Data Management Plan

Fugro Horizons Inc. acquired highly accurate Light Detection and Ranging (LiDAR) elevation data for the Twin Cities metropolitan region in east-central Minnesota in Spring and Fall 2011, with some reflights in Spring 2012. The data cover Anoka, Benton, Carver, Dakota, Goodhue, Hennepin, Isanti, Kanabec, Meeker, Mille Lacs, Morrison, Ramsey, Scott, Sherburne and Washington counties.

Most of the data was collected at 1.5 points/square meter. Smaller areas were collected with 2 points/square meter and with 8 points/square meter:

1. 1.5 points/square meter covers Morrison, Mille Lacs, Benton, Isanti, Sherburne, Anoka, Meeker, Hennepin, Washington, Carver, Scott, and Goodhue counties.

2. 2 points/square meter covers the Dakota Block (southern 2/3 of Dakota County)

3. 8 points/square meter covers portions of Minneapolis/St. Paul and the City of Maple Grove

See map of block boundaries: ftp://lidar.dnr.state.mn.us/documentation/status/metro_data_delivery_dates.pdf

Data are in the UTM Zone 15 coordinate system, NAD83 NAVD88 Geoid09 meters. The tiling scheme is 16th USGS 1:24,000 quadrangle tiles.

The vendor delivered the data to the Minnesota Department of Natural Resources (DNR) in several formats:

1. One-meter digital elevation model

2. Edge-of-water breaklines

3. Classified LAS formatted point cloud data

DNR staff quality-checked the data and created two additional products: two-foot contours and building outlines.

Note: The original metadata record was created at the Minnesota Geospatial Information Office using information supplied by the vendor and by DNR. Abstract Addendum, USGS National Geospatial Technical Operations Center (NGTOC), data edited November 2015: Data may have been modified from the original, delivered data by the NGTOC to correct issues such as breakline enforcement and hydro-flattening of water bodies, pits and spikes, and to remove edge tinning and other anomalies. End Abstract Addendum.

This metadata record reflects the Dakota Block portion of the Twin Cities Metro data set and supports the data entry in the NOAA Digital Coast Data Access Viewer (DAV). For this data set, the DAV is leveraging the Entwine Point Tiles (EPT) hosted by USGS on Amazon Web Services.

Lineage Statement:
The Dakota block of the Twin Cities Metro, MN lidar was ingested into the Data Access Viewer for custom product generation by leveraging USGS hosted Entwine Point Tiles.

Process Steps:

• VENDOR PROCESSING STEPS: (See map of block boundaries: ftp://lidar.dnr.state.mn.us/documentation/status/metro_data_delivery_dates.pdf ) 1. Specifications for Blocks A-H (1.5 points/square meter): The settings for the Leica sensor ALS50-II MPiA 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). 2. Specifications for the Dakota Block (2 points/square meter): The settings for the FLI-MAP sensor included acquisition at 2,700' AMT, 145 knots, 30% sidelap, 150kHz, 60% degree field of View, 3,116ft swath to attain an approximate 8 points per square meter. This sensor was also equipped with an 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. 17.64cm ACCz 95% (9.0cm RMSEz) 24.5cm ACCz 95% (12.5cm RMSEz) 24.5cm ACCz 95% (12.5cm RMSEz). 3. Specifications for the Metro Block and the Maple Grove Block (8 points/square meter): The settings for the FLI-MAP sensor included acquisition at 2,100' AMT, 130 knots, 60% sidelap, 200kHz, 60% degree field of View, 2,424ft swath to attain an approximate 8 points per square meter. This sensor was also equipped with an 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 17.64cm ACCz 95% (9.0cm RMSEz) 24.5cm ACCz 95% (12.5cm RMSEz) 24.5cm ACCz 95% (12.5cm RMSEz). 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. 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.
• VENDOR DELIVERABLES Deliverables for the LiDAR are in UTM15N NAD83/HARN NAVD88 Geiod09 meters. Each geodatabase is named for its respective USGS quarter-quarter quad name; there is a tiling scheme feature class in the elevation_data file geodatabase. 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. For the higher density blocks (Dakota Block; Metro Block; Maple Grove Block), the vendor tiled the las files further, breaking each standard tile into 16 additional tiles. They are simply appended an A,B,C, or D starting in the upper left and proceeding in a clockwise direction. A sample image ( http://www.mngeo.state.mn.us/chouse/elevation/16tile_naming_convention.jpg ) taken from the tile index map that is on the FTP site, shows a single tile with the sub-block lettering scheme. A sample tile name would be: 4243-02-30_a_a.laz 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). ADDITIONAL PRODUCTS GENERATED BY MINNESOTA DNR STAFF: These products are in the geodatabase for each of the tiles: 1. Two-foot contours were created by resampling the 1-meter DEM to 3 meters, then smoothing the 3-meter grid using a neighborhood average routine, and then creating contours from this surface using standard ArcGIS processing tools. 2. Building outlines were created by extracting from the LAS files those points with Classification 6 (buildings), then grouping those points within 3 meters of each other into a single cluster and then creating an outline around those points. This was done using standard ArcMap tools. 3. Hillshades were created from the one- and three-meter DEMs using standard ArcMap tools. Azimuth value = 215, Altitude = 45, Z-Factor = 1
• Original point clouds in LAS/LAZ format were restructured as Entwine Point Tiles and stored on Amazon Web Services. The data were reprojected horizontally to WGS84 web mercator (EPSG 3857) and no changes were made to the vertical (NAVD88 GEOID09 meters).
• 2022-12-08 00:00:00 - The NOAA Office for Coastal Management (OCM) created references to the Entwine Point Tiles (EPT) that were ingested into the NOAA Digital Coast Data Access Viewer (DAV). No changes were made to the data. The DAV will access the point cloud as it resides on Amazon Web Services (AWS) under the usgs-lidar-public container. This is the AWS URL being accessed: https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MN_Phase4_Metro_Dakota_2011_LAS_2016/ept.json

Data is available online for bulk and custom downloads.

Data is backed up to tape and to cloud storage.