100+ datasets found
  1. o

    USGS 3DEP LiDAR Point Clouds

    • registry.opendata.aws
    Updated Jan 22, 2019
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    USGS 3DEP LiDAR Point Clouds [Dataset]. https://registry.opendata.aws/usgs-lidar/
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    Dataset updated
    Jan 22, 2019
    Dataset provided by
    <a href="https://hobu.co">Hobu, Inc.</a>
    Description

    The goal of the USGS 3D Elevation Program (3DEP) is to collect elevation data in the form of light detection and ranging (LiDAR) data over the conterminous United States, Hawaii, and the U.S. territories, with data acquired over an 8-year period. This dataset provides two realizations of the 3DEP point cloud data. The first resource is a public access organization provided in Entwine Point Tiles format, which a lossless, full-density, streamable octree based on LASzip (LAZ) encoding. The second resource is a Requester Pays of the original, Raw LAZ (Compressed LAS) 1.4 3DEP format, and more complete in coverage, as sources with incomplete or missing CRS, will not have an ETP tile generated. Resource names in both buckets correspond to the USGS project names.

  2. d

    Lidar Point Cloud - USGS National Map 3DEP Downloadable Data Collection

    • catalog.data.gov
    • data.usgs.gov
    • +1more
    Updated Mar 11, 2025
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    U.S. Geological Survey (2025). Lidar Point Cloud - USGS National Map 3DEP Downloadable Data Collection [Dataset]. https://catalog.data.gov/dataset/lidar-point-cloud-usgs-national-map-3dep-downloadable-data-collection
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    Dataset updated
    Mar 11, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Description

    This data collection of the 3D Elevation Program (3DEP) consists of Lidar Point Cloud (LPC) projects as provided to the USGS. These point cloud files contain all the original lidar points collected, with the original spatial reference and units preserved. These data may have been used as the source of updates to the 1/3-arcsecond, 1-arcsecond, and 2-arcsecond seamless 3DEP Digital Elevation Models (DEMs). 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. Lidar (Light detection and ranging) discrete-return point cloud data are available in LAZ format. The LAZ format is a lossless compressed version of the American Society for Photogrammetry and Remote Sensing (ASPRS) LAS format. Point Cloud data can be converted from LAZ to LAS or LAS to LAZ without the loss of any information. Either format stores 3-dimensional point cloud data and point attributes along with header information and variable length records specific to the data. Millions of data points are stored as a 3-dimensional data cloud as a series of geo-referenced x, y coordinates and z (elevation), as well as other attributes for each point. Additonal information about the las file format can be found here: https://www.asprs.org/divisions-committees/lidar-division/laser-las-file-format-exchange-activities. All 3DEP products are public domain.

  3. 2018 - 2020 NOAA USGS Lidar: Hawaii, HI

    • fisheries.noaa.gov
    • datasets.ai
    • +1more
    las/laz - laser
    Updated Dec 29, 2020
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    Office for Coastal Management (2020). 2018 - 2020 NOAA USGS Lidar: Hawaii, HI [Dataset]. https://www.fisheries.noaa.gov/inport/item/68082
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    las/laz - laserAvailable download formats
    Dataset updated
    Dec 29, 2020
    Dataset provided by
    Office for Coastal Management
    Time period covered
    Jan 30, 2018 - Jan 6, 2020
    Area covered
    Description

    Product: Processed, classified lidar point cloud data tiles in LAS 1.4 format. Geographic Extent: Approximately 4,028 square miles encompassing the Big Island of Hawaii. Dataset Description: The HI Hawaii Island Lidar NOAA 2017 B17 lidar project called for the planning, acquisition, processing, and production of derivative products of lidar data to be collected at a nominal pulse spacing (NPS...

