100+ datasets found
  1. a

    Connecticut 3D Lidar Viewer

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • gemelo-digital-en-arcgis-gemelodigital.hub.arcgis.com
    • +1more
    Updated Jan 8, 2020
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    UConn Center for Land use Education and Research (2020). Connecticut 3D Lidar Viewer [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/788d121c4a1f4980b529f914c8df19f4
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    Dataset updated
    Jan 8, 2020
    Dataset authored and provided by
    UConn Center for Land use Education and Research
    Description

    Statewide 2016 Lidar points colorized with 2018 NAIP imagery as a scene created by Esri using ArcGIS Pro for the entire State of Connecticut. This service provides the colorized Lidar point in interactive 3D for visualization, interaction of the ability to make measurements without downloading.Lidar is referenced at https://cteco.uconn.edu/data/lidar/ and can be downloaded at https://cteco.uconn.edu/data/download/flight2016/. Metadata: https://cteco.uconn.edu/data/flight2016/info.htm#metadata. The Connecticut 2016 Lidar was captured between March 11, 2016 and April 16, 2016. Is covers 5,240 sq miles and is divided into 23, 381 tiles. It was acquired by the Captiol Region Council of Governments with funding from multiple state agencies. It was flown and processed by Sanborn. The delivery included classified point clouds and 1 meter QL2 DEMs. The 2016 Lidar is published on the Connecticut Environmental Conditions Online (CT ECO) website. CT ECO is the collaborative work of the Connecticut Department of Energy and Environmental Protection (DEEP) and the University of Connecticut Center for Land Use Education and Research (CLEAR) to share environmental and natural resource information with the general public. CT ECO's mission is to encourage, support, and promote informed land use and development decisions in Connecticut by providing local, state and federal agencies, and the public with convenient access to the most up-to-date and complete natural resource information available statewide.Process used:Extract Building Footprints from Lidar1. Prepare Lidar - Download 2016 Lidar from CT ECO- Create LAS Dataset2. Extract Building Footprints from LidarUse the LAS Dataset in the Classify Las Building Tool in ArcGIS Pro 2.4.Colorize LidarColorizing the Lidar points means that each point in the point cloud is given a color based on the imagery color value at that exact location.1. Prepare Imagery- Acquire 2018 NAIP tif tiles from UConn (originally from USDA NRCS).- Create mosaic dataset of the NAIP imagery.2. Prepare and Analyze Lidar Points- Change the coordinate system of each of the lidar tiles to the Projected Coordinate System CT NAD 83 (2011) Feet (EPSG 6434). This is because the downloaded tiles come in to ArcGIS as a Custom Projection which cannot be published as a Point Cloud Scene Layer Package.- Convert Lidar to zlas format and rearrange. - Create LAS Datasets of the lidar tiles.- Colorize Lidar using the Colorize LAS tool in ArcGIS Pro. - Create a new LAS dataset with a division of Eastern half and Western half due to size limitation of 500GB per scene layer package. - Create scene layer packages (.slpk) using Create Cloud Point Scene Layer Package. - Load package to ArcGIS Online using Share Package. - Publish on ArcGIS.com and delete the scene layer package to save storage cost.Additional layers added:Visit https://cteco.uconn.edu/projects/lidar3D/layers.htm for a complete list and links. 3D Buildings and Trees extracted by Esri from the lidarShaded Relief from CTECOImpervious Surface 2012 from CT ECONAIP Imagery 2018 from CTECOContours (2016) from CTECOLidar 2016 Download Link derived from https://www.cteco.uconn.edu/data/download/flight2016/index.htm

  2. Open Topographic Lidar Data - Dataset - data.gov.ie

    • data.gov.ie
    Updated Oct 22, 2021
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    data.gov.ie (2021). Open Topographic Lidar Data - Dataset - data.gov.ie [Dataset]. https://data.gov.ie/dataset/open-topographic-lidar-data
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    Dataset updated
    Oct 22, 2021
    Dataset provided by
    data.gov.ie
    License

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

    Description

    This data was collected by the Geological Survey Ireland, the Department of Culture, Heritage and the Gaeltacht, the Discovery Programme, the Heritage Council, Transport Infrastructure Ireland, New York University, the Office of Public Works and Westmeath County Council. All data formats are provided as GeoTIFF rasters but are at different resolutions. Data resolution varies depending on survey requirements. Resolutions for each organisation are as follows: GSI – 1m DCHG/DP/HC - 0.13m, 0.14m, 1m NY – 1m TII – 2m OPW – 2m WMCC - 0.25m Both a DTM and DSM are raster data. Raster data is another name for gridded data. Raster data stores information in pixels (grid cells). Each raster grid makes up a matrix of cells (or pixels) organised into rows and columns. The grid cell size varies depending on the organisation that collected it. GSI data has a grid cell size of 1 meter by 1 meter. This means that each cell (pixel) represents an area of 1 meter squared.

