Lidar-derived snow surface elevation data for Deadhorse, northern Alaska, collected May 10, 2022

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Frequently anticipated questions:


What does this data set describe?

Title:
Lidar-derived snow surface elevation data for Deadhorse, northern Alaska, collected May 10, 2022
Abstract:
Lidar-derived snow surface elevation data for Deadhorse, northern Alaska, collected May 10, 2022, Raw Data File 2024-13, provides aerial lidar-derived classified classified point cloud, digital surface model (DSM), digital terrain model (DTM), and an intensity model of Deadhorse, Northern Alaska, during during peak snowpack conditions. The survey provides snow surface elevations for use in snowpack assessment. Aerial lidar data and ground control data were collected on May 10, 2022, and subsequently merged and processed using a suite of geospatial processing software. This data collection is released as a Raw Data File with an open end-user license. All files can be downloaded from the Alaska Division of Geological & Geophysical Surveys website (http://doi.org/10.14509/31259).
Supplemental_Information:
boundaries:    A boundary, also known as an Area of Interest (AOI) or border, that defines the area covered by the data. Also includes footprints for tiled data.	
classified_points:    Classified point cloud data are provided in LAZ format. Data are classified following ASPRS 2019 guidelines and contain return and intensity information. For classified ground points, the average point density is 4.90 pts/m2, and the average spacing is 45.2 cm.	
dsm:    The DSM represents surface elevations, including heights of vegetation, buildings, powerlines, pipelines, bridge decks, etc. The DSM is a single-band, 32-bit GeoTIFF file of 50-cm resolution. No Data value is set to -3.40282306074e+38 (32-bit, floating-point minimum).	
dtm:    The DTM represents bare earth elevations, excluding vegetation, bridge decks, buildings, powerlines, etc. The DTM is a single-band, 32-bit GeoTIFF file of 50-cm resolution. No Data value is set to -3.40282306074e+38.	
lidar_intensity:    The lidar intensity image describes the relative amplitude of reflected signals contributing to the point cloud. Lidar intensity is (1) primarily a function of scanned object reflectance in relation to the signal frequency, (2) dependent on ambient conditions, and (3) not necessarily consistent between separate scans. The intensity image is a single-band, 32-bit GeoTIFF file of 50-cm resolution. No Data value is set to -3.40282306074e+38.
  1. How might this data set be cited?
    Zechmann, J.M., Daanen, R.P., Salisbury, J.B., and Wolken, G.J., 2024, Lidar-derived snow surface elevation data for Deadhorse, northern Alaska, collected May 10, 2022: Raw Data File RDF 2024-13, Alaska Division of Geological & Geophysical Surveys, Fairbanks, Alaska, United States.

    Online Links:

    Other_Citation_Details: 9 p.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -148.661363
    East_Bounding_Coordinate: -148.332445
    North_Bounding_Coordinate: 70.309062
    South_Bounding_Coordinate: 70.163330
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 10-May-2022
    Currentness_Reference:
    ground condition
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: data
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
      This is a raster data set.
    2. What coordinate system is used to represent geographic features?
      Grid_Coordinate_System_Name: Universal Transverse Mercator
      Universal_Transverse_Mercator:
      UTM_Zone_Number: 6
      Transverse_Mercator:
      Scale_Factor_at_Central_Meridian: 0.999600
      Longitude_of_Central_Meridian: -147
      Latitude_of_Projection_Origin: 0
      False_Easting: 500000.000000
      False_Northing: 0
      Planar coordinates are encoded using coordinate pair
      Abscissae (x-coordinates) are specified to the nearest .00000001
      Ordinates (y-coordinates) are specified to the nearest .00000001
      Planar coordinates are specified in Meters
      The horizontal datum used is NAD83 (2011).
      The ellipsoid used is GRS 80.
      The semi-major axis of the ellipsoid used is 6378137.
      The flattening of the ellipsoid used is 1/298.257222101.
      Vertical_Coordinate_System_Definition:
      Altitude_System_Definition:
      Altitude_Datum_Name: NAVD88, GEOID12B
      Altitude_Resolution: 0.001
      Altitude_Distance_Units: meters
      Altitude_Encoding_Method:
      Explicit elevation coordinate included with horizontal coordinates
  7. How does the data set describe geographic features?
    boundaries
    A boundary, also known as an Area of Interest (AOI) or border, that defines the area covered by the data. Also includes footprints for tiled data. (Source: DGGS)
    classified_points
    Classified point cloud data are provided in LAZ format. Data are classified following ASPRS 2019 guidelines and contain return and intensity information. For classified ground points, the average point density is 4.90 pts/m2, and the average spacing is 45.2 cm. (Source: DGGS)
    dsm
    The DSM represents surface elevations, including heights of vegetation, buildings, powerlines, pipelines, bridge decks, etc. The DSM is a single-band, 32-bit GeoTIFF file of 50-cm resolution. No Data value is set to -3.40282306074e+38 (32-bit, floating-point minimum). (Source: DGGS)
    dtm
    The DTM represents bare earth elevations, excluding vegetation, bridge decks, buildings, powerlines, etc. The DTM is a single-band, 32-bit GeoTIFF file of 50-cm resolution. No Data value is set to -3.40282306074e+38. (Source: DGGS)
    lidar_intensity
    The lidar intensity image describes the relative amplitude of reflected signals contributing to the point cloud. Lidar intensity is (1) primarily a function of scanned object reflectance in relation to the signal frequency, (2) dependent on ambient conditions, and (3) not necessarily consistent between separate scans. The intensity image is a single-band, 32-bit GeoTIFF file of 50-cm resolution. No Data value is set to -3.40282306074e+38. (Source: DGGS)