  4. a

    Intensity Images - USGS LiDAR

    • data-dauphinco.opendata.arcgis.com
    • hub.arcgis.com
    • +1more
    Updated May 1, 2018
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    Dauphin County, PA (2018). Intensity Images - USGS LiDAR [Dataset]. https://data-dauphinco.opendata.arcgis.com/documents/f44ca0ba1a2d4551be483da92f500442
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    Dataset updated
    May 1, 2018
    Dataset authored and provided by
    Dauphin County, PA
    Description

    The Dauphin County, PA 2016 QL2 LiDAR project called for the planning, acquisition, processing and derivative products of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet; NAVD1988 (Geoid 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 711 individual 5,000-foot x 5,000-foot tiles. Tile names use the following naming schema: "YYYYXXXXPAd" where YYYY is the first 3 characters of the tile's upper left corner Y-coordinate, XXXX - the first 4 characters of the tile's upper left corner X-coordinate, PA = Pennsylvania, and d = 'N' for North or 'S' for South. Corresponding 2.5-foot gridded hydro-flattened bare earth raster tiled DEM files and intensity image files were created using the same 5,000-foot x 5,000-foot schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. Continuous 2-foot contours were produced in Esri file geodatabase format. Ground Conditions: LiDAR collection began in Spring 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, Quantum Spatial established a total of 84 control points (24 calibration control points and 60 QC checkpoints). These were used to calibrate the LIDAR to known ground locations established throughout the project area.

  5. 2023 USGS Lidar: San Francisco, CA

    • fisheries.noaa.gov
    las/laz - laser +1
    Updated Jan 1, 2024
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    OCM Partners (2024). 2023 USGS Lidar: San Francisco, CA [Dataset]. https://www.fisheries.noaa.gov/inport/item/73386
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    las/laz - laser, not applicableAvailable download formats
    Dataset updated
    Jan 1, 2024
    Dataset provided by
    OCM Partners, LLC
    Time period covered
    Apr 20, 2023
    Area covered
    Description

    Original Product: These lidar data are processed Classified LAS 1.4 files, formatted to 654 individual 1000 m x 1000 m tiles; used to create intensity images, 3D breaklines, and hydro-flattened DEMs as necessary.

    Original Dataset Geographic Extent: 4 counties (Alameda, Marin, San Francisco, San Mateo) in California, covering approximately 53 total square miles.

    Original Dataset Descriptio...

  6. U

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

    • data.usgs.gov
    • datadiscoverystudio.org
    • +4more
    Updated Jan 27, 2017
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    U.S. Geological Survey (2017). 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
    Jan 27, 2017
    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 ...

  7. 2021 - 2022 USGS Lidar (QL1): Southeast Minnesota Driftless

    • fisheries.noaa.gov
    las/laz - laser
    Updated Aug 31, 2022
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    OCM Partners (2022). 2021 - 2022 USGS Lidar (QL1): Southeast Minnesota Driftless [Dataset]. https://www.fisheries.noaa.gov/inport/item/70275
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    las/laz - laserAvailable download formats
    Dataset updated
    Aug 31, 2022
    Dataset provided by
    OCM Partners, LLC
    Time period covered
    Apr 22, 2021 - Jun 13, 2021
    Area covered
    Dakota County, Mower County, Houston County, Fillmore County, Waseca County, Rice County, Minnesota, Steele County, VERTICAL LOCATION > LAND SURFACE, Minnesota, United States
    Description

    Product: Processed, classified lidar point cloud data tiles in LAS 1.4 format. Geographic Extent: This dataset covers approximately 5847 square miles in southeast Minnesota and consists of 3 deliveries or blocks. MN_SEDriftless_1 (Work Unit 228969) - Approximately 1,741 square miles in southeast Minnesota, including Dakota, Dodge, Freeborn, Mower, Rice, Scott, Steele, and Waseca counties MN...

  8. 2022 - 2023 NOAA USGS Lidar: Hawaii (Kahoolawe, Lanai, Maui, Molokai, Oahu)

    • catalog.data.gov
    • fisheries.noaa.gov
    Updated May 29, 2025
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    NOAA Office for Coastal Management (Point of Contact, Custodian) (2025). 2022 - 2023 NOAA USGS Lidar: Hawaii (Kahoolawe, Lanai, Maui, Molokai, Oahu) [Dataset]. https://catalog.data.gov/dataset/2022-2023-noaa-usgs-lidar-hawaii-kahoolawe-lanai-maui-molokai-oahu
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    Dataset updated
    May 29, 2025
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Area covered
    Maui County, O‘ahu, Kaho‘olawe, Moloka‘i, Hawaii, Maui, Lanai
    Description

