2011 MN DNR Lidar: Arrowhead, 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 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.

Link to view the Block/Delivery 1 point cloud (using the Entwine Point Tile (EPT) format) in the 3D Potree viewer.

Link to view the Block/Delivery 2 point cloud (using the Entwine Point Tile (EPT) format) in the 3D Potree viewer.

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

Link to view the Block/Delivery 4 point cloud (using the Entwine Point Tile (EPT) format) in the 3D Potree viewer.

Link to view the Block/Delivery 5 point cloud (using the Entwine Point Tile (EPT) format) in the 3D Potree 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.

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.

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.

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.

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.

This pdf shows the block boundaries and their delivery dates.

Vendor Processing Steps:

Woolpert Inc. was selected to provide LiDAR services for CFMS Contract Number B41672 T-Number 1029G Work Order #3 - Minnesota Arrowhead Region.

Using Light Detection And Ranging (LiDAR) systems, 390 flight lines of high density data, at a nominal pulse spacing (NPS) of 1.0 meter for acquisition areas 1 and 2 while the remaining areas were collected and processed to meet a Nominal Post Spacing (NPS) of 1.5 meter, were collected over Minnesota counties of Carlton, Cook, Lake, St. Louis, and Itasca Counties and that portion of Koochiching County that comprises Voyageurs National Park (approximately 12,433 square miles). Multiple returns were recorded for each laser pulse along with an intensity value for each return.

A total of 55 missions were flown over a 20 day period: May 03, 2011 through June 02, 2011. A minimum of two airborne global positioning system (GPS) base stations were used in support of the LiDAR data acquisition. 87 ground control points were surveyed through static methods. The geoid used to reduce satellite derived elevations to orthometric heights was Geoid09. All data for the 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 ArcINFO ArcGrid binary format: bare-earth.

LAS data were classified using the following standard ASPRS categories: 0 Unclassified, 1 Unknown, 2 Bare Earth, 3 Low Vegetation (less than 1.1 m), 4 Medium Vegetation (1.11 - 2.4 m), 5 High Vegetation (2.41 - 200 m), 6 Buildings, 7 Noise, 8 Model Keypoint, 9 Water, 14 Bridge Decks, 17 Overlap

System Parameters for 1.0 NPs:

Post Spacing (Minimum): 3.28 ft / 1.0 m

AGL (Above Ground Level) average flying height: 6,500 ft / 1,981.2 m

MSL (Mean Sea Level) average flying height: 7,700 ft / 2,247 m

Average Ground Speed: 130 knots / 149 mph

Field of View (full): 40 degrees

Pulse Rate: 115.6 kHz

Scan Rate: 41.8 Hz

Side Lap (Minimum): 25%

System Parameters for 1.5 NPs:

Post Spacing (Minimum): 4.92 ft / 1.5 m

AGL (Above Ground Level) average flying height: 7,800 ft / 2,377.4 m

MSL (Mean Sea Level) average flying height: 8,900 ft / 2712.7 m

Average Ground Speed: 150 knots / 172.6 mph

Field of View (full): 40 degrees

Pulse Rate: 99 kHz

Scan Rate: 38 Hz

Side Lap (Minimum): 25%

Swath Width : variable due to multiple flying heights

Distance Between Flight Lines: variable due to multiple flying heights

Data is tiled by 1/16 1:24,000-scale quadrangle.

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).

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.

These are the AWS URLs being accessed:

https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MN_Arrowhead_B1_2011_LAS_2016/ept.json

https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MN_Arrowhead_B2_2011_LAS_2016/ept.json

https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MN_Arrowhead_B3_2011_LAS_2016/ept.json

https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MN_Arrowhead_B4_2011_LAS_2016/ept.json

https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MN_Arrowhead_B5_2011_LAS_2016/ept.json