included developing habitat maps for 2008 and 2015-2016 for the following BICM regions (Enwright and others, 2020): 1) West Chenier; 2) East Chenier; 3) Acadiana Bays (only Marsh Island); 4) Early Lafourche Delta; 5) Late Lafourche Delta; 6) Modern Delta (only Chaland Headland and Shell Island); and 7) Chandeleur Islands. Additionally, a habitat change analysis was conducted comparing reaches mapped in 2008 and 2015-2016. The current effort of this habitat mapping program includes developing habitat maps for 2021 for the previously mentioned regions. A habitat change analysis will be conducted comparing reaches mapped 2015-2016 and 2021. The BICM program has developed two habitat classification schemes which include a detailed 15-class habitat scheme and a general eight-class habitat scheme. The detailed scheme was developed specifically for this habitat mapping effort and builds off the general scheme used in previous BICM habitat mapping efforts (Fearnley and others, 2009). The additional classes developed in the detailed scheme are primarily used to further delineate various dune habitats, separate marsh and mangrove, and distinguish between beach and unvegetated barrier flat habitats. To ensure comparability between this effort and previous BICM map products, we have crosswalked the detailed classes to general habitat classes previously used by Fearnley and others (2009). In other words, the general habitat classes included in these products were not directly interpreted using aerial imagery and lidar elevation data. Thus, we recommend only using these general habitat classes for analyses that include previous BICM habitat maps (1996-2005). For more information about the BICM program, see Kindinger and others (2013). For more details on BICM habitat classes, see the Entity and Attribute Information section of the metadata. Please consult the accompanying readME.txt file for information and recommendations on the contents of this dataset (i.e., dataset and recommended symbology). For more information about the BICM program, see Kindinger and others (2013). References: Kindinger, J.L., Buster, N.A., Flocks, J.G., Bernier, J.C., and Kulp, M.A., 2013, Louisiana Barrier Island Comprehensive Monitoring (BICM) program summary report—Data and analyses 2006 through 2010: U.S. Geological Survey Open-File Report 2013–1083, 86 p., at https://pubs.usgs.gov/of/2013/1083/. Enwright, N.M., SooHoo, W.M., Dugas, J.L., Conzelmann, C.P., Laurenzano, C., Lee, D.M., Mouton, K., and Stelly, S.J., 2020, Louisiana Barrier Island Comprehensive Monitoring Program—Mapping habitats in beach, dune, and intertidal environments along the Louisiana Gulf of Mexico shoreline, 2008 and 2015–16: U.S. Geological Survey Open-File Report 2020–1030, 57 p., https://doi.org/10.3133/ofr20201030. Fearnley, S., Brien, L., Martinez, L., Miner, M., Kulp, M., and Penland, S., 2009, Chenier Plain, South-Central Louisiana, and Chandeleur Islands, Habitat mapping and change analysis 1996 to 2005, Part 1—Methods for habitat mapping and change analysis 1996 to 2005—Louisiana Barrier Island Comprehensive Monitoring Program (BICM) 5: New Orleans, University of New Orleans, Pontchartrain Institute for Environmental Sciences, 11 p.

  18. d

    Data from: EAARL Coastal Topography--Central Wetlands, Louisiana, 2010.

    • datadiscoverystudio.org
    Updated Feb 23, 2018
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    (2018). EAARL Coastal Topography--Central Wetlands, Louisiana, 2010. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/e5857b6ea278448d87de71c3a3ef764e/html
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    Dataset updated
    Feb 23, 2018
    Description

    description: A digital elevation model (DEM) of a portion of the Central Wetlands, Louisiana was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area on March 4 and 5, 2010, using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 50 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 2-3 meters. The EAARL, developed originally by the National Aeronautics and Space Administration (NASA) at Wallops Flight Facility in Virginia, measures ground elevation with a vertical resolution of +/-15 centimeters. A sampling rate of 3 kilohertz or higher results in an extremely dense spatial elevation dataset. Over 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development. The Central Wetlands data provided represent the last return pulses and were processed and filtered for bare-earth topography. The difference in water levels between data collections on March 4 and 5 resulted in elevation variations in the merged data.; abstract: A digital elevation model (DEM) of a portion of the Central Wetlands, Louisiana was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area on March 4 and 5, 2010, using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 50 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 2-3 meters. The EAARL, developed originally by the National Aeronautics and Space Administration (NASA) at Wallops Flight Facility in Virginia, measures ground elevation with a vertical resolution of +/-15 centimeters. A sampling rate of 3 kilohertz or higher results in an extremely dense spatial elevation dataset. Over 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development. The Central Wetlands data provided represent the last return pulses and were processed and filtered for bare-earth topography. The difference in water levels between data collections on March 4 and 5 resulted in elevation variations in the merged data.