  3. d

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

    • catalog.data.gov
    • data.usgs.gov
    • +1more
    Updated Mar 11, 2025
    + more versions
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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.

  4. NOAA Coastal Lidar Data

    • registry.opendata.aws
    Updated Feb 24, 2021
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    NOAA (2021). NOAA Coastal Lidar Data [Dataset]. https://registry.opendata.aws/noaa-coastal-lidar/
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    Dataset updated
    Feb 24, 2021
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Description

    Lidar (light detection and ranging) is a technology that can measure the 3-dimentional location of objects, including the solid earth surface. The data consists of a point cloud of the positions of solid objects that reflected a laser pulse, typically from an airborne platform. In addition to the position, each point may also be attributed by the type of object it reflected from, the intensity of the reflection, and other system dependent metadata. The NOAA Coastal Lidar Data is a collection of lidar projects from many different sources and agencies, geographically focused on the coastal areas of the United States of America. The data is provided in Entwine Point Tiles (EPT; https://entwine.io) format, which is a lossless streamable octree of the point cloud, and in LAZ format. Datasets are maintained in their original projects and care should be taken when merging projects. The coordinate reference system for the data is The NAD83(2011) UTM zone appropriate for the center of each data set for EPT and geographic coordinates for LAZ. Vertically they are in the orthometric datum appropriate for that area (for example, NAVD88 in the mainland United States, PRVD02 in Puerto Rico, or GUVD03 in Guam). The geoid model used is reflected in the data set resource name.
    The data are organized under directories entwine and laz for the EPT and LAZ versions respectively. Some datasets are not in EPT format, either because the dataset is already in EPT on the USGS public lidar site, they failed to build or their content does not work well in EPT format. Topobathy lidar datasets using the topobathy domain profile do not translate well to EPT format.

  5. d

    Lidar Data Viewer

    • catalog.data.gov
    • data.oregon.gov
    Updated May 17, 2025
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    State of Oregon (2025). Lidar Data Viewer [Dataset]. https://catalog.data.gov/dataset/lidar-data-viewer
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    Dataset updated
    May 17, 2025
    Dataset provided by
    State of Oregon
    Description

    {{description}}

  6. d

    Topobathymetric LiDAR Data (2017)

    • catalog.data.gov
    • data.cityofnewyork.us
    Updated Jul 5, 2025
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    data.cityofnewyork.us (2025). Topobathymetric LiDAR Data (2017) [Dataset]. https://catalog.data.gov/dataset/topobathymetric-lidar-data-2017
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    Dataset updated
    Jul 5, 2025
    Dataset provided by
    data.cityofnewyork.us
    Description

    Note: The files can be downloaded from the Attachments section below. Please note that the total size is 180GB, so the download may take some time depending on your system’s capabilities and configuration. Topographic and bathymetric LiDAR data was collected for New York City in 2017. Topographic data was collected for the entire city, plus an additional 100 meter buffer, using a Leica ALS80 sensor equipped to capture at least 8 pulse/m2. Dates of capture for topographic data were between 05/03/2017 and 05/17/2017 during 50% leaf-off conditions. Bathymetric data was collected in select areas of the city (where bathymetric data capture was expected) using a Riegl VQ-880-G sensor equipped to capture approximately 15 pulses/m2 (1.5 Secchi depths). Dates of capture for bathymetric were between 07/04/2017 - 07/26/2017. LiDAR data was tidally-coordinated and captured between mean lower low water (+30% of mean tide) ranges. The horizontal datum for all datasets is NAD83, the vertical datum is NAVD88, Geoid 12B, and the data is projected in New York State Plane - Long Island. Units are in US Survey Feet. To learn more about these datasets, visit the interactive “Understanding the 2017 New York City LiDAR Capture” Story Map -- https://maps.nyc.gov/lidar/2017/ Please see the following link for additional documentation on this dataset -- https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_LiDAR_Summary.md

