2015 SEWRPC Lidar: Southeast WI (Milwaukee, Ozaukee, Walworth, Washington, Waukesha Counties)

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 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 data set report.

Link to data set report.

Link to data set breaklines.

This data source was used (along with the airborne GPS/IMU Data) to aid in the georeferencing of the lidar point cloud data.

Quantum Spatial Classified LAS Processing:

The bare earth surface is then manually reviewed to ensure correct classification on the Class 2 (Ground) points.

After the bare-earth surface is finalized, it is then used to generate all hydro-breaklines through heads-up digitization.

Initially, all ground (ASPRS Class 2) LiDAR data inside of the Lake Pond and Double Line Drain hydro flattened breaklines were then classified to water (ASPRS Class 9) using TerraScan macro functionality. A buffer of 3 feet was also used around each hydro-flattened feature to classify these ground (ASPRS Class 2) points to Ignored ground (ASPRS Class 10). All Lake Pond Island and Double Line Drain Island features were checked to ensure that the ground (ASPRS Class 2) points were reclassified to the correct classification after the automated classification was completed. All bridge decks were classified to Class 14.

All Overlap and Model Keypoint data was processed through automated functionality provided by TerraScan to classify the overlapping data to both ground (Class 18) and non-ground (Class 17) and the model keypoints (Class 8) data based flight line data

All data was manually reviewed by Quantum Spatial reviewed and any remaining artifacts were removed using functionality provided by TerraScan and TerraModeler. Global Mapper was used as a final check of the bare earth datase and provided to the Commission.

Upon the delivery of the LiDAR data sets, the Southeastern Wisconsin Regional Planning Commission inspected the data for quality assurance. After a number of iterations, the data was approved in July of 2016.

The Commission in support of the 3DEP project reprocessed the approved LiDAR data set to not only reproject and transform a number of counties to meet the NAD83(2011) datum requirements but also deliver the data in full compliance of the USGS Base LiDAR Specification for LAS version 1.4 format. This process utilized LP360 to create a macro filter to reclassify the overlap non-ground and ground to Class 1 and Class 2, respectively, and assign an overlap flag to the overlapping data and also reclassify the model keypoints to Class 2 with a model keypoint flag assigned. As part of the macro filter, also took into account the movement of the bridge points from Class 14 to Class 17.

Also, the Southeastern Wisconsin Regional Planning Commission transformed and reprojected the breakline data. Upon inspection of the transformed lakes and ponds, it was discovered that these flattened surfaces were not exactly flat due to the dynamic changes between NGVD29 and NAVD88. This required that each lake pond be individually set to the lowest elevation of the vertices found supporting that individual lake elevation so it could pass the flatness test. All rivers were not addressed since these features are not flat.

LP360 was then used to take the transformed LAS files with the correct classification and flags along with the final hydro flattened breaklines to generate 2-feet raster digital elevation models based on the same 10,000-feet by 10,000-feet tiling system used for the LAS files. The final tiles were inspected using Global Mapper to ensure proper triangulation and enforcement along with the vertical testing of the digital elevation models.

Lastly, LP360 was used to perform final statistical analysis of the classification of the LAS files, on a per tile level to verify final classification metrics and full LAS header information and the vertical accuracy of the ground points.

The NOAA Office for Coastal Management (OCM) downloaded:

655 laz files from ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/USGS_LPC_WI_SEWRPC_2017_LAS_2019

The 655 files contained elevation and intensity measurements for the southeast Wisconsin project area. The data were in WI State Plane South NAD83 2011, US survey feet coordinates and NAVD88 (Geoid12B) elevations in feet. The data were classified as: 1 - Unclassified, 2 - Ground, 7 - Noise, 9 - Water, 10 - Ignored Ground, 17 - Bridge Decks. 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, 7, 9, 10, 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 Geoid12B model, to convert from WI State Plane South NAD 1983 2011,US survey feet coordinates to geographic coordinates, to convert from vertical units of feet to meters, to assign the geokeys, to sort the data by gps time and zip the data to database and to http.