66 datasets found
  1. 2014 Horry County, South Carolina Lidar

    • catalog.data.gov
    • fisheries.noaa.gov
    Updated Oct 31, 2024
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    NOAA Office for Coastal Management (Point of Contact, Custodian) (2024). 2014 Horry County, South Carolina Lidar [Dataset]. https://catalog.data.gov/dataset/2014-horry-county-south-carolina-lidar1
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    Dataset updated
    Oct 31, 2024
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Area covered
    Horry County, South Carolina
    Description

    This data set is comprised of lidar point cloud data. This project required lidar data to be acquired over Horry County, South Carolina. The total area of the Horry County Elevation Data and Imagery AOI is approximately 1092 square miles. Lidar data was collected and processed to meet the requirements of the project task order. The lidar collection was a collaborative effort between two data acquisition firms. While Woolpert was responsible for collection of the majority of the county, the coastal portion of the data was collected by Quantum Geospatial and is detailed in the processing steps of the metadata. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, four (4) foot pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Ground conditions: Water at normal levels; no unusual inundation; no snow. The bare earth DEMs along the coast may have a variance in the water heights due to temporal differences during the lidar data acquisition and will be represented in DEM as a seam-like anomaly. One coastal elevation was applied to entire project area. Due to differing acquisition dates and thus differing tide levels there will be areas in the DEM exhibiting what appears to be "digging" water features. Sometimes as much as approximately 2.5 feet. This was done to ensure that no coastal hydro feature was "floating" above ground surface. This coastal elevation will also affect connected river features wherein a sudden increase in flow will be observed in the DEM to accommodate the coastal elevation value. During Hydrologic breakline collection, Woolpert excluded obvious above-water piers or pier-like structures from the breakline placement. Some features extend beyond the apparent coastline and are constructed in a manner that can be considered an extension of the ground. These features were treated as ground during classification and subsequent hydrologic delineation. In all cases, professional practice was applied to delineate what appeared to be the coast based on data from multiple sources; Due to the many substructures and the complexity of the urban environment, interpolation and apparent "divots" (caused by tinning) may be evident in the surface of the bare earth DEM. In all cases, professional practice was applied to best represent the topography. The data received by the NOAA OCM are topographic data in LAS 1.2 format, classified as unclassified (1), ground (2), all noise (7), water (9), ignored ground (10), overlap unclassified (17), and overlap ground (18). Digital Elevation Models (DEMs) and breakline data are also available. The DEM data are available at: ftp://coast.noaa.gov/pub/DigitalCoast/lidar1_z/geoid18/data/4814/DEMs/ The breakline data are available at: ftp://coast.noaa.gov/pub/DigitalCoast/lidar1_z/geoid18/data/4814/breaklines Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office of Coastal Management (OCM)or its partners. Original contact information: Contact Org: Woolpert Phone: (937) 461-5660

  2. 2007 South Carolina LiDAR: Charleston (partial), Jasper, and Colleton...

    • catalog.data.gov
    • fisheries.noaa.gov
    Updated Oct 31, 2024
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    NOAA Office for Coastal Management (Point of Contact, Custodian) (2024). 2007 South Carolina LiDAR: Charleston (partial), Jasper, and Colleton Counties [Dataset]. https://catalog.data.gov/dataset/2007-south-carolina-lidar-charleston-partial-jasper-and-colleton-counties1
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    Dataset updated
    Oct 31, 2024
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Area covered
    Charleston, Colleton County, South Carolina
    Description

    LiDAR data collection was performed utilizing a Leica ALS-50 sensor, collecting multiple return x, y, and z data as well as intensity data. LiDAR data was processed to achieve a bare ground surface, and was delivered in LAS format. Classified LAS data was also used as a base for collection of hydro features, delivered in MicroStation v8 format. The dates of collection are: 1. JASPER COUNTY (full county): 20061227 to 20070216 2. COLLETON COUNTY (full county: 20070216 to 20070323 3. CHARLESTON COUNTY (Partial County): 20070222 to 20070223 Original contact information: Contact Org: NOAA Office for Coastal Management Phone: 843-740-1202 Email: coastal.info@noaa.gov