    Original Dataset Product: Processed, classified lidar point cloud data tiles in LAZ 1.4 format. Original Dataset Geographic Extent: HI_NOAAMauiOahu_1: The work unit covers approximately 446 square miles (260.7 square miles of Molokai, 140.7 square miles of Lanai, and 44.6 square miles of Kahoolawe in the state of Hawaii). HI_NOAAMauiOahu_2: The work unit covers approximately 540.86 square miles of Maui and 496.61 square miles of Oahu in the state of Hawaii. Original Dataset Description: HI_NOAAMauiOahu_1 (Kahoolawe, Lanai, Molokai) HI_NOAAMauiOahu_1_B20 lidar project called for the planning, acquisition, processing, and production of derivative products of QL1 lidar data to be collected an aggregate nominal pulse spacing (ANPS) of 0.35-meters and 8 points per square meter (ppsm). Project specifications were based on the National Geospatial Program Lidar Base Specification Version 2.1, and the American Society of Photogrammetry and Remote Sensing (ASPRS) Positional Accuracy Standards for Digital Geospatial Data (Edition 1, Version 1.0). The data was developed based on a horizontal reference system of NAD83 (PA11), UTM 4 (EPSG 6634), Meter, and a vertical reference system of NAVD88 (GEOID12B), Meter. Lidar data was delivered as processed LAZ 1.4 files formatted to 5,044 individual 500-meters x 500-meters tiles. Note: Between 2020 and 2023 multiple mobilizations were made to collect the data in the project area due to the extreme terrain and persistent low clouds. On March 31, 2023, it was decided between Woolpert and USGS to end the acquisition phase of the project and move onto processing with the data collected. The DPA and work unit has been clipped to the extent of the data collected. Areas of low point density and/or small data voids within the work unit have been identified with low confidence polygons. HI_NOAAMauiOahu_2 (Maui, Oahu) HI_NOAAMauiOahu_2_B20 lidar project called for the planning, acquisition, processing, and production of derivative products of QL1 lidar data to be collected an aggregate nominal pulse spacing (ANPS) of 0.35-meters and 8 points per square meter (ppsm). Project specifications were based on the National Geospatial Program Lidar Base Specification Version 2.1, and the American Society of Photogrammetry and Remote Sensing (ASPRS) Positional Accuracy Standards for Digital Geospatial Data (Edition 1, Version 1.0). The data was developed based on a horizontal reference system of NAD83 (PA11), UTM 4 (EPSG 6634), Meter, and a vertical reference system of NAVD88 (GEOID12B), Meter. Lidar data was delivered as processed LAZ 1.4 files formatted to 11,716 individual 500-meters x 500-meters tiles. Note: Between 2020 and 2023 multiple mobilizations were made to collect the data in the project area due to the extreme terrain and persistent low clouds. On March 31, 2023, it was decided between Woolpert and USGS to end the acquisition phase of the project and move onto processing with the data collected. The DPA and work unit has been clipped to the extent of the data collected. Areas of low point density and/or small data voids within the work unit have been identified with low confidence polygons. Original Dataset Ground Conditions: HI_NOAAMauiOahu_1 (Kahoolawe, Lanai, Molokai) Lidar was collected from August 2, 2022, through July 9, 2023 while no snow was on the ground and rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Woolpert established ground control points that were used to calibrate the lidar to known ground locations established throughout the entire project area. An additional independent accuracy checkpoints were collected throughout the entire project area and used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data. HI_NOAAMauiOahu_2 (Maui, Oahu) Lidar was collected from January 11, 2023, through July 7, 2023 while rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Woolpert established ground control points that were used to calibrate the lidar to known ground locations established throughout the entire project area. An additional independent accuracy checkpoints were collected throughout the entire project area and used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.

