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LiDAR Elevation Data: Milwaukee County WI, 2020

Identification Information

Citation
Title
LiDAR Elevation Data: Milwaukee County WI, 2020
Originator
Milwaukee County
Publication Date
2020-10-05
Edition
2020
Geospatial Data Presentation Form
modelDigital
Collection Title
Wisconsin Elevation Data, Coastal
Abstract
This Southeastern Wisconsin Regional Planning Commission (SEWRPC) high density lidar project encompassed the entirety of Milwaukee County, Wisconsin, which covers approximately 250 square miles and includes a 333 foot buffer around the county boundary. The airborne lidar data was acquired at an aggregate nominal point density (ANPD) of 30 points per square meter. Project specifications are based on SEWRPC requirements. The data was developed and delivered in State Plane Coordinates, Wisconsin South zone, with a horizontal datum of NAD83(2011) and vertical datum of NAVD88 - Geoid12B, with horizontal and vertical units in US Survey Feet. LiDAR data was acquired using a Riegl VQ 1560i sensor, serial number 4040, from April 2, 2020 to April 3, 2020 in three total lifts. Lidar acquisition occurred with leaves absent from deciduous trees, when no snow was present on the ground and with rivers at or below normal levels. The lidar data was calibrated, processed, and delivered in 2020.
Purpose
This data represents lidar elevation data for Milwaukee County in 2020. The following derivatives are available: classified LAS (tiled), breaklines, 2-D buildings, 1ft contours, DEM (tiled), DEM hillshade (tiled), DEM slope degree (tiled), DEM slope percent (tiled), DSM (tiled), DSM hillshade (tiled), and intensity images (tiled). [This data, along with its derivatives, is the result of a countywide elevation mapping with cooperative partnerships from Southeastern Wisconsin Regional Planning Commission (SEWRPC). This data was produced from lidar data collected in April 2020, which was processed and delivered in October 2020.]
Supplemental Information
This an archived copy of the data held at UW-Madison (WisconsinView)
Temporal Extent
Currentness Reference
ground condition
Time Period
Begin
2020-04-02
End
2020-04-03
Bounding Box
West
-88.075628
East
-87.811807
North
43.195998
South
42.837963
ISO Topic Category
elevation
Place Keyword
Milwaukee County
Wisconsin
Place Keyword Thesaurus
Theme Keyword
LAS Point Cloud
Elevation Data
Lidar
Model
Remote Sensing
Theme Keyword Thesaurus
Resource Constraints
Use Limitation
None. However, users should be aware that temporal changes may have occurred since this dataset was collected and that some parts of these data may no longer represent actual surface conditions. Users should not use these data for critical applications without a full awareness of its limitations. The lidar data is not to be used for purposes other than those outlined by SEWRPC for its partners and stakeholders on this project. Acknowledgement of the Southeastern Wisconsin Regional Planning Commission (SEWRPC) would be appreciated for products derived from these data.
Legal Constraints
Other Restrictions
No restrictions apply to this data.
Status
completed
Maintenance and Update Frequency
notPlanned
Language
eng
Credit
Milwaukee County
Point of Contact
Contact
Milwaukee County
Delivery Point
633 W Wisconsin Avenue Suite 903
City
Milwaukee
Administrative Area
WI
Postal Code
53203
Country
US
Email
mclioservices@milwaukeecountywi.gov