  3. 2020 USGS Lidar DEM: Savannah Pee Dee, SC

    • fisheries.noaa.gov
    geotiff
    Updated Sep 4, 2020
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    OCM Partners (2020). 2020 USGS Lidar DEM: Savannah Pee Dee, SC [Dataset]. https://www.fisheries.noaa.gov/inport/item/65959
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    geotiffAvailable download formats
    Dataset updated
    Sep 4, 2020
    Dataset provided by
    OCM Partners
    Time period covered
    Jan 1, 2020 - Feb 3, 2020
    Area covered
    Marlboro County, Allendale County, Georgetown County, Charleston County, Chesterfield County, Fairfield County, Lee County, Newberry County, Beaufort County, Sumter County
    Description

    Product: Lidar based digital elevation model (DEM) data tiles for ground classified points.

    Geographic Extent: Approximately 21,453 square miles across South Carolina; Block 1 (Lot 6 QL2) - approximately 3,583 square miles in Anderson, Cherokee, Greenville, Laurens, Newberry, Oconee, Pickens, Spartanburg, and Union counties Block 2 (Lot 7 QL1) - approximately 950 square miles in Greenvill...

  4. d

    Lidar-derived Data Layers for South Carolina StreamStats, 2007-2013

    • catalog.data.gov
    • data.usgs.gov
    • +1more
    Updated Oct 1, 2025
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    U.S. Geological Survey (2025). Lidar-derived Data Layers for South Carolina StreamStats, 2007-2013 [Dataset]. https://catalog.data.gov/dataset/lidar-derived-data-layers-for-south-carolina-streamstats-2007-2013
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    Dataset updated
    Oct 1, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    South Carolina
    Description

    In cooperation with the South Carolina Department of Transportation, the U.S. Geological Survey developed a StreamStats web application (https://water.usgs.gov/osw/streamstats/) that provides analytical tools for water-resources planning and management (Ries and others, 2017). This data set presents the lidar-derived flow direction, flow accumulation, streamline, and hydro-enforced digital elevation model raster data used for analysis in StreamStats. Rasters are included for each of the following hydrologic unit codes (HUCs): 03040101, 03040102, 03040103, 03040104, 03040105, 03040201, 03040202, 03040203, 03040204, 03040205, 03040206, 03040207, 03040208, 03050101, 03050102, 03050103, 03050104, 03050105, 03050106, 03050107, 03050108, 03050109, 03050110, 03050111, 03050112, 03050201, 03050202, 03050203, 03050204, 03050205, 03050206, 03050207, 03050208, 03050209, 03050210, 03060101, 03060102, 03060103, 03060104, 03060105, 03060106, 03060107, 03060108, 03060109, and 03060110. The raster data is organized into four main zip folders, which are called “Flow_Accumulation_Grids,” “Flow_Direction_Grids,” Hydro_Enforced_DEM_Grids,” and “Streamline_Grids.” Reference: Ries, K.G., III, Newson J.K., Smith, M.J., Guthrie, J.D., Steeves, P.A., Haluska, T.L., Kolb, K.R., Thompson, R.F., Santoro, R.D., and Vraga, H.W., 2017, StreamStats, version 4: U.S. Geological Survey Fact Sheet 2017–3046, 4 p., https://doi.org/10.3133/fs20173046.

  5. 2008 South Carolina Department of Natural Resources (SCDNR) South Carolina...