  9. d

    2015 USGS Lidar DEM: 3DEP Co-Op South Central MS.

    • datadiscoverystudio.org
    Updated Feb 7, 2018
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    (2018). 2015 USGS Lidar DEM: 3DEP Co-Op South Central MS. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/8d105a5e228b499a95e8788fd4b0f437/html
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    Dataset updated
    Feb 7, 2018
    Description

    description: Mississippi Coastal QL2 Lidar with 3DEP Extension Lidar 0.7m NPS Lidar Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G15PD00091 Woolpert Order No. 75157 CONTRACTOR: Woolpert, Inc. This metadata record describes the 1m bare earth Digital Elevation Models (DEMs)for the following counties in Mississippi: Copiah, Lawrence, Lincoln, Pike, and Simpson. This task is for a high resolution data set of lidar covering approximately 5981 square miles. The lidar data was acquired and processed in compliance to U.S. Geological Survey National Geospatial Program Lidar Base Specification version 1.2. The lidar data was acquired and processed under the requirements identified in this task order. 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, one (1) meter pixel raster DEMs of the bare-earth surface in ERDAS IMG Format, and 8-bit intensity images. Gridded products conform to a 1500 m x 1500 m tiling scheme. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, control data, flight line vectors and tile index provided as ESRI shapefile, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format, and LAS swath data. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. In addition to the bare earth DEMs, the topobathy lidar point data are also available. These data are available for custom download here: https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=6306 Breaklines created from the lidar area also available for download in both gdb and gpkg format at: https://coast.noaa.gov/htdata/lidar2_z/geoid12b/data/6306/breaklines. The DEM and breakline products have not been reviewed by the NOAA Office for Coastal Management (OCM) and any conclusions drawn from the analysis of this information are not the responsibility of NOAA, OCM or its partners.; abstract: Mississippi Coastal QL2 Lidar with 3DEP Extension Lidar 0.7m NPS Lidar Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G15PD00091 Woolpert Order No. 75157 CONTRACTOR: Woolpert, Inc. This metadata record describes the 1m bare earth Digital Elevation Models (DEMs)for the following counties in Mississippi: Copiah, Lawrence, Lincoln, Pike, and Simpson. This task is for a high resolution data set of lidar covering approximately 5981 square miles. The lidar data was acquired and processed in compliance to U.S. Geological Survey National Geospatial Program Lidar Base Specification version 1.2. The lidar data was acquired and processed under the requirements identified in this task order. 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, one (1) meter pixel raster DEMs of the bare-earth surface in ERDAS IMG Format, and 8-bit intensity images. Gridded products conform to a 1500 m x 1500 m tiling scheme. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, control data, flight line vectors and tile index provided as ESRI shapefile, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format, and LAS swath data. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. In addition to the bare earth DEMs, the topobathy lidar point data are also available. These data are available for custom download here: https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=6306 Breaklines created from the lidar area also available for download in both gdb and gpkg format at: https://coast.noaa.gov/htdata/lidar2_z/geoid12b/data/6306/breaklines. The DEM and breakline products have not been reviewed by the NOAA Office for Coastal Management (OCM) and any conclusions drawn from the analysis of this information are not the responsibility of NOAA, OCM or its partners.

  10. 2022 - 2023 NOAA USGS Lidar DEM: HI (Kahoolawe, Lanai, Maui, Molokai, Oahu)

    • catalog.data.gov
    • fisheries.noaa.gov
    Updated May 29, 2025
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    NOAA Office for Coastal Management (Point of Contact, Custodian) (2025). 2022 - 2023 NOAA USGS Lidar DEM: HI (Kahoolawe, Lanai, Maui, Molokai, Oahu) [Dataset]. https://catalog.data.gov/dataset/2022-2023-noaa-usgs-lidar-dem-hi-kahoolawe-lanai-maui-molokai-oahu
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    Dataset updated
    May 29, 2025
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Area covered
    O‘ahu, Kaho‘olawe, Moloka‘i, Maui, Lanai
    Description