  19. d

    EAARL-B Coastal Topography--Chandeleur Islands, Louisiana, 2012: Seamless...

    • search.dataone.org
    • data.usgs.gov
    • +3more
    Updated Sep 14, 2017
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    U.S. Geological Survey (2017). EAARL-B Coastal Topography--Chandeleur Islands, Louisiana, 2012: Seamless (Bare Earth and Submerged) (.shp file) [Dataset]. https://search.dataone.org/view/4c2d3a07-cf33-488e-b6c1-928c50258ce1
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    Dataset updated
    Sep 14, 2017
    Dataset provided by
    USGS Science Data Catalog
    Authors
    U.S. Geological Survey
    Area covered
    Variables measured
    FID, Shape, LABEL_POS, TILE_NAME, TILE_NUMBE
    Description

    This shapefile was produced from 52 2-kilometer by 2-kilometer tile extents of remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 55 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 0.5 - 1.6 meters. The nominal vertical elevation accuracy expressed as the root mean square error (RMSE) is 15 centimeters. A peak sampling rate of 15 - 30 kilohertz results in an extremely dense spatial elevation dataset. Over 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development.

  20. u

    Dune crest elevation

    • marine.usgs.gov
    Updated Aug 6, 2024
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    (2024). Dune crest elevation [Dataset]. https://marine.usgs.gov/coastalchangehazardsportal/ui/info/item/Mg23acy9
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    Dataset updated
    Aug 6, 2024
    Area covered
    Description

    This dataset contains elevation of the dune crest (m, NAVD88) for the United States coastline. The elevation of the dune crest, or top of the foredune, was extracted for open coast sandy beaches from gridded lidar topography every 10 m alongshore and then averaged in 1-km bins. Lidar surveys were collected from may 2010 to november 2022.

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Horton, John D.; San Juan, Carma A. (2017). Prospect- and Mine-Related Features from U.S. Geological Survey 7.5- and 15-Minute Topographic Quadrangle Maps of the United States [Dataset]. https://search.dataone.org/view/a9701210-a1d7-41b4-be00-f9843d2b3892

Data from: Prospect- and Mine-Related Features from U.S. Geological Survey 7.5- and 15-Minute Topographic Quadrangle Maps of the United States

Related Article
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Dataset updated
Dec 14, 2017
Dataset provided by
United States Geological Surveyhttp://www.usgs.gov/
Authors
Horton, John D.; San Juan, Carma A.
Time period covered
Jan 1, 1888 - Jan 1, 2006
Area covered
Variables measured
State, County, GDA_ID, ScanID, Remarks, Ftr_Name, Ftr_Type, Topo_Date, Topo_Name, CompiledBy, and 2 more
Description

These data are part of a larger USGS project to develop an updated geospatial database of mines, mineral deposits and mineral regions in the United States. Mine and prospect-related symbols, such as those used to represent prospect pits, mines, adits, dumps, tailings, etc., hereafter referred to as “mine” symbols or features, are currently being digitized on a state-by-state basis from the 7.5-minute (1:24,000-scale) and the 15-minute (1:48,000 and 1:62,500-scale) archive of the USGS Historical Topographic Maps Collection, or acquired from available databases (California and Nevada, 1:24,000-scale only). Compilation of these features is the first phase in capturing accurate locations and general information about features related to mineral resource exploration and extraction across the U.S. To date, the compilation of 500,000-plus point and polygon mine symbols from approximately 67,000 maps of 22 western states has been completed: Arizona (AZ), Arkansas (AR), California (CA), Colorado (CO), Idaho (ID), Iowa (IA), Kansas (KS), Louisiana (LA), Minnesota (MN), Missouri (MO), Montana (MT), North Dakota (ND), Nebraska (NE), New Mexico (NM), Nevada (NV), Oklahoma (OK), Oregon (OR), South Dakota (SD), Texas (TX), Utah (UT), Washington (WA), and Wyoming (WY). The process renders not only a more complete picture of exploration and mining in the western U.S., but an approximate time line of when these activities occurred. The data may be used for land use planning, assessing abandoned mine lands and mine-related environmental impacts, assessing the value of mineral resources from Federal, State and private lands, and mapping mineralized areas and systems for input into the land management process. The data are presented as three groups of layers based on the scale of the source maps. No reconciliation between the data groups was done.

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