WARNING TO USERS OF THIS SYSTEM This computer system, including all related equipment, networks, and network devices (including Internet access), is provided by the Department of the Interior (DOI) in accordance with the agency policy for official use and limited personal use. All agency computer systems may be monitored for all lawful purposes, including but not limited to, ensuring that use is authorized, for management of the system, to facilitate protection against unauthorized access, and to verify security procedures, survivability and operational security. Any information on this computer system may be examined, recorded, copied and used for authorized purposes at any time. All information, including personal information, placed or sent over this system may be monitored, and users of this system are reminded that such monitoring does occur. Therefore, there should be no expectation of privacy with respect to use of this system. By logging into this agency computer system, you acknowledge and consent to the monitoring of this system. Evidence of your use, authorized or unauthorized, collected during monitoring may be used for civil, criminal, administrative, or other adverse action. Unauthorized or illegal use may subject you to prosecution. Minnesota Metro Region LiDAR Acquisition (1.5 meter Nominal Post Spacing)

Minnesota Metro Region LiDAR Acquisition (1.5 meter Nominal Post Spacing)

Metadata also available as

Frequently-anticipated questions:

What does this data set describe?

Title:
Minnesota Metro Region LiDAR Acquisition (1.5 meter Nominal Post Spacing)
Abstract:
Fugro Horizons Inc aquired LiDAR with Leica sensor ALS50-II MPiA for the Minnesota Metro Region. The region that was collected at 1.5m LiDAR post spacing covers Morrison, Mille Lacs, Benton, Isanti, Sherburne, Anoka, Meeker, Hennepin, Washington, Carver, Scott, and Goodhue counties. Acquisition was planned between spring and fall 2011, with some reflights spring 2012. The LiDAR sensor settings included acquisition at 6,600' AMT, 130 knots, pulse rate 99,500Hz, scan rate 27.28Hz, 40 degree field of view, 4,805ft swath width, maximum along track spacing (occurs at FOV edge) of 2.45m in overlap areas, maximum cross track spacing (occurs at Nadir) 1.24m, 3sigma post spacing of 1.4m and 3sigma point density of 0.65 points per square meter. This sensor was also equipped with IPAS inertial measuring unit (IMU) and a dual frequency airborne GPS receiver. These settings were used to meet or exceed the following accuracy specification in flat areas with minimal vegetation. 24.5cm ACCz, 95% (12.5cm RMSEz) 29.4cm ACCz, 95% (15.0cm RMSEz) 29.4cm ACCz 95% (15.0cm RMSEz) Deliverables for the LiDAR are in UTM15N NAD83/HARN NAVD88 Geiod09 meters *******DELIVERABLE OVERVIEW***** Each geodatabase is named for its respective USGS quarter-quarter quad name. Every geodatabase contains a feature dataset called "terrain_data". The terrain_data feature dataset contains up to two feature classes; Bare_Earth_Points and Hydro_Breaklines (when applicable). The Bare-Earth_Points feature class is comprised of MultipointZ shapefiles extracted from the Ground and KeyPoint LAS files. Both the Bare_Earth_Points and Hydro-Breaklines have been clipped to the USGS quarter-quarter quad extent. Each geodatabase also contains a DEM. The DEM was created from a terrain using bare-earth multipoint PointZ and hydro-breaklines. The Terrain was then converted to a Raster DEM using a 1-meter cell-size, then clipped to an adjusted, quarter-quarter quad minimum-bounding- rectangle and buffered an additional 50 meters. The naming convention for all DEMs is "DEM01". LAS files are clipped to the provided USGS quarter-quarter quad. 1 - unclassified 2 - ground 3 - low veg 4 - med. veg 5 - high veg 6 - building 7 - noise 8 - keypoint 9 - water 10 - water edge (withheld / ignored ground) 11 - Scan edge (unreliable points near the extreme edge of swath) 12 - Overlap (NOT USED) 14 - bridge Water edges were created using proprietary processes to create an accurate 3D representation of water features. Further hands-on evaluations are performed to ensure compliance with USGS V13 regarding Hydro-Flattening. Once the waterbodies are finalized, LAS bare-earth points within the extents of the water polygons are classified to Class 9 (Water). Bare-earth points within 1-meter of the water polygons are re-classified to Class 10 (Ignored Class). ACQUISITION DATES LiDAR Block A - 5-11-11 to 5-15-11 LiDAR Block B - 5-11-11 to 5-15-11 LiDAR Block C - 5-10-11 LiDAR Block D - 4-29-11 to 5-8-11 LiDAR Block E - 4-25-11 LiDAR Block F - 11-13-11 to 11-17-11, reflight 3-25-12 LiDAR Block G - 11-11-11 to 11-12-11, reflight 3-24-12 LiDAR Block H - 11-12-11 to 11-13-11, reflight 3-28-12 LiDAR Block X - 4-25-11 to 11-15-11, reflight 3-24-12 to 3-28-12
Supplemental_Information:
The Minnesota Department of Natural Resources works to integrate and sustain the interdependent values of a healthy environment, a sustainable economy, and livable communities. DNR’s integrated resource management strategy shares stewardship responsibility with citizens and partners to manage for multiple interests. DNR protects the state’s natural heritage by conserving the diversity of natural lands, waters, and fish and wildlife that provide the foundation for Minnesota’s recreational and natural resource-based economy (M.S. 84, M.S. 97A). DNR manages natural lands such as forests, wetlands, and native prairies; maintains healthy populations of fish and wildlife; and protects rare plant and animal communities throughout the state. DNR manages the state’s water resources, sustaining healthy waterways and ground water resources. DNR provides access to enrich public outdoor recreational opportunities, such as hunting, fishing, wildlife-watching, camping, skiing, hiking, biking, motorized recreation, and conservation education through a state outdoor recreation system that includes parks, trails, wildlife management areas, scientific and natural areas, water trails, and other facilities (M.S. 86A). DNR supports natural resource-based economies, managing state forest lands for multiple forest values (M.S. 89), ensuring the maximum long-term economic return from school trust lands (M.S. 127A), and providing other economic opportunities in a manner consistent with sound natural resource conservation and management principles.
  1. How should this data set be cited?

