4 datasets found
  1. DEM, DSM, and Cleaned LiDAR Point Cloud Data from the NGEE Arctic UAS...

    • osti.gov
    • search.dataone.org
    • +1more
    Updated Mar 7, 2024
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    U.S. DOE > Office of Science > Biological and Environmental Research (BER) (2024). DEM, DSM, and Cleaned LiDAR Point Cloud Data from the NGEE Arctic UAS Campaigns at the Teller 27 Field Site from 2017 and 2018, Seward Peninsula, Alaska [Dataset]. http://doi.org/10.5440/2217322
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    Dataset updated
    Mar 7, 2024
    Dataset provided by
    United States Department of Energyhttp://energy.gov/
    Next Generation Ecosystems Experiment - Arctic, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US)
    Area covered
    Arctic, Alaska, Seward Peninsula
    Description

    A Digital Elevation Model (DEM) and Digital Surface Model (DSM) were derived from airborne Light Detection and Ranging (LiDAR) data collected from Los Alamos National Laboratory's (LANL) heavy-lift unoccupied aerial system (UAS) quadcopter and hexacopter platforms operated by Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) scientists from the EES-14 group at LANL. These data were collected in August 2017 and July 2018 at the NGEE Arctic field site near mile marker 27 of the Bob Blodgett Nome-Teller Memorial Highway between Nome, Alaska and Teller, Alaska. A Vulcan Raven X8 Airframe (Mitcheldean, Gloucestershire, UK), DJI Matrice 600 Pro Airframe (Shenzhen, China), and Routescene UAV LiDARSystem (Edinburgh, Scotland, UK) were used to collect LiDAR data. Following pre-processing in Routescene LidarViewer Pro software, the LiDAR point clouds were cleaned and processed using CloudCompare software to separate ground and off-ground points. A high resolution DEM and DSM were then created using ArcGIS Pro software. This data package contains fully cleaned point clouds of ground and off-ground points (.las), a 25 cm DEM (.tif), and a 25 cm DSM (.tif) for the Teller 27 field site. Ancillary aircraft data, flight mission parameters, weather conditions, and raw lidar data and imagery can be found in the L0 datasets for these campaigns: NGA299 (2017) and NGA297 (2018). Minimally processed point clouds and auxiliary files can be found in the L1 dataset: NGA304 (2017 and 2018).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

  2. a

    2022 Building Footprints

    • hamhanding-dcdev.opendata.arcgis.com
    • private-demo-dcdev.opendata.arcgis.com
    • +2more
    Updated May 8, 2023
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    Douglas County (2023). 2022 Building Footprints [Dataset]. https://hamhanding-dcdev.opendata.arcgis.com/maps/dogis::2022-building-footprints-1
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    Dataset updated
    May 8, 2023
    Dataset authored and provided by
    Douglas County
    Area covered
    Description

    2022 Douglas County building footprints. This data was created using QL1 LiDAR classified point cloud (.LAS) captured by VeriDaas between April 4-17th 2022. ArcGIS Pro 3.x was used to process the 2022 building footprints. After the footprints were created, all polygons less than 64 square feet were deleted. All larger buildings that were inside a commercial or industrial parcel were examined to make sure HVAC artifacts were removed from the building footprint.

  3. n

    Merced Vernal Pools and Grassland Reserve sUAS-LiDAR High Resolution...

    • data.niaid.nih.gov
    • datadryad.org
    zip
    Updated Oct 27, 2020
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    Michael Kalua; Joshua Viers; Andreas Anderson (2020). Merced Vernal Pools and Grassland Reserve sUAS-LiDAR High Resolution 0.25-meter DEM [Dataset]. http://doi.org/10.6071/M33D4N
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    zipAvailable download formats
    Dataset updated
    Oct 27, 2020
    Dataset provided by
    University of California, Merced
    Authors
    Michael Kalua; Joshua Viers; Andreas Anderson
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    Merced
    Description

    The Merced Vernal Pools and Grassland Reserve is 6,500 acres of protected habitat adjacent to the University of California Merced containing rare and endangered species and a unique seasonal wetland habitat. These data were gathered to be used for hydrological modelling on the Reserve for potential restoration projects and to be made public for other researchers who may find very high resolution topographical information useful for their work. This dataset contains a Digital Elevation Model created from 8 field survey days of Aerial LiDAR Scanning (ALS) with a small Unmanned Aerial System (sUAS).