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    Updated Mar 11, 2021
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    South Carolina Department of Natural Resources (Point of Contact) (2021). 2008 South Carolina Department of Natural Resources (SCDNR) South Carolina Lidar - Chesterfield County [Dataset]. https://catalog.data.gov/dataset/2008-south-carolina-department-of-natural-resources-scdnr-south-carolina-lidar-chesterfiel
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    Dataset updated
    Mar 11, 2021
    Dataset provided by
    South Carolina Department of Natural Resourceshttp://www.dnr.sc.gov/
    Area covered
    Chesterfield County, South Carolina
    Description

    The project area is composed of 16 counties in the State of South Carolina - Cherokee, Union, Laurens, Greenwood, Newberry, Chester, Fairfield, Lancaster, Chesterfield, Marlboro, Darlington, Dillon, Marion, Williamsburg, Clarendon, and Orangeburg. The project area consists of approximately 10,194 square miles including a buffer of 50 feet along the edges of the project area and an additional buffer in some areas. The project design of the lidar data acquisition was developed to support a nominal post spacing of 1.4 meters. The Fugro EarthData, Inc. acquisition team of Fugro Horizons, Inc. and North West Group acquired 721 flight lines in 44 lifts from January 15, 2008 through February 10, 2008. The data was divided into 5000' by 5000' foot cells that serve as the tiling scheme. Lidar data collection was performed with a Cessna 310 aircraft, utilizing a Leica ALS50-II MPiA sensor, collecting multiple return x, y, and z data as well as intensity data. Lidar data was processed to achieve a bare ground surface (Classes 2 and 8). Lidar data is remotely sensed high-resolution elevation data collected by an airborne collection platform. Using a combination of laser range finding, GPS positioning and inertial measurement technologies, lidar instruments are able to make highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation.

  6. 2007 South Carolina DNR Lidar: Dorchester County

    • fisheries.noaa.gov
    html
    Updated Oct 17, 2016
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    OCM Partners (2016). 2007 South Carolina DNR Lidar: Dorchester County [Dataset]. https://www.fisheries.noaa.gov/inport/item/49960
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    htmlAvailable download formats
    Dataset updated
    Oct 17, 2016
    Dataset provided by
    OCM Partners, LLC
    Time period covered
    Mar 5, 2007 - Mar 7, 2007
    Area covered
    Description

    Woolpert Inc. conducted a LiDAR survey to acquire LiDAR capable of producing a DEM for orthophoto rectification and able to support 2-foot contour specifications. The LiDAR data was acquired across the project area of Dorchester County, SC. The lidar data acquisition was executed in 5 sessions, from March 5 to March 7, 2007, using a Leica ALS50(83) Lidar System. The airborne GPS (ABGPS) base st...

  7. w

    2008 South Carolina Lidar: Union County

    • data.wu.ac.at
    • fisheries.noaa.gov
    Updated Feb 7, 2018
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    National Oceanic and Atmospheric Administration, Department of Commerce (2018). 2008 South Carolina Lidar: Union County [Dataset]. https://data.wu.ac.at/schema/data_gov/ZmFlMGY2MGItZDk1YS00YTJlLWE0YjYtYWNjNjBjMWM2Njcz
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    Dataset updated
    Feb 7, 2018
    Dataset provided by
    National Oceanic and Atmospheric Administration, Department of Commerce
    License

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

    Area covered
    2ffc4f15e57fd6fc7bab5b627ea89b75100c168c
    Description

    The project area is composed of 16 counties in the State of South Carolina - Cherokee, Union, Laurens, Greenwood, Newberry, Chester, Fairfield, Lancaster, Chesterfield, Marlboro, Darlington, Dillon, Marion, Williamsburg, Clarendon, and Orangeburg. This metadata file is for the lidar county deliverables for Union County, SC. The project area consists of approximately 10,194 square miles including a buffer of 50 feet along the edges of the project area and an additional buffer in some areas. The project design of the lidar data acquisition was developed to support a nominal post spacing of 1.4 meters. The Fugro EarthData, Inc. acquisition team of Fugro Horizons, Inc. and North West Group acquired 721 flight lines in 44 lifts from January 15, 2008 through February 10, 2008. The data was divided into 5000' by 5000' foot cells that serve as the tiling scheme. Lidar data collection was performed with a Cessna 310 aircraft, utilizing a Leica ALS50-II MPiA sensor, collecting multiple return x, y, and z data as well as intensity data. Lidar data was processed to achieve a bare ground surface (Classes 2 and 8). Lidar data is remotely sensed high-resolution elevation data collected by an airborne collection platform. Using a combination of laser range finding, GPS positioning and inertial measurement technologies, lidar instruments are able to make highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation.