    Minnesota Department of Natural Resources, 20120000, Minnesota Metro Region LiDAR Acquisition (1.5 meter Nominal Post Spacing): Minnesota Department of Natural Resources, Minnesota Department of Natural Resources.

    Online Links:

  2. What geographic area does the data set cover?

    West_Bounding_Coordinate: +094.714600
    East_Bounding_Coordinate: +092.120234
    North_Bounding_Coordinate: +46.395540
    South_Bounding_Coordinate: +44.211950

  3. What does it look like?

    None (None)
    None

  4. Does the data set describe conditions during a particular time period?

    Beginning_Date: 25-Apr-2011
    Ending_Date: 28-Mar-2012
    Currentness_Reference: Publication Date

  5. What is the general form of this data set?

    Geospatial_Data_Presentation_Form: remote-sensing image

  6. How does the data set represent geographic features?

    1. How are geographic features stored in the 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: 15
      Transverse_Mercator:
      Scale_Factor_at_Central_Meridian: 0.9996
      Longitude_of_Central_Meridian: +093.000000
      Latitude_of_Projection_Origin: 0.0
      False_Easting: 500000
      False_Northing: 0.0

      Planar coordinates are encoded using row and column
      Abscissae (x-coordinates) are specified to the nearest .001
      Ordinates (y-coordinates) are specified to the nearest .001
      Planar coordinates are specified in Meters

      The horizontal datum used is North American Datum of 1983/HARN adjustment.
      The ellipsoid used is Geodetic Reference System 80 (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: North American Vertical datum of 1988 Geoid09
      Altitude_Resolution: .001
      Altitude_Distance_Units: Meters
      Altitude_Encoding_Method: Implicit coordinate
      Depth_System_Definition:
      Depth_Datum_Name: No correction
      Depth_Resolution: .001
      Depth_Distance_Units: Meters
      Depth_Encoding_Method: Implicit coordinate

  7. How does the data set describe geographic features?

    Entity_and_Attribute_Overview:
    1.5m LiDAR acquisition and processing for Minnesota Department of Natural Resources and supporting partners.
    Entity_and_Attribute_Detail_Citation: None

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)

    • Minnesota Department of Natural Resources

  2. Who also contributed to the data set?

  3. To whom should users address questions about the data?

    Minnesota Department of Natural Resources
    DNR Central Office
    500 Lafayette Road
    St. Paul, MN 55155-4040
    USA

    (651) 296-6157 (voice)
    info.dnr@state.mn.us

    Hours_of_Service: 8am to 5pm Central Time
    Contact_Instructions: <http://www.dnr.state.mn.us/index.html>

Why was the data set created?

The mission of the Minnesota Department of Natural Resources (DNR) is to work with citizens to conserve and manage the state's natural resources, to provide outdoor recreation opportunities, and to provide for commercial uses of natural resources in a way that creates a sustainable quality of life. One of the products of this effort is 1.5m average post spacing LiDAR and its derivatives.

How was the data set created?