  7. H

    Texas Basemap - Lidar Elevation Data (DEM)

    • hydroshare.org
    • beta.hydroshare.org
    • +1more
    zip
    Updated Nov 3, 2023
    + more versions
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    HydroShare (2023). Texas Basemap - Lidar Elevation Data (DEM) [Dataset]. http://doi.org/10.4211/hs.af6ae321e2ad40a1bc6d0b695370fbfc
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    zip(5.5 GB)Available download formats
    Dataset updated
    Nov 3, 2023
    Dataset provided by
    HydroShare
    License

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

    Area covered
    Texas
    Description

    This resource contains Lidar-DEM collection status shapefiles from the Texas Natural Resources Information System (TNRIS) [http://tnris.org]. November 2023 updates: this year, TNRIS changed its name to Texas Geographic Information Office (TxGIO). The domain name hasn't changed yet, but the data hub is continually evolving. See [1], [2] for current downloadable data.

    For purposes of Hurricane Harvey studies, the 1-m DEM for Harris County (2008) has also been uploaded here as a set of 4 zipfiles containing the DEM in tiff files. See [1] for a link to the current elevation status map and downloadable DEMs.
    Project name: H-GAC 2008 1m Datasets: 1m Point Cloud, 1M Hydro-Enforced DEM, 3D Breaklines, 1ft and 5ft Contours Points per sq meter: 1 Total area: 3678.56 sq miles Source: Houston-Galveston Area Council (H-GAC) Acquired by: Merrick, QA/QC: Merrick Catalog: houston-galveston-area-council-h-gac-2008-lidar

    References: [1] TNRIS/TxGIO StratMap elevation data [https://tnris.org/stratmap/elevation-lidar/] [2] TNRIS/TxGIO DataHub [https://data.tnris.org/]

  8. LIDAR Composite Digital Terrain Model (DTM) - 1m

    • environment.data.gov.uk
    Updated Dec 15, 2023
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    Environment Agency (2023). LIDAR Composite Digital Terrain Model (DTM) - 1m [Dataset]. https://environment.data.gov.uk/dataset/13787b9a-26a4-4775-8523-806d13af58fc
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    Dataset updated
    Dec 15, 2023
    Dataset authored and provided by
    Environment Agencyhttps://www.gov.uk/ea
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    The LIDAR Composite DTM (Digital Terrain Model) is a raster elevation model covering ~99% of England at 1m spatial resolution. The DTM (Digital Terrain Model) is produced from the last or only laser pulse returned to the sensor. We remove surface objects from the Digital Surface Model (DSM), using bespoke algorithms and manual editing of the data, to produce a terrain model of just the surface.

    Produced by the Environment Agency in 2022, the DTM is derived from a combination of our Time Stamped archive and National LIDAR Programme surveys, which have been merged and re-sampled to give the best possible coverage. Where repeat surveys have been undertaken the newest, best resolution data is used. Where data was resampled a bilinear interpolation was used before being merged.

    The 2022 LIDAR Composite contains surveys undertaken between 6th June 2000 and 2nd April 2022. Please refer to the metadata index catalgoues which show for any location which survey was used in the production of the LIDAR composite.

    The data is available to download as GeoTiff rasters in 5km tiles aligned to the OS National grid. The data is presented in metres, referenced to Ordinance Survey Newlyn and using the OSTN’15 transformation method. All individual LIDAR surveys going into the production of the composite had a vertical accuracy of +/-15cm RMSE.

  9. a

    Elevation from Lidar (Image Service)

    • hub.arcgis.com
    • gis.data.mass.gov
    • +2more
    Updated Jul 23, 2020
    + more versions
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    MassGIS - Bureau of Geographic Information (2020). Elevation from Lidar (Image Service) [Dataset]. https://hub.arcgis.com/datasets/49cbba6636fa4c41a5ea162ccf1e41bc
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    Dataset updated
    Jul 23, 2020
    Dataset authored and provided by
    MassGIS - Bureau of Geographic Information
    Area covered
    Description