    Original Dataset Product: 0.5-meter bare-earth raster digital elevation model (DEM) data tiles in GeoTIFF format. Original Dataset Geographic Extent: HI_NOAAMauiOahu_1: The work unit covers approximately 446 square miles (260.7 square miles of Molokai, 140.7 square miles of Lanai, and 44.6 square miles of Kahoolawe in the state of Hawaii). HI_NOAAMauiOahu_2: The work unit covers approximately 540.86 square miles of Maui and 496.61 square miles of Oahu in the state of Hawaii. Original Dataset Description: HI_NOAAMauiOahu_1 (Kahoolawe, Lanai, Molokai) HI_NOAAMauiOahu_1_B20 lidar project called for the planning, acquisition, processing, and production of derivative products of QL1 lidar data to be collected an aggregate nominal pulse spacing (ANPS) of 0.35-meters and 8 points per square meter (ppsm). Project specifications were based on the National Geospatial Program Lidar Base Specification Version 2.1, and the American Society of Photogrammetry and Remote Sensing (ASPRS) Positional Accuracy Standards for Digital Geospatial Data (Edition 1, Version 1.0). The data was developed based on a horizontal reference system of NAD83 (PA11), UTM 4 (EPSG 6634), Meter, and a vertical reference system of NAVD88 (GEOID12B), Meter. DEM data was delivered as processed GeoTIFF files formatted to 5,044 individual 500-meters x 500-meters tiles. Note: Between 2020 and 2023 multiple mobilizations were made to collect the data in the project area due to the extreme terrain and persistent low clouds. On March 31, 2023, it was decided between Woolpert and USGS to end the acquisition phase of the project and move onto processing with the data collected. The DPA and work unit has been clipped to the extent of the data collected. Areas of low point density and/or small data voids within the work unit have been identified with low confidence polygons. HI_NOAAMauiOahu_2 (Maui, Oahu) HI_NOAAMauiOahu_2_B20 lidar project called for the planning, acquisition, processing, and production of derivative products of QL1 lidar data to be collected an aggregate nominal pulse spacing (ANPS) of 0.35-meters and 8 points per square meter (ppsm). Project specifications were based on the National Geospatial Program Lidar Base Specification Version 2.1, and the American Society of Photogrammetry and Remote Sensing (ASPRS) Positional Accuracy Standards for Digital Geospatial Data (Edition 1, Version 1.0). The data was developed based on a horizontal reference system of NAD83 (PA11), UTM 4 (EPSG 6634), Meter, and a vertical reference system of NAVD88 (GEOID12B), Meter. DEM data was delivered as processed GeoTIFF files formatted to 11,716 individual 500-meters x 500-meters tiles. Note: Between 2020 and 2023 multiple mobilizations were made to collect the data in the project area due to the extreme terrain and persistent low clouds. On March 31, 2023, it was decided between Woolpert and USGS to end the acquisition phase of the project and move onto processing with the data collected. The DPA and work unit has been clipped to the extent of the data collected. Areas of low point density and/or small data voids within the work unit have been identified with low confidence polygons. Original Dataset Ground Conditions: HI_NOAAMauiOahu_1 (Kahoolawe, Lanai, Molokai) Lidar was collected from August 2, 2022, through July 9, 2023 while no snow was on the ground and rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Woolpert established ground control points that were used to calibrate the lidar to known ground locations established throughout the entire project area. An additional independent accuracy checkpoints were collected throughout the entire project area and used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data. HI_NOAAMauiOahu_2 (Maui, Oahu) Lidar was collected from January 11, 2023, through July 7, 2023 while rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Woolpert established ground control points that were used to calibrate the lidar to known ground locations established throughout the entire project area. An additional independent accuracy checkpoints were collected throughout the entire project area and used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.

  11. U

    2018 lidar-derived imagery of karst areas in Puerto Rico at 1-meter...

    • data.usgs.gov
    • s.cnmilf.com
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    Cheyenne Cox; Daniel Doctor, 2018 lidar-derived imagery of karst areas in Puerto Rico at 1-meter resolution [Dataset]. http://doi.org/10.5066/P98XAH2V
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    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Cheyenne Cox; Daniel Doctor
    License

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

    Time period covered
    Jul 5, 2016 - Aug 15, 2018
    Area covered
    Puerto Rico
    Description

    This raster dataset contains 1-meter lidar-derived imagery of 7.5 minute quadrangles in karst areas of Puerto Rico and was created using geographic information systems (GIS) software. Lidar-derived elevation data, acquired in 2018, were used to create a 1-meter resolution working digital elevation model (DEM). To create this imagery, a hillshade was applied and a topographic position index (TPI) raster was calculated. These two rasters were uploaded into GlobalMapper, where the TPI raster was made partially transparent and overlaid the hillshade DEM. The resulting image was exported to create these 1-meter resolution lidar-derived images. The data is projected in North America Datum (NAD) 1983 (2011) UTM Zone 19N.