  8. w

    2013 South Carolina DNR Lidar: Beaufort County

    • data.wu.ac.at
    • fisheries.noaa.gov
    Updated Feb 7, 2018
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    National Oceanic and Atmospheric Administration, Department of Commerce (2018). 2013 South Carolina DNR Lidar: Beaufort County [Dataset]. https://data.wu.ac.at/schema/data_gov/NzFmOTYwMzAtMDZjOC00OTM4LWE4ZWItMTkwNzU2OTQ5YjVl
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    Dataset updated
    Feb 7, 2018
    Dataset provided by
    National Oceanic and Atmospheric Administration, Department of Commerce
    License

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

    Area covered
    e2b4376484b3466db291230a2ca3bf1b60b464c4
    Description

    LMSI provided high accuracy, calibrated multiple return LiDAR for roughly 785 square miles covering Beaufort County, South Carolina. The nominal point spacing for this project was at least 4 points per square meter. Dewberry used proprietary procedures to classify the LAS according to project specifications: 1-Unclassified, 2-Ground, 7-Noise, 8-Model Key Points, 9-Water, 10-Ignored Ground, 11-Withheld Points, 13-Bridges and Culverts. Dewberry produced 3D breaklines and combined these with the final LiDAR data to produce seamless hydro-enforced DEMs for the 982 tiles (5000 ft x 5000 ft) that cover the project area.

  9. NOAA Office for Coastal Management Coastal Inundation Digital Elevation...

    • catalog.data.gov
    • fisheries.noaa.gov
    Updated Oct 31, 2024
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    NOAA Office for Coastal Management (Point of Contact) (2024). NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: South Carolina Central [Dataset]. https://catalog.data.gov/dataset/noaa-office-for-coastal-management-coastal-inundation-digital-elevation-model-south-carolina-ce1
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    Dataset updated
    Oct 31, 2024
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Area covered
    South Carolina
    Description

    These data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the Sea Level Rise and Coastal Flooding Impacts Viewer. It depicts potential sea level rise and its associated impacts on the nation's coastal areas. The purpose of the mapping viewer is to provide coastal managers and scientists with a preliminary look at sea level rise and coastal flooding impacts. The viewer is a screening-level tool that uses nationally consistent data sets and analyses. Data and maps provided can be used at several scales to help gauge trends and prioritize actions for different scenarios. The Sea Level Rise and Coastal Flooding Impacts Viewer may be accessed at: https://coast.noaa.gov/slr. This metadata record describes the South Carolina Central digital elevation model (DEM), which is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea Level Rise and Coastal Flooding Impacts Viewer described above. This DEM includes the best available lidar known to exist at the time of DEM creation that met project specifications. This DEM includes data for Charleston, Berkeley and Dorchester Counties. The DEM was produced from the following lidar data sets: 1. 2017 SC DNR Lidar DEM: Charleston County, SC 2. 2017 SC DNR Lidar DEM: Berkeley County, SC 3. 2007 SC DNR Lidar DEM: Dorchester County, SC The DEM is referenced vertically to the North American Vertical Datum of 1988 (NAVD88, Geoid12B) with vertical units of meters and horizontally to the North American Datum of 1983 (NAD83). The resolution of the DEM is approximately 3 meters.

  10. 2017 SC DNR Lidar: Coastal Counties (Berkeley, Charleston and Williamsburg...

    • fisheries.noaa.gov
    las/laz - laser
    Updated Jan 1, 2020
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    OCM Partners (2020). 2017 SC DNR Lidar: Coastal Counties (Berkeley, Charleston and Williamsburg Counties) [Dataset]. https://www.fisheries.noaa.gov/inport/item/57035
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    las/laz - laserAvailable download formats
    Dataset updated
    Jan 1, 2020
    Dataset provided by
    OCM Partners
    Time period covered
    Dec 15, 2016 - Dec 30, 2016
    Area covered
    Description

    Axis Geospatial collected 1265 square miles in the South Carolina county of Berkeley, and 1124 sq miles in Charleston County. Precision Aerial Reconnaissance collected 965 square miles in Williamsburg county. The nominal pulse spacing for this project was 1 point every 0.7 meters. Dewberry used proprietary procedures to classify the LAS according to project specifications: 1-Unclassified, 2-...

