2012 MN DNR Lidar: Duluth Post-Flood

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Bulk download of data files in LAZ format, geographic coordinates, orthometric heights. Note that the vertical datum (hence elevations) of the files here are different than described in this document. They will be in an orthometric datum.

The Data Access Viewer (DAV) allows a user to search for and download elevation, imagery, and land cover data for the coastal U.S. and its territories. The data, hosted by the NOAA Office for Coastal Management, can be customized and requested for free download through a checkout interface. An email provides a link to the customized data, while the original data set is available through a link within the viewer.

This graphic displays the footprint for this lidar data set.

Link to data set report.

Link to the MN DNR Vertical Accuracy Validation Report.

Using Light Detection And Ranging (LiDAR) systems, 154 flight lines of high density data, at a nominal pulse spacing (NPS) of 1.5 meter, were collected over Minnesota counties of Lake, St Louis, Aitkin, Carlton, and Pine (approximately 3,078 sq. miles), along with a 100 meter buffer beyond the project tile boundary. Multiple returns were recorded for each laser pulse along with an intensity value for each return. A total of eleven (11) missions were flown from October 29, 2012 through Novembe 08, 2012. A minimum of three (3) airborne global positioning system (GPS) base stations were used in support of the LiDAR data acquisition. All data for this task order is referenced to UTM 15N, NAD83, NAVD88, in meters. Airborne GPS data was differentially processed and integrated with the post processed IMU data to derive a smoothed best estimate of trajectory (SBET). The SBET was used to reduce the LiDAR slant range measurements to a raw reflective surface for each flight line. The coverage was classified to extract a bare earth digital elevation model (DEM) and separate last returns. In addition to the LAS deliverables, one layer of coverage were delivered in the ArcGrid binary format: bare-earth.

System Parameters for 1.5 NPs:

ALS70 Specifications

Post Spacing (Minimum): 4.92 ft / 1.5 m

AGL (Above Ground Level) average flying height: 7,799 ft / 2,377.1 m

MSL (Mean Sea Level) average flying height: 8,392 ft / 2,557.9m

Average Ground Speed: 150 knots / 172.6 mph

Field of View (full): 40 degrees

Pulse Rate: 115 kHz

Scan Rate: 25 Hz

Side Lap (Minimum): 25%

Optech ALTM Gemini Specifications

Post Spacing (Minimum): 4.92 ft / 1.5 m

AGL (Above Ground Level) average flying height: 6,800 ft / 2,072.6 m

MSL (Mean Sea Level) average flying height: 7,400 ft / 2255.5 m

Average Ground Speed: 150 knots / 172.6 mph

Field of View (full): 40 degrees

Pulse Rate: 100 kHz

Scan Rate: 29 Hz

Side Lap (Minimum): 25%

The ALS70 and Optech Gemini calibration and system performance is verified on a periodic basis using Woolpert's calibration range. The calibration range consists of a large building and runway. The edges of the building and control points along the runway have been located using conventional survey methods. Inertial measurement unit (IMU) misalignment angles and horizontal accuracy are calculated by comparing the position of the building edges between opposing flight lines. The scanner scale factor and vertical accuracy is calculated through comparison of LiDAR data against control points along the runway. Field calibration is performed on all flight lines to refine the IMU misalignment angles. IMU misalignment angles are calculated from the relative displacement of features within the overlap region of adjacent (and opposing) flight lines. The raw LiDAR data is reduced using the refined misalignment angles.

Once the data acquisition and GPS processing phases are complete, the LiDAR data was processed immediately to verify the coverage had no voids. The GPS and IMU data was post processed using differential and Kalman filter algorithms to derive a best estimate of trajectory. The quality of the solution was verified to be consistent with the accuracy requirements of the project.

The individual flight lines were inspected to ensure the systematic and residual errors have been identified and removed. Then, the flight lines were compared to adjacent flight lines for any mismatches to obtain a homogenous coverage throughout the project area. The point cloud underwent a classification process to determine bare-earth points and non-ground points utilizing "first and only" as well as "last of many" LiDAR returns. This process determined The LiDAR LAS files for this task order have been classified into the Default (Class 1), Ground (Class 2), Low Vegetation (Class 3), Medium Vegetation (Class 4), High Vegetation (Class 5)

Buildings (Class 6), Noise (Class 7), Model Keypoints (Class 8), Water (Class 9), Ignored Ground(Class 10), bridges (Class 14), and Overlap (Class 17) classifications. The bare-earth (Class 2 - Ground) LiDAR points underwent a manual QA/QC step to verify that artifacts have been removed from the bare-earth surface. The surveyed ground control points are used to perform the accuracy checks and statistical analysis of the LiDAR dataset.

The NOAA Office for Coastal Management (OCM) downloaded 964 laz files from ftp://ftp.gisdata.state.mn.us/pub/data/elevation/lidar/projects/duluth_fall_2012/

The files contained elevation and intensity measurements for the Duluth Post-Flood project area. The data were in UTM 15, NAD83, meters coordinates and NAVD88 (Geoid09) elevations in meters. The data were classified as: 1 - Unclassified, 2 - Ground, 3 - Low Veg, 4 - Medium Veg, 5 - High Veg, 6 - Buildings, 7 - Noise, 8 - Model Keypoint, 9 - Water, 10 - Ignored Ground, 14 - Bridge Decks, 17 - Overlap. The NOAA Office for Coastal Management processed all classifications of points to the Digital Coast Data Access Viewer (DAV). Classes available on the DAV are: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 14, 17.

OCM performed the following processing on the data for Digital Coast storage and provisioning purposes:

1. An internal OCM script was run to check the number of points by classification and by flight ID and the gps and intensity ranges.

2. Internal OCM scripts were run on the laz files to convert from orthometric (NAVD88) elevations to ellipsoid elevations using the Geoid09 model, to convert from UTM 15, NAD83, meters coordinates to geographic coordinates, to assign the geokeys, to sort the data by gps time and zip the data to database and to http.