  12. d

    2012 Pre-Sandy New York and New Jersey USGS Lidar-Derived Dune Crest, Toe...

    • catalog.data.gov
    • data.usgs.gov
    • +3more
    Updated Jul 6, 2024
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    U.S. Geological Survey (2024). 2012 Pre-Sandy New York and New Jersey USGS Lidar-Derived Dune Crest, Toe and Shoreline [Dataset]. https://catalog.data.gov/dataset/2012-pre-sandy-new-york-and-new-jersey-usgs-lidar-derived-dune-crest-toe-and-shoreline
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    New York, New Jersey
    Description

    The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2012 Pre Hurricane Sandy New York and New Jersey United States Geological Survey (USGS) Experimental Advanced Airborne Research lidar B (EAARL-B) survey. Beach width is included and is defined as the distance between the dune toe and shoreline along a cross-shore profile. The beach slope is calculated using this beach width and the elevation of the shoreline and dune toe.

  13. d

    Data from: 2020 New Jersey USACE USGS Lidar-Derived Dune Crest, Toe and...

    • catalog.data.gov
    • data.usgs.gov
    • +1more
    Updated Jul 6, 2024
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    U.S. Geological Survey (2024). 2020 New Jersey USACE USGS Lidar-Derived Dune Crest, Toe and Shoreline [Dataset]. https://catalog.data.gov/dataset/2020-new-jersey-usace-usgs-lidar-derived-dune-crest-toe-and-shoreline
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    New Jersey
    Description

    The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline derived from the 2020 United States Army Corps of Engineers (USACE) United States Geological Survey (USGS) New Jersey lidar survey. Beach width is included and is defined as the distance between the dune toe and shoreline along a cross-shore profile. The beach slope is calculated using this beach width and the elevation of the shoreline and dune toe.

  14. 2023 NOAA USGS Lidar: Hawaii (Big Island)

    • catalog.data.gov
    • fisheries.noaa.gov
    Updated May 29, 2025
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    NOAA Office for Coastal Management (Point of Contact, Custodian) (2025). 2023 NOAA USGS Lidar: Hawaii (Big Island) [Dataset]. https://catalog.data.gov/dataset/2023-noaa-usgs-lidar-hawaii-big-island
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    Dataset updated
    May 29, 2025
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Area covered
    Island of Hawai'i, Hawaii
    Description

    Original Dataset Product: Processed, classified lidar point cloud data tiles in LAZ 1.4 format. Original Dataset Geographic Extent: HI_NOAAMauiOahu_3: The work unit covers approximately Approximately 306 square miles on the eastern side of the big island of Hawaii. Original Dataset Description: HI_NOAAMauiOahu_3 (Big Island) The HI_NOAAMauiOahu_3_B20 lidar project called for the planning, acquisition, processing, and production of derivative products of QL1 lidar data to be collected an aggregate nominal pulse spacing (ANPS) of 0.35-meters and 8 points per square meter (ppsm). Project specifications were based on the National Geospatial Program Lidar Base Specification Version 2.1, and the American Society of Photogrammetry and Remote Sensing (ASPRS) Positional Accuracy Standards for Digital Geospatial Data (Edition 1, Version 1.0). The data was developed based on a horizontal reference system of NAD83 (PA11), UTM 5 (EPSG 6635), Meter, and a vertical reference system of NAVD88 (GEOID12B), Meter. Lidar data was delivered as processed LAZ 1.4 files formatted to 3,450 individual 500-meters x 500-meters tiles. Note: Between 2020 and 2023 multiple mobilizations were made to collect the data in the project area due to the extreme terrain and persistent low clouds. On March 31, 2023, it was decided between Woolpert and USGS to end the acquisition phase of the project and move onto processing with the data collected. The DPA and work unit has been clipped to the extent of the data collected. Areas of low point density and/or small data voids within the work unit have been identified with low confidence polygons. Original Dataset Ground Conditions: HI_NOAAMauiOahu_3 (Big Island) Lidar was collected from February 14, 2023, through March 15, 2023 while no snow was on the ground and rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Woolpert established ground control points that were used to calibrate the lidar to known ground locations established throughout the entire project area. An additional independent accuracy checkpoints were collected throughout the entire project area and used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.