  11. U

    Foundational Geospatial Layers for South Carolina StreamStats 2024

    • data.usgs.gov
    • datasets.ai
    • +2more
    Updated Apr 11, 2024
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    Jonathan Musser; Katharine Kolb; Joshua Henley; Samantha Doering (2024). Foundational Geospatial Layers for South Carolina StreamStats 2024 [Dataset]. http://doi.org/10.5066/P132UCHM
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    Dataset updated
    Apr 11, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Jonathan Musser; Katharine Kolb; Joshua Henley; Samantha Doering
    License

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

    Time period covered
    2023
    Area covered
    South Carolina
    Description

    In cooperation with the South Carolina Department of Transportation, the U.S. Geological Survey updated the foundational geospatial layers for the South Carolina StreamStats web application (https://water.usgs.gov/osw/streamstats/), which provides analytical tools useful for water-resources planning and management (Kolb and others, 2018). This dataset presents the digital elevation model, lidar-derived flow direction, flow accumulation, and percent basin slope raster data layers used for analysis in StreamStats. It also includes the streamline vector data used to hydro-enforce the raster data layers.

  12. 2010 South Carolina DNR Lidar: Richland County

    • data.wu.ac.at
    • fisheries.noaa.gov
    Updated Feb 7, 2018
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    National Oceanic and Atmospheric Administration, Department of Commerce (2018). 2010 South Carolina DNR Lidar: Richland County [Dataset]. https://data.wu.ac.at/schema/data_gov/MzJiM2Y3NzktMDYzNC00NzQ1LTg3NDctNTdkNWZkNDcwYjRh
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    Dataset updated
    Feb 7, 2018
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    License

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

    Area covered
    3c227b68adfec5170c433d31bc9867b3a24ce979
    Description

    Provide high density LiDAR elevation data map of Richland County, SC. Provide Bare Earth DEM (vegetation removal) of Richland County, SC.

  13. d

    Stream Lines Used to Produce the South Carolina StreamStats 2018 Release

    • catalog.data.gov
    • data.usgs.gov
    • +1more
    Updated Sep 30, 2025
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    U.S. Geological Survey (2025). Stream Lines Used to Produce the South Carolina StreamStats 2018 Release [Dataset]. https://catalog.data.gov/dataset/stream-lines-used-to-produce-the-south-carolina-streamstats-2018-release
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    Dataset updated
    Sep 30, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    South Carolina
    Description

    The U.S. Geological Survey South Atlantic Water Science Center, in cooperation with the South Carolina Department of Transportation, implemented a South Carolina StreamStats application in 2018. This shapefile dataset contains vector lines representing streams, rivers, and ditches that were used in preparing the underlying data for the South Carolina StreamStats application. Data were compiled from multiple sources, but principally represent lidar-derived linework from the South Carolina Department of Natural Resources and the South Carolina Lidar Consortium.The South Carolina hydrography lines were created from elevation rasters that ranged from 4 to 10 ft resolution, to produce a product of approximately 1:6,000-scale. Other sources include the 1:24,000 scale high resolution National Hydrography Dataset streamlines [for streamlines in Georgetown County (SC), NC, and GA] and the 1:4,800 scale local-resolution North Carolina Stream Mapping Project lines (mountain counties). These vector lines were used to enforce drainages on digital elevation model raster grids using the HydroDem/Agree program during data preparation.