    Methods Work Completed by Researchers at University of California, Merced under the direction of Dean/Director/Professor Joshua H. Viers | Vicelab and CITRIS Aviation

    Spatial Reference: WGS 1984 UTM Zone 10N / WGS84 Geoid

    Units: Meters

    Equipment: DJI M600 Pro with Phoenix Aerial Systems AL3-32 LiDAR

    Software: Phoenix LiDAR Systems SpatialSuite 4.0.3, LasTools, ArcGIS Pro 2.4, Litchi, ArduPilot Mission Planner

    Field Crew/Processing: Michael Kalua (sUAS Pilot/Mission Planning/Sensor Operator/Data Processing), Andreas Anderson (sUAS Pilot/Mission Planning/Sensor Operator), Daniel Gomez (Sensor Operator), Hayden Namgostar (Sensor Operator)

    Field Methods: An RTK reference station was set up before each field day over a previously-surveyed benchmark near the entrance of the Reserve, which would continuously send RTK corrections to the LiDAR system over an internet connection service. Before flight the LiDAR system was allowed at least 15 minutes to reach thermal equilibrium and for the onboard Intertial Measurement Unit (IMU) to get a fix on the sensor's position and attitude. At the beginning of each set of flights the Pilot in Command (PIC) would perform a manual takeoff and IMU calibration maneuvers (straight-and-level flight and figure-eights) as per Phoenix LiDAR System's recommended procedures. Once the manuevers were completed and the Sensor Operator determined IMU attitude and position uncertainties were below threshold (0.003- typical values ranged an order of magnitude lower) the PIC would begin the automated waypoint mission via Litchi. During flight, the Sensor Operator would ensure the scanner was operational, that the IMU uncertainties were below margin, and address any potential error messages. In the event of errors, the PIC would bring the sUAS back and the section would be re-surveyed after the issues were addressed.

    Processing Methods: The raw flightlines were fused using Phoenix SpatialExplorer 4.0.3 to include only the straight-and-level flightlines over the region of interest. The output were individual flightline .las point clouds conforming to LAS 1.4 format. These flightlines were then passed through a noise filter using LasNoise to remove any "birds" or unwanted noise. Using LasTools these noise-removed flightlines were then tiled, classified into ground/non-ground points, and rasterized into 0.25-meter Digital Surface Models (DSM) containing all points and Bare-Earth Digital Elevation Models (DEM) containing only ground-classified points. These tiled raster outputs were then mosiaced together in ArcGIS Pro.

    Please reach out to Michael Kalua (mkalua@ucmerced.edu) for any questions about this dataset.

  4. Orthomosaic and digital surface model of the main Casey station buildings,...

    • researchdata.edu.au
    • cmr.earthdata.nasa.gov
    • +1more
    Updated Mar 19, 2021
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    METS, JOHAN; WILKINS, DANIEL; MCWATTERS, REBECCA; HELLIE, ANNE; Hellie, A., Mcwatters, R., Mets, J. and Wilkins, D.; WILKINS, DANIEL (2021). Orthomosaic and digital surface model of the main Casey station buildings, 12th February 2021. [Dataset]. https://researchdata.edu.au/orthomosaic-digital-surface-february-2021/1695852
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    Dataset updated
    Mar 19, 2021
    Dataset provided by
    Australian Antarctic Divisionhttps://www.antarctica.gov.au/
    Australian Antarctic Data Centre
    Authors
    METS, JOHAN; WILKINS, DANIEL; MCWATTERS, REBECCA; HELLIE, ANNE; Hellie, A., Mcwatters, R., Mets, J. and Wilkins, D.; WILKINS, DANIEL
    License

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

    Time period covered
    Feb 12, 2021
    Area covered
    Description

    Images were acquired from approximately 80 m above ground surface on the 12th of February 2021, using a Phantom 4 Advanced drone with an FC330 camera. The images are in file input_images.zip.

    The mission planning software DJI GS Pro was used to automatically acquire images at suitable locations across the survey area to enable the reconstruction of a three dimensional model.

    Images 422 to 531 were imported to the photogrammetry software Pix4D (version 4.6.4). The created Pix4D project is Station12Feb2021_limited.p4d, and the processing report is Station12Feb2021_limited_report.pdf.

    Four three-dimensional ground control points were used to improve the positioning of the model. No two dimensional control points or check points were used.

    These points were in ITRF 2000@2000 datum (UTM Zone 49S), with co-ordinates as per the table below:

    Label, Type, X(m), Y(m), Z(m), Accuracy Horz(m), Accuracy Vert(M)
    BM05, 3D GCP, 478814.460, 2648561.910, 38.558, 0.050, 0.100
    EW-05, 3D GCP, 478635.540, 2648617.260, 27.260, 0.050, 0.100
    FuelFlange, 3D GCP, 478970.810, 2648642.250, 21.920, 0.050, 0.100
    MeltbellFootingA, 3D GCP, 478680.270, 2648466.547, 35.850, 0.050, 0.100

    BM-05 is a survey benchmark near the Casey flagpoles, see https://data.aad.gov.au/aadc/survey/display_station.cfm?station_id=600
    EW-05 is a 44 gallon drum used as a groundwater extraction well by the remediation project
    Fuel Flange is the last fuel flange located on the elevated fuel line prior to the fuel line “dipping” under the wharf road.
    Meltbell footing A is a concrete footing for the Casey melt bell (surveyed in 2019/20).