Spatial Reference Information

Reference System Identifier
Code
6609
Code Space
EPSG
Version

Data Quality Information

Absolute External Positional Accuracy
Evaluation Method
Tested 0.154 feet NVA at a 95% confidence level using RMSE(z) x 1.9600 as defined by the National Standards for Spatial Data Accuracy (NSSDA). The NVA of the raw lidar point cloud swath files was calculated against TINs derived from the final calibrated and controlled swath data using 11 independent checkpoints located in Bare Earth and Urban land cover classes.
Result
0.078
Lineage
Process Step
Description
The boresight for each lift was done individually as the solution may change slightly from lift to lift. The following steps describe the Raw Data Processing and Boresight process: 1) Technicians processed the raw data to LAS format flight lines using the final GPS/IMU solution. This LAS data set was used as source data for boresight. 2) Technicians first used RIEGL RiPROCESS software to calculate initial boresight adjustment angles based on sample areas selected in the lift. These areas cover calibration flight lines collected in the lift, cross tie and production flight lines. These areas are well distributed in the lift coverage and cover multiple terrain types that are necessary for boresight angle calculation. The technician then analyzed the results and made any necessary additional adjustment until it is acceptable for the selected areas. 3) Once the boresight angle calculation was completed for the selected areas, the adjusted settings were applied to all of the flight lines of the lift and checked for consistency. The technicians utilized commercial and proprietary software packages to analyze how well flight line overlaps match for the entire lift and adjusted as necessary until the results met the project specifications. 4) Once all lifts were completed with individual boresight adjustment, the technicians checked and corrected the vertical misalignment of all flight lines and also the matching between data and ground truth. The relative accuracy was less than or equal to 2 cm RMSEz within individual swaths and less than or equal to 5 cm RMSEz or within swath overlap (between adjacent swaths). 5) The technicians ran a final vertical accuracy check of the boresighted flight lines against the surveyed check points after the z correction to ensure the requirement of NVA = 9.8 cm 95% Confidence Level (Required Accuracy) was met. Point classification was performed according to USGS Lidar Base Specification 1.3, and breaklines were collected for water features. Bare earth DEMs were exported from the classified point cloud using collected breaklines for hydroflattening.
Process Date
2020-10-05T00:00:00
Process Step
Description
LAS Point Cloud Classification: LiDAR data processing for the point cloud deliverable consists of classifying the LiDAR using a combination of automated classification and manual edit/reclassification processes. On most projects the automated classification routines will correctly classify 90-95 percent of the LiDAR points. The remaining 5-10 percent of the bare earth ground class must undergo manual edit and reclassification. Because the classified points serve as the foundation for the Terrain, DEM and breakline products, it is necessary for the QA/QC supervisor to review the completed point cloud deliverables prior to the production of any additional products. The following workflow steps are followed for automated LiDAR classification: 1. Lead technicians review the group of LiDAR tiles to determine which automated classification routines will achieve the best results. Factors such as vegetation density, cultural features, and terrain can affect the accuracy of the automated classification. The lead technicians have the ability to edit or tailor specific routines in order to accommodate the factors mentioned above, and achieve the best results and address errors. 2. Distributive processing is used to maximize the available hardware resources and speed up the automated processing as this is a resource-intensive process. 3. Once the results of the automated classification have been reviewed and passed consistent checks, the supervisor then approves the data tiles for manual classification. The following workflow steps are followed for manual edits of the LiDAR bare earth ground classification: 1. LiDAR technicians review each tile for errors made by the automated routines and correctly address errors any points that are in the wrong classification. By methodically panning through each tile, the technicians view the LiDAR points in profile, with a TIN surface, and as a point cloud. 2. Any ancillary data available, such as Google Earth, is used to identify any features that may not be identifiable as points so that the technician can make the determination to which classification the feature belongs. The QA/QC processes for the LiDAR processing phase consist of: 1. The lead technician reviews all automated classification results and adjust the macros as necessary to achieve the optimal efficiency. This is an iterative process, and the technician may need to make several adjustments to the macros, depending upon the complexity of the features in the area being processed.  During the manual editing process, the LiDAR technicians use a system of QA, whereby they check each other’s edits. This results in several benefits to the process:  There is a greater chance of catching minor blunders  It increases communication between technicians on technique and appearance  Solutions to problems are communicated efficiently  To ensure consistency across the project area, the supervisor reviews the data once the manual editing is complete. For this phase of a project, the following specifications are checked against: • Point cloud – all points must be classified according to the USGS classification standard for LAS. The all-return point cloud must be delivered in fully-compliant LAS version 1.4. • LAS files will use the Spatial Reference Framework according to project specification and all files shall be projected and defined. • General Point classifications:  Class 1. Processed, but unclassified  Class 2. Bare Earth  Class 7. Noise  Class 9. Water  Class 17. Bridge Decks  Class 18. High Noise  Class 20. Ignored ground (Breakline proximity) • Outliers, noise, blunders, duplicates, geometrically unreliable points near the extreme edge of the swath, and other points deemed unusable are to be identified using the "Withheld" flag. This applies primarily to points which are identified during pre-processing or through automated post-processing routines. Subsequently identified noise points may be assigned to the standard Noise Classes (Class 7). • Point classification shall be consistent across the entire project. Noticeable variations in the character, texture, or quality of the classification between tiles, swaths, lifts, or other non-natural divisions will be cause for rejection. • Once the data is imported into GeoCue and has undergone and passed the QC process, the strip data will be tiled to the 2500’ x 2500’ tiling scheme determined by the client.
Process Date
2020-10-05T00:00:00
Process Step
Description
Archived data at UW-Madison
Process Date
2023-01-26T00:00:00

Distribution Information

Distributor
UW-Madison
Online Access
https://bin.ssec.wisc.edu/pub/wisconsinview/lidar/Milwaukee/Milwaukee_2020_County_Delivery/
Protocol
WWW:DOWNLOAD-1.0-http--download
Name
Wisconsinview.org
Function
download

Metadata Reference Information

Hierarchy Level
dataset
Metadata File Identifier
6C135FCD-A991-4589-870E-9A23F50CA5C2
Metadata Date Stamp
2023-01-26
Metadata Standard Name
ISO 19139 Geographic Information - Metadata - Implementation Specification
Metadata Standard Version
2007
Character Set
utf8
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