  1. From what previous works were the data drawn?

    Georectifed LiDAR data sets (source 1 of 1)
    Minnesota Department of Natural Resources, 20120000, <http://www.dnr.state.mn.us/>.

    Online Links:

    Type_of_Source_Media: Digital copy
    Source_Contribution: Digital Georectifed LiDAR.

  2. How were the data generated, processed, and modified?

    Date: 2010 (process 1 of 1)
    The data set for each flight line was checked for project area coverage, data gaps between overlapping flight lines, and tension/compression areas (areas where data points are more or less dense that the average project specified post spacing). Using an iterative process that involves analyzing raster difference calculations the omega, phi, kappa angle corrections for the LiDAR instrument were determined. Corrections were applied to the LiDAR data set. Extensive comparisons were made of vertical and horizontal positional differences between points common to two or more LiDAR flight lines. An intensity raster for each flight line was generated and verified that intensity was recorded for each LiDAR point. LiDAR ground points were compared to independently surveyed and positioned ground control points in the project area. Based on the results of these comparisons, the LiDAR data was vertically biased to the ground. (1) PRE-PROCESSING STAGE LiDAR, GPS and IMU data are processed together using LiDAR processing software. The LiDAR data set for each flight line is checked for project area coverage and LiDAR post spacing is checked to ensure it meets project specifications. The LiDAR collected at the calibration area is used to correct the rotational, atmospheric, and vertical elevation differences that are inherent to LiDAR data. Intensity raster is generated to verify that intensity was recorded for each LiDAR point. LiDAR data is transformed to the specified project coordinate system. By utilizing the ground survey data collected at the calibration site and project area, the LiDAR data is vertically biased to the ground. Comparisons between the biased LiDAR data and ground survey data within the project area are evaluated and a final RMSE value is generated to ensure the data meets project specifications.

  3. What similar or related data should the user be aware of?

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

  1. How well have the observations been checked?

    GPS phase data was post processed with continuous kinematic survey techniques using "On the Fly" (OTF) integer ambiguity resolution. The GPS data was rocessed with forward and reverse processing algorithms. The results from each process, using the data collected at the airport and in project area, were combined to yield a single fixed integer phase differential solution of the aircraft trajectory. The differences between the forward to reverse solution within the project area were within project specifications, indicating a valid and accurate solution. An IMU was used to record precise changes in position and orientation of the LIDAR scanner at a rate of 200 Hz. All IMU data was processed post flight with a filter to integrate inertial measurements and precise phase differential GPS positions. The resulting solution contains geodetic position, omega, phi, kappa, and time for subsequent merging with the laser ranging information.

  2. How accurate are the geographic locations?

    Meets or exceeds horizontal accuracy of 0.6m RMSE.

  3. How accurate are the heights or depths?

    Vertical Accuracy of the lidar data will be assessed and reported in accordance with the guidelines developed by the NDEP and subsequently adopted by the ASPRS. The complete guidelines may be found in Section 1.5 of the //www.ndep.gov/NDEP_Elevation_Guidelines_Ver1_ 10May2004.pdf Vertical accuracy requirements using the NDEP/ASPRS Sub-Project A 24.5cm ACCz, 95% (12.5cm RMSEz) 29.4cm ACCz, 95% (15.0cm RMSEz) 29.4cm ACCz 95% (15.0cm RMSEz)

  4. Where are the gaps in the data? What is missing?

    Complete

  5. How consistent are the relationships among the observations, including topology?

    All deliverables were quality checked by MN DNR and passed.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?

Access_Constraints: There are no limitations for access.
Use_Constraints:
None other than Minnesota Department of Natural Resources and supporting partners ask to be credited in any derived products or services.

  1. Who distributes the data set? (Distributor 1 of 1)

    TBD
    TBD
    TBD, TBD TBD
    USA

    TBD (voice)

    Hours_of_Service: 8am to 5pm Central Time
    Contact_Instructions: TBD
  2. What's the catalog number I need to order this data set?

  3. What legal disclaimers am I supposed to read?

    In no event shall the creators, custodians, or distributors of this information be liable for any damages arising out of its use (or the inability to use it).

  4. How can I download or order the data?

Who wrote the metadata?

Dates:
Last modified: 2011
Metadata author:
Minnesota Department of Natural Resources
DNR Central Office
500 Lafayette Road
St. Paul, MN 55155-4040
USA

(651) 296-6157 (voice)

Hours_of_Service: 8am to 5pm Central Time
Contact_Instructions: info.dnr@state.mn.us
Metadata standard:
FGDC Content Standards for Digital Geospatial Metadata (FGDC-STD-001-1998)

Generated by mp version 2.9.0 on Tue Feb 12 15:25:38 2013