    No point cloud processing (e.g. removal of errant points) was done prior to orthomosaic and model generation.

    The resulting orthomosaic (Station12Feb2021_limited_transparent_mosaic_group1.tif) has an average ground sampling distance of 2.9 cm, and covers an area of approximately 15.8 hectares, encompassing the majority of buildings along “main street” at Casey. The quarry, biopiles, helipad, and upper fuel farm area are all visible.

    Contour lines were generated in Pix4D at 0.5 m intervals.

    Due to the limited number of ground control points, and their imprecision, the estimated residual mean squared error across three dimensions is 0.17 m (17cm), and will be worse on the periphery of the imaged area.

    The orthomosaic was exported from ArcGIS to a Google Earth file (CaseyStation Orthomosaic Feb 12 2021.kmz) using XTools Pro Version 17.2.

    A map was created in ArcGIS showing the orthomosaic with a background showing contour lines obtained from the AADC data product windmill_is.mdb.

    The map was exported in .jpg and .pdf format at 250 dpi.
    Casey Station Orthomosaic Feb 12 2021.pdf
    Casey Station Orthomosaic Feb 12 2021.jpg

    The Pix4D folder structure has been copied across (with the exception of the temp folder) and is included in this dataset.

    Pix4D Folder Structure:

    Station12Feb2021_limited.zip
    1_intitial
    • Contains Pix4D files created during the project
    • Contains the final processing report (as .pdf)
    2_densification
    • Contains the 3D mesh as an .obj file
    • Contains the point cloud as a .LAS and .PLY file
    • Contains the point cloud as a .p4b file
    3_dsm_ortho
    • Contains the digital surface model as a georeferenced .tif file
    • Contains the orthomosaic as a georeferenced .tif file

    A text readable log file from the project processing is in the file Station12Feb2021_limited.log

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U.S. DOE > Office of Science > Biological and Environmental Research (BER) (2024). DEM, DSM, and Cleaned LiDAR Point Cloud Data from the NGEE Arctic UAS Campaigns at the Teller 27 Field Site from 2017 and 2018, Seward Peninsula, Alaska [Dataset]. http://doi.org/10.5440/2217322
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DEM, DSM, and Cleaned LiDAR Point Cloud Data from the NGEE Arctic UAS Campaigns at the Teller 27 Field Site from 2017 and 2018, Seward Peninsula, Alaska

Explore at:
Dataset updated
Mar 7, 2024
Dataset provided by
United States Department of Energyhttp://energy.gov/
Next Generation Ecosystems Experiment - Arctic, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US)
Area covered
Arctic, Alaska, Seward Peninsula
Description

A Digital Elevation Model (DEM) and Digital Surface Model (DSM) were derived from airborne Light Detection and Ranging (LiDAR) data collected from Los Alamos National Laboratory's (LANL) heavy-lift unoccupied aerial system (UAS) quadcopter and hexacopter platforms operated by Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) scientists from the EES-14 group at LANL. These data were collected in August 2017 and July 2018 at the NGEE Arctic field site near mile marker 27 of the Bob Blodgett Nome-Teller Memorial Highway between Nome, Alaska and Teller, Alaska. A Vulcan Raven X8 Airframe (Mitcheldean, Gloucestershire, UK), DJI Matrice 600 Pro Airframe (Shenzhen, China), and Routescene UAV LiDARSystem (Edinburgh, Scotland, UK) were used to collect LiDAR data. Following pre-processing in Routescene LidarViewer Pro software, the LiDAR point clouds were cleaned and processed using CloudCompare software to separate ground and off-ground points. A high resolution DEM and DSM were then created using ArcGIS Pro software. This data package contains fully cleaned point clouds of ground and off-ground points (.las), a 25 cm DEM (.tif), and a 25 cm DSM (.tif) for the Teller 27 field site. Ancillary aircraft data, flight mission parameters, weather conditions, and raw lidar data and imagery can be found in the L0 datasets for these campaigns: NGA299 (2017) and NGA297 (2018). Minimally processed point clouds and auxiliary files can be found in the L1 dataset: NGA304 (2017 and 2018).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

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