    This is a seamless bare earth digital elevation model (DEM) created from lidar terrain elevation data for the Commonwealth of Massachusetts. It represents the elevation of the surface with vegetation and structures removed. The spatial resolution of the map is 1 meter. The elevation of each 1-meter square cell was linearly interpolated from classified lidar-derived point data.This version of the DEM stores the elevation values as integers. The native VALUE field represents the elevation above/below sea level in meters. MassGIS added a FEET field to the VAT (value attribute table) to store the elevation in feet as calculated by multiplying VALUE x 3.28084.Dates of lidar data used in this DEM range from 2010-2015. The overlapping lidar projects were adjusted to the same projection and datum and then mosaicked, with the most recent data replacing any older data. Several very small gaps between the project areas were patched with older lidar data where necessary or with models from recent aerial photo acquisitions. See https://www.mass.gov/doc/lidar-project-areas-original/download for an index map.This DEM is referenced to the WGS_1984_Web_Mercator_Auxiliary_Sphere spatial reference.See the MassGIS datalayer page to download the data as a file geodatabase raster dataset.View this service in the Massachusetts Elevation Finder.

  10. a

    Data from: LIDAR data

    • hub.arcgis.com
    Updated Oct 8, 2021
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    GlasgowGIS (2021). LIDAR data [Dataset]. https://hub.arcgis.com/documents/5e01825608454952bbb3386c4ab395a3
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    Dataset updated
    Oct 8, 2021
    Dataset authored and provided by
    GlasgowGIS
    Description

    LIDAR data is extremely accurate 3D data generated from sensors on the ground or on airplanes. This data was acquired in 2021.

  11. k

    Kentucky LiDAR Point Cloud Data

    • kyfromabove.ky.gov
    • hub.arcgis.com
    • +1more
    Updated Aug 30, 2016
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    KyGovMaps (2016). Kentucky LiDAR Point Cloud Data [Dataset]. https://kyfromabove.ky.gov/maps/kentucky-lidar-point-cloud-data/about
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    Dataset updated
    Aug 30, 2016
    Dataset authored and provided by
    KyGovMaps
    Area covered
    Description

    This web map allows for the download of KyFromAbove LiDAR data by 5k tile in LAZ format. This point cloud data was acquired during the typical leaf-off acquisition period (winter-spring) over a period of several years and may be provided as LAS version 1.1, 1.2, or 1.4 depending upon the acquisition period. Users will need to download the LAZIP.exe in order to decompress each tile. LiDAR data specifications adopted by the KyFromAbove Technical Advisory Committee can be found here. This is the source data used to create the Commonwealth's 5 foot digital elevation model (DEM) and its associated derivatives. More information regarding this data resource can be found on the KyGeoPortal.

  12. a

    GEO Project Lidar Viewer

    • gulf-coast-geospatial-geo-project.hub.arcgis.com
    Updated Oct 7, 2021
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    kg160_GEO_Project (2021). GEO Project Lidar Viewer [Dataset]. https://gulf-coast-geospatial-geo-project.hub.arcgis.com/maps/188410fd28cb4186bb7032345d0b19bf
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    Dataset updated
    Oct 7, 2021
    Dataset authored and provided by
    kg160_GEO_Project
    Area covered
    Description

    GEO Project Lidar Viewercreated by Kate Grala, Dr. Cartwright, John, and John VanderZwaag

  13. Lidar Download Map

    • open.canada.ca
    • catalogue.arctic-sdi.org
    • +2more
    html
    Updated Jan 9, 2025
    + more versions
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    Government of New Brunswick (2025). Lidar Download Map [Dataset]. https://open.canada.ca/data/en/dataset/80ccc975-d6ec-9e24-a7f9-a8bd81a0b3c2
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    htmlAvailable download formats
    Dataset updated
    Jan 9, 2025
    Dataset provided by
    Government of New Brunswickhttps://www.gnb.ca/
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    Lidar point cloud data with classifications – unclassified (1), ground (2), low vegetation (3), medium vegetation (4), high vegetation (5), buildings (6), low point - noise (7), reserved – model keypoint (8), high noise (18).

  14. g

    Lidar Data Viewer | gimi9.com

    • gimi9.com
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    Lidar Data Viewer | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_lidar-data-viewer/
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    Description

    🇺🇸 미국

  15. n

    NEON (National Ecological Observatory Network) Discrete return LiDAR point...

    • data.neonscience.org
    zip
    + more versions
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    NEON (National Ecological Observatory Network) Discrete return LiDAR point cloud (DP1.30003.001) [Dataset]. https://data.neonscience.org/data-products/DP1.30003.001
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    zipAvailable download formats
    License

    https://www.neonscience.org/data-samples/data-policies-citationhttps://www.neonscience.org/data-samples/data-policies-citation

    Time period covered
    Jun 2013 - Jun 2025
    Area covered
    UKFS, YELL, SERC, WREF, CPER, PRIN, ABBY, BLAN, SRER, GUAN
    Description

    Unclassified three-dimensional point cloud by flightline and classified point cloud by 1 km tile, provided in LAZ format. Classifications follow standard ASPRS definitions. All point coordinates are provided in meters. Horizontal coordinates are referenced in the appropriate UTM zone and the ITRF00 datum. Elevations are referenced to Geoid12A.