  14. 2012 South Carolina DNR Lidar: Edgefield County

    • data.wu.ac.at
    • fisheries.noaa.gov
    Updated Feb 7, 2018
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    National Oceanic and Atmospheric Administration, Department of Commerce (2018). 2012 South Carolina DNR Lidar: Edgefield County [Dataset]. https://data.wu.ac.at/schema/data_gov/OTc3NTJmMzEtYjM5Zi00NWJiLWJiN2EtNWM2NmNhMTY0NzVk
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    Dataset updated
    Feb 7, 2018
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    License

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

    Area covered
    53af670fe2f4c75df27f89134df04f94b9ebd677
    Description

    Towill Inc. collected LiDAR for over 3,300 square miles in Calhoun, Aiken, Barnwell, Edgefield, McCormick, and Abbeville counties in South Carolina. This metadata covers the LiDAR products for Edgefield County. The nominal pulse spacing for this project is 1.4 meters. This project was collected with a sensor which collects waveform data and provides an intensity value for each discrete pulse extracted from the waveform. GPS Week Time, Intensity, Flightline and echo number attributes were provided for each LiDAR point. Dewberry used proprietary procedures to classify the LAS according to contract specifications: 1-Unclassified, 2-Ground, 7-Noise, 8-Model Key Points, 9-Water, 10-Ignored Ground due to breakline proximity. Dewberry produced 3D breaklines and combined these with the final LiDAR data to produce seamless hydro flattened DEMs for the 651 tiles (5000 ft x 5000 ft) that cover the project area.

  15. 2025 SCDVA Lidar DEM: Charleston County, SC

    • catalog.data.gov
    • fisheries.noaa.gov
    Updated Sep 19, 2025
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    NOAA Office for Coastal Management (Point of Contact, Custodian) (2025). 2025 SCDVA Lidar DEM: Charleston County, SC [Dataset]. https://catalog.data.gov/dataset/2025-scdva-lidar-dem-charleston-county-sc
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    Dataset updated
    Sep 19, 2025
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Area covered
    Charleston County, South Carolina
    Description

    BERKELEY, CHARLESTON, ORANGEBURG LIDAR DATA COLLECTION Lidar Data Acquisition and Processing Production Task Charleston County Contract Number: 6004 RFQ Number: 6004-25C Woolpert Order No: 10020258 CONTRACTOR: Woolpert Lidar data is a remotely sensed high-resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. This task order requires lidar data to be acquired over Charleston County (+/- 1,197 square miles). This lidar data set is comprised of lidar point cloud data, raster DEMs, raster DSMs, raster intensity imagery, and GPS flight line trajectory data. The task required the lidar data to be collected at a nominal pulse spacing (NPS) of 1.15 feet. The lidar dataset was produced using a horizontal datum/projection of NAD83, State Plane South Carolina, International Feet and a vertical datum of NAVD88 (Geoid 18), International Feet. Tidal areas in Charleston's data acquisition were collected within +/- 2 hours of low tide. Additional deliverables include control data and tile index in Esri shapefile format, lidar processing and survey reports in PDF format, and project-level FGDC CSDGM metadata in XML format. This data was provided to the NOAA Office for Coastal Management (OCM) by the Charleston County Public Works Department, for the purpose of making the data publicly available for custom and bulk downloads from the NOAA Digital Coast Data Access Viewer.

  16. d

    Calhoun Critical Zone Observatory 2016 Leaf Off LiDAR Survey

    • search.dataone.org
    • portal.opentopography.org
    • +1more
    Updated Oct 24, 2023
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    OpenTopography (2023). Calhoun Critical Zone Observatory 2016 Leaf Off LiDAR Survey [Dataset]. https://search.dataone.org/view/sha256%3A63e3c613790cdf029aa248e7cc9331a6582490e0796df7d1dd00db7dc3ef1716
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    Dataset updated
    Oct 24, 2023
    Dataset provided by
    OpenTopography
    Time period covered
    Feb 26, 2016
    Area covered
    Description

    The National Center for Airborne Laser Mapping (NCALM) conducted a lidar survey of the Calhoun Critical Zone Observatory (CCZO) area on February 26, 2016. The survey was funded by NSF award EAR-1339015; the Calhoun CZO is funded by NSF award EAR-1331846 (P.I. Daniel deB. Richter).


