2010 FEMA Lidar: Ozaukee County (WI)

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This graphic shows the lidar coverage for the 2010 project for the coastal region of Wisconsin in Ozaukee County.

Date that the source FGDC record was last modified.

Converted from FGDC Content Standards for Digital Geospatial Metadata (version FGDC-STD-001-1998) using 'fgdc_to_inport_xml.pl' script. Contact Tyler Christensen (NOS) for details.

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GPS based surveys were utilized to support both processing and testing of LiDAR data within FEMA designated Areas of Interest (AOIs). Geographically distinct ground points were surveyed using GPS technology throughout the AOIs to provide support for three distinct tasks.

Task 1 was to provide Vertical Ground Control to support the aerial acquisition and subsequent bare earth model processing. To accomplish this, survey-grade Trimble R-8 GPS receivers were used to collect a series of control points located on open areas, free of excessive or significant slope, and at least 5 meters away from any significant terrain break. Most if not all control points were collected at street/road intersections on bare level pavement.

Task 2 was to collect Fundamental Vertical Accuracy (FVA) checkpoints to evaluate the initial quality of the collected point cloud and to ensure that the collected data was satisfactory for further processing to meet FEMA specifications. The FVA points were collected in identical fashion to the Vertical Ground Control Points, but segregated from the point pool to ensure independent quality testing without prior knowledge of FVA locations by the aerial vendors.

Task 3 was to collect Consolidated Vertical Accuracy CVA) checkpoints to allow vertical testing of the bare-earth processed LiDAR data in different classes of land cover, including: Open (pavement, open dirt, short grass), High Grass and Crops, Brush and Low Trees, Forest, Urban. CVA points were collected in similar fashion as Control and FVA points with emphasis on establishing point locations within the predominant land cover classes within each AOI or Functional AOI Group. In order to successfully collect the Forest land cover class, it was necessary to establish a Backsight and Initial Point with the R8 receiver, and then employ a Nikon Total Station to observe a retroreflective prism stationed under tree canopy. This was necessary due to the reduced GPS performance and degradation of signal under tree canopy.

The R-8 receivers were equipped with cellular modems to receive real-time correction signals from the Keystone Precision Virtual Reference Station (VRS) network encompassing the Region 1 AOIs. Use of the VRS network allowed rapid collection times (~3 minutes/point) at 2.54 cm (1 inch) initial accuracy.

All points collected were below the 8cm specification for testing 24cm, Highest category LiDAR data. To ensure valid in-field collections, an NGS monument with suitable vertical reporting was measured using the same equipment and procedures used for Control, FVA and CVA points on a daily basis. The measurement was compared to the NGS published values to ensure that the GPS collection schema was producing valid data and as a physical proof point of quality of collection. Those monument measurements are summarized in the Accuracy report included in the data delivered to FEMA.

20 FVA points and 15 additional CVA points across the group of AOIs were collected. 20 FVA points are necessary to allow testing to CE95 ? 1 point out of 20 may fail vertical testing and still allow the entire dataset to meet 95% accuracy requirements.In similar fashion, 20 CVA points are necessary to test to CE95 as discussed above. 15 CVA points were collected with the intention at the outset that 5 of the collected FVAs would perform double?duty as Open-class CVA points, to total 20 CVAs per AOI.

The following software packages and utilities were used to control the GPS receiver in the field during data collection, and then ingest and export the collected GPS data for all points: Trimble Survey Controller, Trimble Pathfinder Office.

The following software utilities were used to translate the collected Latitude/Longitude Decimal Degree HAE GPS data for all points into Latitude/Longitude Degrees/Minutes/Seconds for checking the collected monument data against the published NGS Datasheet Lat/Long DMS values and into UTM NAD83 Northings/Eastings: U.S. Army Corps of Engineers CorpsCon, National Geodetic Survey Geoid09 NAVD88.

MSL values were determined using the most recent NGS-approved geoid model to generate geoid separation values for each Lat/Long coordinate pair. In this fashion, Orthometric heights were determined for each Control, FVA and CVA point by subtracting the generated Geoid Separation value from the Ellipsoidal Height (HAE) for publication and use as MSL NAVD88(09).

Using a Optech Gemini LiDAR system, 56 flight lines of highest density (Nominal Pulse Spacing of 1.0m) were collected over the Ozaukee area. A total of five missions were flown: November 11, 2010, November 15, 2010, 2 on November 16, 2010, November 23, 2010. Seven airborne global positioning system (GPS) base stations were used to support the LiDAR data acquisition: WIM5, SHAN, CHON, FOLA, WEBE, RASN, SIWI. Coordinates are available in the Post-Flight Aerial Acquisition Report.

Raw airborne GPS and IMU data were extracted from Applanix CARD. The GPS data was differentially processed in PosGPS and integrated with the IMU data in PosPAC. The GPS/IMU data is processed in Applanix to derive a smoothed best estimate of trajectory (SBET).The SBET was used to reduce the LiDAR slant range measurements to derive the Return measurement for each LiDAR pulse for all LiDAR pulses within for each flight line. The coverage was imported into TerraScan and tiled into 1500m x 1500m tiles. An initial accuracy assessment is done using the ground point survey data. The data then is classified to extract a bare earth digital elevation model (DEM). Once all project data was imported and classified, the survey ground control data was imported again and calculated against the LAS Class 2 (Ground) data for an accuracy assessment. As a QC measure, a routine was used to generate accuracy statistical reports by comparison among LiDAR points, ground control, and triangulated irregular networks (TIN). Any systematic bias in the data is removed to meet or exceed the vertical accuracy requirements.

The calibrated and filtered LiDAR point cloud was hand checked for accuracy. All points were placed in one of the following categories: 1 Unclassified, 2 Ground, 7 Noise, and 12 Overlap Points. Model Key points were then generated from the Ground points and placed in Category 8. Requested elevation values to were then provided to CompassData for their evaluation of the Consolidated Vertical Accuracy (CVA).

The NOAA Office for Coastal Management (OCM) received the files in laz format from USGS via an FTP online repository. The files contained lidar elevation and intensity measurements. The data were in UTM Zone 16 N, NAVD88 (orthometric) heights in meters. OCM performed the following processing for data storage and Digital Coast provisioning purposes:

1. The data were converted from UTM coordinates to geographic coordinates.

2. Erroneous elevations were removed.

3. The data were converted from NAVD88 (orthometric) heights in meters to GRS80 (ellipsoid) heights in meters using Geoid 09.

4. The LAS data were sorted by latitude and the headers were updated.