  16. U

    Lidar Point Clouds (LPCs), Digital Elevation Models (DEMs), and Snow Depth...

    • data.usgs.gov
    • catalog.data.gov
    Updated Jul 18, 2024
    + more versions
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    Mark Bauer; Matthew Burgess; Josip Adams; Graham Sexstone; John Fulton; William Mcdermott; Lance Brady (2024). Lidar Point Clouds (LPCs), Digital Elevation Models (DEMs), and Snow Depth Raster Maps Derived from Lidar Data Collected on Small, Uncrewed Aircraft Systems in the Upper Colorado River Basin, Colorado, 2020-22 [Dataset]. http://doi.org/10.5066/P9LF15AE
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    Dataset updated
    Jul 18, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Authors
    Mark Bauer; Matthew Burgess; Josip Adams; Graham Sexstone; John Fulton; William Mcdermott; Lance Brady
    License

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

    Time period covered
    Jan 1, 2020 - Dec 1, 2022
    Area covered
    Colorado, Colorado River
    Description

    This data release consists of three child items distinguishing the following types of data: light detection and ranging (lidar) point clouds (LPCs), digital elevation models (DEMs), and snow depth raster maps. These three data types are all derived from lidar data collected on small, uncrewed aircraft systems (sUAS) at study areas in the Upper Colorado River Basin, Colorado, from 2020 to 2022. These data were collected and generated as part of the U.S. Geological Survey's (USGS) Next Generation Water Observing Systems (NGWOS) Upper Colorado River Basin project.

  17. 2019-2021 USGS Lidar: Alameda County Lidar

    • fisheries.noaa.gov
    not applicable
    Updated Dec 22, 2021
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    OCM Partners (2021). 2019-2021 USGS Lidar: Alameda County Lidar [Dataset]. https://www.fisheries.noaa.gov/inport/item/71712
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    not applicableAvailable download formats
    Dataset updated
    Dec 22, 2021
    Dataset provided by
    OCM Partners, LLC
    Time period covered
    Jul 2, 2019 - Jul 2, 2021
    Area covered
    Description

    This metadata reflects the combination of three lidar collections over Alameda County, CA. These are: 1) a 2019 QL1 collection upgraded to 3DEP specifications; 2) a 2021 QL1 collection; and 3) a 2021 QL0 collection. Each dataset has an Entwine Point Tile version that makes the data accessible by the Digital Coast Data Access Viewer. This metadata is to support that use by the Data Access Viewer...

  18. Wisconsin DEM and Hillshade from LiDAR - Web Map

    • hub.arcgis.com
    • data-wi-dnr.opendata.arcgis.com
    • +1more
    Updated Jan 17, 2019
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    Wisconsin Department of Natural Resources (2019). Wisconsin DEM and Hillshade from LiDAR - Web Map [Dataset]. https://hub.arcgis.com/maps/wi-dnr::wisconsin-dem-and-hillshade-from-lidar-web-map/about
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    Dataset updated
    Jan 17, 2019
    Dataset authored and provided by
    Wisconsin Department of Natural Resourceshttp://dnr.wi.gov/
    Area covered
    Description

    Web map displaying Wisconsin DNR-produced Digital Elevation Model (DEM) and Hillshade image services, along with their index layer, in formats that are clickable and can be symbolized and filtered. This map can also be used as a starting point to create a new map. To open the web map from DNR's GIS Open Data Portal, click the View Metadata: link to the right of the description, then click Open in Map Viewer.

