2012 MN DNR Lidar: Blue Earth County, MN

Create custom data files by choosing data area, product type, map projection, file format, datum, etc. A new metadata will be produced to reflect your request using this record as a base. Change to an orthometric vertical datum is one of the many options.

Bulk download of the Blue Earth County data files in LAZ format, based on a horizontal datum/projection of UTM Zone 15, NAD83, meters and a vertical datum of NAVD88 (GEOID09) and units in meters. This url links to the USGS copy of the files, from which the Entwine Point Tile files originated. These have not been reviewed by OCM and the link is provided here for convenience.

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.

Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud.

Link to view the point cloud (using the Entwine Point Tile (EPT) format) in the 3D Potree viewer.

The vertical accuracy validation report for the 2012 MN DNR Blue Earth County, MN lidar data set.

LiDAR data and derivative products produced in compliance with this task order are part of the data to be obtained under Contract number E112-10821 with Minnesota Department of Natural Resources. Specifications listed below are based on National Digital Elevation Program (NDEP) and the American Society for Photogrammetry and Remote Sensing (ASPRS) and Other High Quality Digital Topography.

AEROMETRIC, INC. PROCESSING INFORMATION:

This LiDAR data set consists of approximately 2,260 square kilometers (862 square miles). The airborne GPS and IMU data were processed immediately following each mission. In addition, a sample of the LIDAR data was post-processed at the completion of each mission and the data was reviewed to ensure planned data quality and coverage.

The LiDAR data was captured using a twin engine fixed wing aircraft equipped with a LiDAR system. The LiDAR system includes a differential GPS unit and inertial measurement system to provide highly accurate positioning.

Acquisition parameters:

1. Scanner - Leica ALS70

2. Flight Height - 2400 meters above ground level

3. Swath Width - 40 degrees

4. Sidelap - 30 percent

5. Nominal Point Spacing - 1.4 meters

GPS and IMU processing parameters:

1. Processing Programs and version - TerraTec TerraPOS, TPAS TC GNSS/INS Processor version 3.10, IPAS Pro version 2.01.02

2. IMU processing monitored for consistency and smoothness - Yes

Point Cloud Processing:

1. Program and version - ALS Post Processor version 2.74 build#9

2. Horizontal Datum - NAD83 HARN

3. Horizontal Coordinates - UTM zone 15N, in meters

4. Vertical Datum - NAVD88

5. Geoid Model used to reduce satellite derived elevations to orthometric heights - Geoid09 (Meters)

Lidar Processing:

1. Processing Programs and versions - ALS Post Processor version 2.74 build#9, TerraSolid TerraScan (version 012.010), TerraModeler (version 012.005 and TerraMatch (version 012.004) and Intergraph MicroStation (version.08.05.02.70).

2. Point Cloud data was imported to TerraScan in a Microstation V8 (V) CAD environment on a specified tiling scheme based on the US National Grid Square.

3. Analyzed the data for overall completeness and consistency. This was to ensure that there were no voids in the data collection.

4. QC (Quality Control) for calibration errors in the dataset. This was accomplished by sampling the data collected across all flight lines and classifying the individual lines to ground. The software used the ground-classified lines to compute corrections (Heading, Pitch, Roll, and Scale).

5. Orientation corrections (i.e. Calibration corrections) were then applied (if needed) to the entire dataset.

6. Automatic ground classification was performed using algorithms with customized parameters to best fit the project area. Several areas of varying relief and planimetric features were inspected to verify the final ground surface.

7. AeroMetric, Inc. provided Quality Assurance and Quality Control (QAQC) data for this project. AeroMetric processed QA/QC points in 'open terrain' land cover category that were used to test the accuracy of the LiDAR ground surface. TerraScan's Output Control Report (OCR) tool was used to compare the QAQC data to the lidar data. This routine searches the lidar dataset by X and Y coordinate, finds the closest lidar point and compares the vertical (Z) values to the known data collected in the field. Based on the QAQC data, a bias adjustment was determined, and the results were applied to the lidar data. A final OCR was performed on the entire data set to assess any adjustment and ensure that data was accurately positioned.

8. Once the automatic processing and testing of lidar was complete, Aerometric meticulously reviewed the generated bare-earth surface data to insure that proper classification was achieved. Each tile was reviewed for accuracy and consistency of the macro ground classification. Also during this phase, MicroStation was used to generate linework representing water bodies and rivers. Separate linework was also placed in instances where overpasses had blocked enough valid ground returns or water gave too few ground returns to reasonably portray the ground surface. A proprietary in-house software program was then run to drape the river linework in a flowing fashion. Contours were generated on the river breaklines to review monotonicity of the draped linework.

9. After the lidar data was finalized for vertical placement, a macro was run via TerraScan to output a dataset generated on a per swath basis as part of the final deliverables. All points of the swath were reclassified to class 0 during this step.

10. Final deliverables were generated and output to a client-specified tiling scheme set of geodatabases.

DNR PROCESSING INFORMATION

Additional products generated by Minnesota DNR staff 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).

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_BlueEarth_2011_LAS_2016/ept.json