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
  2. Who also contributed to the data set?
    This survey area is on the traditional homelands of the Inupiat peoples. A National Science Foundation grant, federal award No, funded this work. ICER-1928237 made to the University of Alaska, with the State of Alaska as a sub-recipient under sub-award number UA 21-0135. We thank Pollux Aviation for their expertise and contribution to these data products. The views and conclusions contained in this document are those of the authors. They should not be interpreted as necessarily representing the official policies, either expressed or implied, of the U.S. Government.
  3. To whom should users address questions about the data?
    Alaska Division of Geological & Geophysical Surveys
    Metadata Manager
    3354 College Road
    Fairbanks, AK
    USA

    (907)451-5020 (voice)
    (907)451-5050 (FAX)
    dggspubs@alaska.gov
    Hours_of_Service: 8 am to 4:30 pm, Monday through Friday, except State holidays
    Contact_Instructions:
    Please view our website (https://www.dggs.alaska.gov) for the latest information on available data. Please contact us using the e-mail address provided above when possible.

Why was the data set created?

The survey provides snow surface elevations for use in snowpack assessment.

How was the data set created?

  1. From what previous works were the data drawn?
  2. How were the data generated, processed, and modified?
    Date: 10-May-2022 (process 1 of 3)
    Ground survey - Ground control points were collected on May 10, 2022. We deployed a Trimble R10 GNSS base receiver to provide a base station occupation and real-time kinematic (RTK) corrections to points we surveyed with a rover Trimble R10 GNSS receiver/Mesa3 controller. A levee along the Sagavanirktok River served as the base station location. We collected 51 ground control points and checkpoints to use for calibration and to assess the vertical accuracy of the point cloud. Checkpoints were collected on bare earth (hardpack, pavement, and gravel).
    Date: 2022 (process 2 of 3)
    Aerial survey - DGGS used a Riegl VUX1-LR laser scanner with a global navigation satellite system (GNSS) and Northrop Grumman LN-200C inertial measurement unit (IMU) integrated by Phoenix LiDAR Systems. The sensor can collect a maximum of 820,000 points per second at a range of 215 m or a minimum of 50,000 points per second at a range of 820 m (ranges assume greater than or equal to 20 percent natural reflectance). The scanner operated with a pulse refresh rate of 200,000-400,000 pulses per second at a scan rate of 100-200 revolutions per second. We used an R-44 helicopter to survey from an elevation of approximately 100-160 m above ground level, at a ground speed of approximately 30 m/s, and with a scan angle set from 80 to 280 degrees. The total survey area covers approximately 100.8 km2. The survey area was accessed by air from Deadhorse Airport. Data collection occurred from 2:50 pm to 5:00 pm (AST). Weather throughout the survey was overcast with light wind.
    Date: 2024 (process 3 of 3)
    Lidar dataset processing - We processed point data in Spatial Explorer for initial filtering and multiple-time-around (MTA) disambiguation. MTA errors, corrected in this process, result from ambiguous interpretations of received pulse time intervals and occur more frequently with higher pulse rates. IMU and GNSS data were processed in Inertial Explorer, and flightline information was integrated with the point cloud in Spatial Explorer. We calibrated the point data at an incrementally precise scale of sensor movement and behavior, incorporating sensor velocity, roll, pitch, and yaw fluctuations throughout the survey. For the lidar data collection, the average pulse density is 6.75 pulses/m2, and the average pulse spacing is 38.5 cm. We created macros in Terrasolid software and classified points in accordance with the American Society for Photogrammetry & Remote Sensing (ASPRS) 2019 guidelines (ASPRS, 2019). Once classified, we applied a geometric transformation and converted the points from ellipsoidal heights to GEOID12B (Alaska) orthometric heights. Raster products were derived from the point cloud in ArcGIS Pro. A 50-cm DSM was interpolated from the maximum ground, vegetation, bridge deck, overhead structure, and building classes using a binning method. A 50-cm DTM was interpolated from all ground-class returns using a binning method and minimum values. We also produced a 50-cm intensity image for the entire area using average binning in ArcGIS Pro, with no normalization or corrections applied.
  3. What similar or related data should the user be aware of?
    Wolken, G.J., Hendricks, K.A., Daanen, R.P., Overbeck, J.R., Stevens, D.S.P., and Masterman, S.S., 2017, Alaska & climate change: Information Circular IC 64, Alaska Division of Geological & Geophysical Surveys, Fairbanks, Alaska, United States.