  19. a

    Data from: LIDAR Data

    • data-peoriacountygis.opendata.arcgis.com
    Updated May 29, 2018
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    County of Peoria (2018). LIDAR Data [Dataset]. https://data-peoriacountygis.opendata.arcgis.com/documents/8eb2e37088d94f7e93f81667a1d4f00e
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    Dataset updated
    May 29, 2018
    Dataset authored and provided by
    County of Peoria
    License

    https://data-peoriacountygis.opendata.arcgis.com/pages/peoria-county-gis-open-data-license-agreementhttps://data-peoriacountygis.opendata.arcgis.com/pages/peoria-county-gis-open-data-license-agreement

    Description

    This zip file contains LIDAR, Digital Terrain Models (DTM's), surface, and breakline datasets covering the extent of Peoria County. The LIDAR data was captured during spring leaf-off in 2008. There are eight databases in Esri's file geodatabase format which are broken down by eight areas in the County. The DTM's conform to the ASPRS Class I Standards using the Illinois State Plane West coordinate system. Please contact us if you would like a copy of the data.More recent LIDAR data for Peoria County, IL was captured in 2012 by the State of Illinois through the Illinois Height Modernization Program (ILHMP). Please click Here to read about the program and data available for download.Contact InformationPeoria County GISEmail: gis@peoriacounty.orgPhone: 309-495-4840This data is bound to the Peoria County GIS Open Data License Agreement which can be found here: https://data-peoriacountygis.opendata.arcgis.com/pages/peoria-county-gis-open-data-license-agreement.

  20. 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 ...

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UConn Center for Land use Education and Research (2020). Connecticut 3D Lidar Viewer [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/788d121c4a1f4980b529f914c8df19f4

Connecticut 3D Lidar Viewer

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Dataset updated
Jan 8, 2020
Dataset authored and provided by
UConn Center for Land use Education and Research
Description

Statewide 2016 Lidar points colorized with 2018 NAIP imagery as a scene created by Esri using ArcGIS Pro for the entire State of Connecticut. This service provides the colorized Lidar point in interactive 3D for visualization, interaction of the ability to make measurements without downloading.Lidar is referenced at https://cteco.uconn.edu/data/lidar/ and can be downloaded at https://cteco.uconn.edu/data/download/flight2016/. Metadata: https://cteco.uconn.edu/data/flight2016/info.htm#metadata. The Connecticut 2016 Lidar was captured between March 11, 2016 and April 16, 2016. Is covers 5,240 sq miles and is divided into 23, 381 tiles. It was acquired by the Captiol Region Council of Governments with funding from multiple state agencies. It was flown and processed by Sanborn. The delivery included classified point clouds and 1 meter QL2 DEMs. The 2016 Lidar is published on the Connecticut Environmental Conditions Online (CT ECO) website. CT ECO is the collaborative work of the Connecticut Department of Energy and Environmental Protection (DEEP) and the University of Connecticut Center for Land Use Education and Research (CLEAR) to share environmental and natural resource information with the general public. CT ECO's mission is to encourage, support, and promote informed land use and development decisions in Connecticut by providing local, state and federal agencies, and the public with convenient access to the most up-to-date and complete natural resource information available statewide.Process used:Extract Building Footprints from Lidar1. Prepare Lidar - Download 2016 Lidar from CT ECO- Create LAS Dataset2. Extract Building Footprints from LidarUse the LAS Dataset in the Classify Las Building Tool in ArcGIS Pro 2.4.Colorize LidarColorizing the Lidar points means that each point in the point cloud is given a color based on the imagery color value at that exact location.1. Prepare Imagery- Acquire 2018 NAIP tif tiles from UConn (originally from USDA NRCS).- Create mosaic dataset of the NAIP imagery.2. Prepare and Analyze Lidar Points- Change the coordinate system of each of the lidar tiles to the Projected Coordinate System CT NAD 83 (2011) Feet (EPSG 6434). This is because the downloaded tiles come in to ArcGIS as a Custom Projection which cannot be published as a Point Cloud Scene Layer Package.- Convert Lidar to zlas format and rearrange. - Create LAS Datasets of the lidar tiles.- Colorize Lidar using the Colorize LAS tool in ArcGIS Pro. - Create a new LAS dataset with a division of Eastern half and Western half due to size limitation of 500GB per scene layer package. - Create scene layer packages (.slpk) using Create Cloud Point Scene Layer Package. - Load package to ArcGIS Online using Share Package. - Publish on ArcGIS.com and delete the scene layer package to save storage cost.Additional layers added:Visit https://cteco.uconn.edu/projects/lidar3D/layers.htm for a complete list and links. 3D Buildings and Trees extracted by Esri from the lidarShaded Relief from CTECOImpervious Surface 2012 from CT ECONAIP Imagery 2018 from CTECOContours (2016) from CTECOLidar 2016 Download Link derived from https://www.cteco.uconn.edu/data/download/flight2016/index.htm

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