Data Management Plan

Product Description of Original Data:

These lidar data are processed Classified LAS 1.4 files, formatted to 1351 individual 4,500 ft x 4,500 ft tiles; used to create intensity images, 3D breaklines and hydro-flattened DEMs as necessary.

Geographic Extent: The AOI is covering approximately 907 square miles of Dodge County along with a 100-foot buffer zone outside the county for the lidar data.

Dataset Description of Original Data:

The WI Dodge County Lidar 2017 B17 Lidar project called for the Planning, Acquisition, processing and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.70 meter. Project specifications were based on the U.S. Geological Survey National Geospatial Program Lidar Base Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD 1983 2011 WISCRS Dodge and Jefferson Survey Feet and vertical datum of NAVD88 (GEOID12B), Survey Feet. Lidar data was delivered as; flightline-extent raw LAS v1.4 swaths, classified point cloud LAS v1.4 files formatted to 1351 individual 4,500 ft x 4,500 ft tiles in NAD 1983 2011 WISCRS Dodge and Jefferson Survey Feet. Derivatives were produced as tiled; Bare Earth Surface DEMs, Intensity Images; all tiled to the same 4,500 ft x 4,500 ft schema.

Ground Conditions: Lidar was collected in April of 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Woolpert established a total of 15 ground control points that were used to calibrate the lidar to known ground locations established throughout the project area. Additional independent accuracy checkpoints were collected (58 NVA points and 48 VVA points) and used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.

This metadata record 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 NOAA Office for Coastal Management (OCM) ingested references to the USGS Entwine Point Tiles (EPT) hosted on Amazon Web Services (AWS) into the Digital Coast Data Access Viewer (DAV). The DAV accesses the point cloud as it resides on AWS under the usgs-lidar-public-container.

Process Steps:

• 2017-04-12 00:00:00 - Classified LAS Processing: Classification Filters were applied to aid in the definition of terrain characteristics and to maintain ground. Filtering processes address aspects of the data such as; ground points, noise points, air points, low points, manmade features, vegetation, and overlap points. The Bare Earth surface was manually reviewed to ensure correct classification of Class 2 (Ground). Upon completion of bare earth review hydro-breaklines were generated through heads-up digitization. Ground (Class 2) Lidar points inside Inland Ponds and Lakes, and Inland Streams and Rivers were classified to Water (Class 9). A buffer of 2.3 feet was used around each hydro-flattened feature to classify Ground points (Class 2) to Ignored ground (Class 10). Island features were checked to ensure that Ground point (Class 2) remained classified as Ground. Ground points (Class 2) within 2.3 feet of breaklines, used to reduce triangulation between bridge decks were also classified to Ignored ground (Class 10). All bridge decks were classified to Bridge (Class 17). All remaining Points were filtered , or manually classified to their respective Point Classification; Processed (Class 1), Low Noise (Class 7), High Noise (Class 18) Overlap data was identified using the Overlap Flag, LAS 1.4 specifications. All data was manually reviewed and any remaining artifacts removed. The bare-earth (Class 2 - Ground) lidar points underwent a manual QA/QC step to verify the quality of the DEM as well as a peer-based QC review. This included a review of the DEM surface to remove artifacts and ensure topographic quality. Classification of water (class 9) and ignored ground (class 10) was completed via the use of the hydrologic breaklines collected for the hydro-flattening phase. Buildings (Class 6) was achieved via the used of digitized building footprints. The overlap classes were determined by first identifying the overlapping areas and reclassifying the LAS data by offset from a corridor. This allows the returns located on the edge of the swath to be removed from the bare earth coverage in an effort to produce a more uniform data density. The returns determined to be overlap including overlap default, ground, water, and ignored ground are then applied an overlap flag and reclassified to their respective standard classification value. The surveyed ground control points are used to make vertical adjustments to the data set and to perform the accuracy checks and statistical analysis of the lidar dataset. Supervisory QC monitoring of work in progress and completed editing ensured consistency of classification character and adherence to project requirements across the entire project area. The resulting deliverables for this task order consist of classified LAS file in LAS 1.4 format, DEM files in ERDAS IMG format and ArcGrid format, 8-bit gray scale Intensity files in GeoTIFF format, Hydrologic and Bridge abutment breakline data in ESRI geodatabase format.
• Original point clouds in LAS/LAZ format were restructured as Entwine Point Tiles and stored on Amazon Web Services. The data were re-projected horizontally to WGS84 web mercator (EPSG 3857) and no changes were made to the vertical (NAVD88 Geoid12b, US survey feet).
• 2024-03-14 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_WI_DodgeCo_2017_LAS_2019/ept.json

Data is available online for bulk and custom downloads.

Data is backed up to cloud storage.