  15. d

    2018 Alabama and Florida USGS Lidar-Derived Dune Crest, Toe and Shoreline

    • catalog.data.gov
    Updated Jul 6, 2024
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    U.S. Geological Survey (2024). 2018 Alabama and Florida USGS Lidar-Derived Dune Crest, Toe and Shoreline [Dataset]. https://catalog.data.gov/dataset/2018-alabama-and-florida-usgs-lidar-derived-dune-crest-toe-and-shoreline
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Florida
    Description

    The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline derived from the 2018 United States Geological Survey (USGS) Alabama and Florida lidar survey. Beach width is included and is defined as the distance between the dune toe and shoreline along a cross-shore profile. The beach slope is calculated using this beach width and the elevation of the shoreline and dune toe.

  16. U

    Geodatabase containing bathymetric and LiDAR data for Blue Mountain Lake,...

    • data.usgs.gov
    • datasets.ai
    • +3more
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    Daniel Wagner, Geodatabase containing bathymetric and LiDAR data for Blue Mountain Lake, Arkansas. [Dataset]. http://doi.org/10.5066/F7Z60N1P
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    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Daniel Wagner
    License

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

    Time period covered
    May 18, 2017 - Jun 1, 2017
    Area covered
    Blue Mountain Lake, Arkansas
    Description

    A bathymetric survey of Blue Mountain Lake, Arkansas, was conducted in May 2017 by the Lower Mississippi-Gulf Water Science Center of the U.S. Geological Survey (USGS) using methodologies for sonar surveys similar to those described by Wilson and Richards (2006). Point data from the bathymetric survey were merged with point data from an aerial LiDAR survey conducted in December 2010, for the U.S. Army Corps of Engineers (USACE), Little Rock District. From the combined point data, a terrain dataset (a type of triangulated irregular network, or TIN, model) was created in Esri ArcGIS for the lakebed within the extent of pool elevation 420 feet above the North American Vertical Datum of 1988 (NAVD88). This Esri file geodatabase contains the following products: 1) point data from the bathymetric and LiDAR surveys; 2) a terrain dataset; 3) a digital elevation model (DEM) in Esri GRID format with a 3-ft cell size; 4) a feature class of bathymetric contours at 4-ft intervals; and 5) a ...

  17. a

    Digital Elevation Model (DEM) - USGS LiDAR

    • hub.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated May 1, 2018
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    Dauphin County, PA (2018). Digital Elevation Model (DEM) - USGS LiDAR [Dataset]. https://hub.arcgis.com/documents/339f39c0b4054cbc90c454b7dfb61231
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    Dataset updated
    May 1, 2018
    Dataset authored and provided by
    Dauphin County, PA
    Description

    The Dauphin County, PA 2016 QL2 LiDAR project called for the planning, acquisition, processing and derivative products of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011) State Plane Pennsylvania South Zone, US survey feet; NAVD1988 (Geoid 12B), US survey feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.4 Files formatted to 711 individual 5,000-foot x 5,000-foot tiles. Tile names use the following naming schema: "YYYYXXXXPAd" where YYYY is the first 3 characters of the tile's upper left corner Y-coordinate, XXXX - the first 4 characters of the tile's upper left corner X-coordinate, PA = Pennsylvania, and d = 'N' for North or 'S' for South. Corresponding 2.5-foot gridded hydro-flattened bare earth raster tiled DEM files and intensity image files were created using the same 5,000-foot x 5,000-foot schema. Hydro-flattened breaklines were produced in Esri file geodatabase format. Continuous 2-foot contours were produced in Esri file geodatabase format. Ground Conditions: LiDAR collection began in Spring 2016, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, Quantum Spatial established a total of 84 control points (24 calibration control points and 60 QC checkpoints). These were used to calibrate the LIDAR to known ground locations established throughout the project area.