    Publications associated with this dataset can be found at NCALM's Data Tracking Center

  17. 2016-2017 NOAA NGS Topobathy Lidar DEM: Coastal South Carolina

    • catalog.data.gov
    • fisheries.noaa.gov
    Updated Oct 31, 2024
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    NOAA Office for Coastal Management (Point of Contact, Custodian) (2024). 2016-2017 NOAA NGS Topobathy Lidar DEM: Coastal South Carolina [Dataset]. https://catalog.data.gov/dataset/2016-2017-noaa-ngs-topobathy-lidar-dem-coastal-south-carolina1
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    Dataset updated
    Oct 31, 2024
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Description

    These data were collected by Quantum Spatial, Inc. (QSI) for the National Oceanic and Atmospheric Administration (NOAA), National Geodetic Survey (NGS), Remote Sensing Devision (RSD), Coastal Mapping Program (CMP) using a Riegl VQ880G system. The Delivery 1 and Delivery 2 (D1/D2) data were acquired from 20161203 - 20170301 in nine missions. The missions were flown on 20161203, 20161209, 20161210, 20161228, 20161229, 20161230, 20170105, 20170228, and 20170301. The Delivery 3 (D3) data were acquired from 20161002 - 20170219 in fifteen missions. Data acquired on 10/02, pre-Hurricane Matthew, was only used to fill a small gap in data entirely over water where no bathymetric coverage was achieved. The Delivery 4 (D4) data were acquired from 20161211 - 20170204 in thirteen missions. The Delivery 5 (D5) data were acquired from 20170112 - 20170204 in eleven missions. The Delivery 6 (D6) data were acquired from 20161203 - 20170301 in eleven missions. The Delivery 7 (D7) data were acquired from 20170212 - 20170221 in eight missions. The Delivery 8 (D8) data were acquired from 20170218 - 20170227 in six missions.

  18. 2020 SC DNR Lidar DEM: 5 County (Cherokee, Chester, Fairfield, Lancaster,...

    • fisheries.noaa.gov
    geotiff +1
    Updated Aug 16, 2023
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    OCM Partners (2023). 2020 SC DNR Lidar DEM: 5 County (Cherokee, Chester, Fairfield, Lancaster, Union), SC [Dataset]. https://www.fisheries.noaa.gov/inport/item/73569
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    geotiff, not applicableAvailable download formats
    Dataset updated
    Aug 16, 2023
    Dataset provided by
    OCM Partners
    Time period covered
    Jan 16, 2020 - Feb 15, 2020
    Area covered
    Description

    Original Dataset Description: Aerial lidar data was collected for a 5-county project area which encompassed the South Carolina Counties of Cherokee, Union, Chester, Lancaster, and Fairfield. Lidar data for the project was collected by Quantum Spatial as part of the ESP team, between January 16, 2020 and February 15, 2020 using 2 Leica ALS80 sensors; serial numbers 3061 and 3546. Data was collec...

  19. 2014 NOAA Post-Sandy Topobathymetric Lidar DEMs: South Carolina to New York

    • catalog.data.gov
    • fisheries.noaa.gov
    Updated Oct 31, 2024
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    NOAA Office for Coastal Management (Point of Contact, Custodian) (2024). 2014 NOAA Post-Sandy Topobathymetric Lidar DEMs: South Carolina to New York [Dataset]. https://catalog.data.gov/dataset/2014-noaa-post-sandy-topobathymetric-lidar-dems-south-carolina-to-new-york1
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    Dataset updated
    Oct 31, 2024
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Area covered
    New York, South Carolina
    Description

    These data were collected by the National Oceanic Atmospheric Administration National Geodetic Survey Remote Sensing Division using a Riegl VQ820G system. The data were acquired from 201311- 201406. The data includes topobathy data with points classified by target type (e.g. ground, water, etc). The final classified LiDAR data were then used to create topobathymetric DEMs in IMG format with 1m pixel size using ground points. The full project consists of 2,775 square miles along the Atlantic Coast from New York to South Carolina, or 41,388 - 500 m x 500 m lidar tiles. These tiles have been combined into 140 larger blocks. The data collection and processing was funded by post-Sandy supplemental funds. While Sandy was considered an extra-tropical storm when it struck, the word hurricane is in this sentence for search purposes. Original contact information: Contact Org: National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), National Geodetic Survey (NGS), Remote Sensing Division Title: Chief, Remote Sensing Division Phone: 301-713-2663

  20. d

    Data from: 2010 lidar-derived mean high water shoreline for the coast of...