    Online Links:

    Other_Citation_Details: 2 p
    Zechmann, J.M., Daanen, R.P., and Salisbury, J.B., 2024, Lidar-derived elevation data for Deadhorse, northern Alaska, collected July 16-18, 2021: Raw Data File RDF 2024-15, Alaska Division of Geological & Geophysical Surveys, Fairbanks, Alaska, United States.

    Online Links:

    Other_Citation_Details: 18 p

How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?
    Not applicable
  2. How accurate are the geographic locations?
    Horizontal accuracy was not measured for this collection.
  3. How accurate are the heights or depths?
    We measured a mean offset of +263.2 cm between 26 control points and the point cloud. This offset was reduced to -1.3 cm by applying a constant vertical correction to the lidar point data. We used 25 checkpoints to determine the vertical accuracy of the point cloud ground class using a Triangulated Irregular Network (TIN) approach. The project's vertical accuracy has a root mean square error (RMSE) of 5.7 cm. We evaluated the relative accuracy for this dataset as the interswath overlap consistency and measured it at 4.1 cm RMSE.
  4. Where are the gaps in the data? What is missing?
    This is a full-release dataset. There was no over-collect, and data quality is consistent throughout the survey, save for gaps over bodies of water.
  5. How consistent are the relationships among the observations, including topology?
    DGGS visually inspected the images for data errors such as shifts, seamline mismatches, and water noise overlapping land. Data quality is consistent throughout the survey.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints:
This report, map, and/or dataset is available directly from the State of Alaska, Department of Natural Resources, Division of Geological & Geophysical Surveys (see contact information below).
Use_Constraints:
Any hard copies or published datasets utilizing these datasets shall clearly indicate their source. If the user has modified the data in any way, the user is obligated to describe the types of modifications the user has made. The user specifically agrees not to misrepresent these datasets, nor to imply that changes made by the user were approved by the State of Alaska, Department of Natural Resources, Division of Geological & Geophysical Surveys. The State of Alaska makes no express or implied warranties (including warranties for merchantability and fitness) with respect to the character, functions, or capabilities of the electronic data or products or their appropriateness for any user's purposes. In no event will the State of Alaska be liable for any incidental, indirect, special, consequential, or other damages suffered by the user or any other person or entity whether from the use of the electronic services or products or any failure thereof or otherwise. In no event will the State of Alaska's liability to the Requestor or anyone else exceed the fee paid for the electronic service or product.
  1. Who distributes the data set? (Distributor 1 of 1)
    Alaska Division of Geological & Geophysical Surveys
    Metadata Manager
    3354 College Road
    Fairbanks, AK
    USA

    (907)451-5020 (voice)
    (907)451-5050 (FAX)
    dggspubs@alaska.gov
    Hours_of_Service: 8 am to 4:30 pm, Monday through Friday, except State holidays
    Contact_Instructions:
    Please view our website (https://www.dggs.alaska.gov) for the latest information on available data. Please contact us using the e-mail address provided above when possible.
  2. What's the catalog number I need to order this data set? RDF 2024-13
  3. What legal disclaimers am I supposed to read?
    The State of Alaska makes no expressed or implied warranties (including warranties for merchantability and fitness) with respect to the character, functions, or capabilities of the electronic data or products or their appropriateness for any user's purposes. In no event will the State of Alaska be liable for any incidental, indirect, special, consequential, or other damages suffered by the user or any other person or entity whether from the use of the electronic services or products or any failure thereof or otherwise. In no event will the State of Alaska's liability to the Requestor or anyone else exceed the fee paid for the electronic service or product.
  4. How can I download or order the data?

Who wrote the metadata?

Dates:
Last modified: 02-Jul-2024
Metadata author:
Alaska Division of Geological & Geophysical Surveys
Attn: Simone Montayne
Metadata Manager
3354 College Road
Fairbanks, AK
USA

(907)451-5020 (voice)
(907)451-5050 (FAX)
dggspubs@alaska.gov
Hours_of_Service: 8 am to 4:30 pm, Monday through Friday, except State holidays
Metadata standard:
FGDC Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
Metadata extensions used:

Generated by mp version 2.9.50 on Tue Jul 02 15:22:11 2024