  18. 2010 NOAA/USGS Lidar: French Frigate Shoals, NWHI

    • fisheries.noaa.gov
    • datasets.ai
    • +1more
    las/laz - laser
    Updated Apr 17, 2014
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    Office for Coastal Management (2014). 2010 NOAA/USGS Lidar: French Frigate Shoals, NWHI [Dataset]. https://www.fisheries.noaa.gov/inport/item/64674
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    las/laz - laserAvailable download formats
    Dataset updated
    Apr 17, 2014
    Dataset provided by
    Office for Coastal Management
    Time period covered
    Jul 23, 2010
    Area covered
    Description

    The U.S. Geological Survey (USGS) contracted with Hawaii-based Aerial Surveying, Inc. to collect lidar-derived elevation data over the low-lying areas within the northwestern Hawaiian Islands (NWHI) during the summer of 2010. A separate contract issued to Aerial Surveying, Inc. by the National Oceanic and Atmospheric Administration (NOAA) funded the lidar data processing and elevation data prod...

  19. d

    2013 Dauphin Island USGS Lidar-Derived Dune Crest, Toe and Shoreline

    • catalog.data.gov
    • data.usgs.gov
    • +3more
    Updated Aug 16, 2024
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    U.S. Geological Survey (2024). 2013 Dauphin Island USGS Lidar-Derived Dune Crest, Toe and Shoreline [Dataset]. https://catalog.data.gov/dataset/2013-dauphin-island-usgs-lidar-derived-dune-crest-toe-and-shoreline
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    Dataset updated
    Aug 16, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Dauphin Island
    Description

    The Storm-Induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Lidar-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline derived from the 2013 Dauphin Island (Alabama) USGS lidar survey. Beach width is included and is defined as the distance between the dune toe and shoreline along a cross-shore profile. The beach slope is calculated using this beach width and the elevation of the shoreline and dune toe.

  20. U

    Topobathymetric elevation models of the upper Delaware River, USA - Version...

    • data.usgs.gov
    • s.cnmilf.com
    • +1more
    Updated Sep 21, 2020
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    John Young (2020). Topobathymetric elevation models of the upper Delaware River, USA - Version 1 [Dataset]. http://doi.org/10.5066/P97031JUv
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    Dataset updated
    Sep 21, 2020
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    John Young
    License

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

    Time period covered
    Nov 26, 2012 - Dec 20, 2012
    Area covered
    Delaware River, United States
    Description

    This dataset includes topographic elevations (in meters) surrounding and bathymetric elevations within the upper Delaware River (USA). Bathymetric lidar data was acquired using the Experimental Advanced Airborne Research Lidar, version B. The EAARL-B is a successor instrument to the original EAARL bathymetric LiDAR sensor developed for mapping coral reef environments in clear water, but subsequently used in river mapping. Both the original EAARL and the EAARL-B are small footprint, full waveform digitizing, green wavelength (532nm) airborne laser scanners, capable of acquiring laser returns from submerged as well as subaerial topography. Improvements from the original sensor include increased sample density, increased pulse rate, enhanced deep and shallow bathymetry performance, and improved data processing hardware. The EAARL-B sensor differs from the original in a 10x laser power increase, and incorporation of three shallow water receiving channels, as well as a deep water recei ...

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USGS 3DEP LiDAR Point Clouds [Dataset]. https://registry.opendata.aws/usgs-lidar/

USGS 3DEP LiDAR Point Clouds

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10 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jan 22, 2019
Dataset provided by
<a href="https://hobu.co">Hobu, Inc.</a>
Description

The goal of the USGS 3D Elevation Program (3DEP) is to collect elevation data in the form of light detection and ranging (LiDAR) data over the conterminous United States, Hawaii, and the U.S. territories, with data acquired over an 8-year period. This dataset provides two realizations of the 3DEP point cloud data. The first resource is a public access organization provided in Entwine Point Tiles format, which a lossless, full-density, streamable octree based on LASzip (LAZ) encoding. The second resource is a Requester Pays of the original, Raw LAZ (Compressed LAS) 1.4 3DEP format, and more complete in coverage, as sources with incomplete or missing CRS, will not have an ETP tile generated. Resource names in both buckets correspond to the USGS project names.

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