    • catalog.data.gov
    • datasets.ai
    • +1more
    Updated Sep 17, 2025
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    U.S. Geological Survey (2025). 2010 lidar-derived mean high water shoreline for the coast of South Carolina [Dataset]. https://catalog.data.gov/dataset/2010-lidar-derived-mean-high-water-shoreline-for-the-coast-of-south-carolina-29b8e
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    Dataset updated
    Sep 17, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    South Carolina
    Description

    The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This data release includes two new mean high water (MHW) shorelines extracted from lidar data collected in 2010 and 2017-2018. Previously published historical shorelines for South Carolina (Kratzmann and others, 2017) were combined with the new lidar shorelines to calculate long-term (up to 166 years) and short-term (up to 18 years) rates of change. Files associated with the long-term and short-term rates are appended with "LT" and "ST", respectively. A proxy-datum bias reference line that accounts for the positional difference in a proxy shoreline (e.g. High Water Line (HWL) shoreline) and a datum shoreline (e.g. MHW shoreline) is also included in this release.

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NOAA Office for Coastal Management (Point of Contact, Custodian) (2024). 2014 Horry County, South Carolina Lidar [Dataset]. https://catalog.data.gov/dataset/2014-horry-county-south-carolina-lidar1
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2014 Horry County, South Carolina Lidar

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Dataset updated
Oct 31, 2024
Dataset provided by
National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
Area covered
Horry County, South Carolina
Description

This data set is comprised of lidar point cloud data. This project required lidar data to be acquired over Horry County, South Carolina. The total area of the Horry County Elevation Data and Imagery AOI is approximately 1092 square miles. Lidar data was collected and processed to meet the requirements of the project task order. The lidar collection was a collaborative effort between two data acquisition firms. While Woolpert was responsible for collection of the majority of the county, the coastal portion of the data was collected by Quantum Geospatial and is detailed in the processing steps of the metadata. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, four (4) foot pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Ground conditions: Water at normal levels; no unusual inundation; no snow. The bare earth DEMs along the coast may have a variance in the water heights due to temporal differences during the lidar data acquisition and will be represented in DEM as a seam-like anomaly. One coastal elevation was applied to entire project area. Due to differing acquisition dates and thus differing tide levels there will be areas in the DEM exhibiting what appears to be "digging" water features. Sometimes as much as approximately 2.5 feet. This was done to ensure that no coastal hydro feature was "floating" above ground surface. This coastal elevation will also affect connected river features wherein a sudden increase in flow will be observed in the DEM to accommodate the coastal elevation value. During Hydrologic breakline collection, Woolpert excluded obvious above-water piers or pier-like structures from the breakline placement. Some features extend beyond the apparent coastline and are constructed in a manner that can be considered an extension of the ground. These features were treated as ground during classification and subsequent hydrologic delineation. In all cases, professional practice was applied to delineate what appeared to be the coast based on data from multiple sources; Due to the many substructures and the complexity of the urban environment, interpolation and apparent "divots" (caused by tinning) may be evident in the surface of the bare earth DEM. In all cases, professional practice was applied to best represent the topography. The data received by the NOAA OCM are topographic data in LAS 1.2 format, classified as unclassified (1), ground (2), all noise (7), water (9), ignored ground (10), overlap unclassified (17), and overlap ground (18). Digital Elevation Models (DEMs) and breakline data are also available. The DEM data are available at: ftp://coast.noaa.gov/pub/DigitalCoast/lidar1_z/geoid18/data/4814/DEMs/ The breakline data are available at: ftp://coast.noaa.gov/pub/DigitalCoast/lidar1_z/geoid18/data/4814/breaklines Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office of Coastal Management (OCM)or its partners. Original contact information: Contact Org: Woolpert Phone: (937) 461-5660

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