Data Management Plan (Deprecated)

These data support the general geospatial needs of the USGS and other federal agencies. LiDAR data is remotely sensed high-resolution elevation

data collected by an airborne collection platform. By positioning laser range finding with the use of 1 second GPS with 200hz inertial measurement

unit corrections, Airborne 1's LiDAR instruments are able to make highly detailed geospatial elevation products of the ground, man-made structures

and vegetation. The LiDAR flightlines for this project were planned for a 50% acquisition overlap. The nominal resolution of this project without

overlap is 1.203m, with a 0.90m resolution with the 50% overlap, assuming a normal distribution. Two returns were recorded for each pulse in addition

to an intensity value. GPS Week Time, Intensity, Flightline and number attributes were recorded for each LiDAR point. Positional values were recorded

to the centimeter level, while GPS is recorded to a 10th of a millisecond. Scan angle was recorded to the nearest angle, Intensity is recorded as a

12 Bit dynamic range value and echo is recorded as a numeric value from 0 to 256.

The data was originally provided as random points, in LAS v1.1 format, classified according to the following codes:

Class 1 Non-ground/Extracted Features Last Pulse

Class 2 Bare Earth Ground Features Last Pulse

Class 3 Extracted Features First Pulse

Class 4 Bare Earth Ground Features First Pulse

It should be noted that Class 3 and 4 are not ASPRS classes but since this data is a two pulse system, this is the most efficient format to

separate the pulses and classification process.

The data was reclassified into 2 distinct classifications:

Class 1 Non-ground/Extracted Features First and Last Pulse

Class 2 Bare Earth Ground Features First and Last Pulse

Process Steps:

• 2008-02-01 00:00:00 - > Airborne GPS Kinematic Airborne GPS kinematic data was post processed at Airborne 1 facilities using POS-GNSS kinematic On-The-Fly (OTF) software. Flights were flown with a minimum of 6 satellites in view (13o above the horizon) and with a PDOP of better than 3.5. Distances from base station to aircraft (differential baselines) were kept to a maximum of 31 km while the mean is 16 km, to ensure a strong OTF (On-The-Fly) solution. For all flights, the GPS data can be classified as excellent, with GPS residuals of 5cm average but no larger than 10 cm being recorded. >Generation and Calibration of laser points (raw data) The initial step of calibration is to verify availability and status of all needed GPS and Laser data against field notes and compile any data if not complete. Subsequently the mission points are output using Optech's REALM, initially with default values from Optech or the last mission calibrated for system. The initial point generation for each mission calibration is verified within Microstation/Terrascan for calibration errors. If a calibration error greater than specification is observed within the mission, the roll pitch and scanner scale corrections that need to be applied are calculated. The missions with the new calibration values are regenerated and validated internally once again to ensure quality. All missions are validated against the adjoining missions for relative vertical biases and collected GPS kinematic ground truthing points for absolute vertical accuracy purposes. On a project level, a coverage check is carried out to ensure no slivers are present. >Data Classification and Editing The data was processed using the software TerraScan, and following the methodology described herein. The initial step is the setup of the TerraScan project, which is done by importing client provided tile boundary index (converted to the native UTM zone for processing)encompassing the entire project areas. The 3D laser point clouds, in binary format, were imported into the TerraScan project and divided in 409 Tiles as specified by 133 Urban Area Ortho tiles in LAS 1.0 format. Once tiled, the laser points were classified using a proprietary routine in TerraScan. This routine removes any obvious outliers from the dataset following which the ground layer is extracted from the point cloud. The ground extraction process encompassed in this routine takes place by building an iterative surface model. This surface model is generated using three main parameters: building size, iteration angle and iteration distance. The initial model is based on low points being selected by a "roaming window" with the assumption is that these are the ground points. The size of this roaming window is determined by the building size parameter. The low points are triangulated and the remaining points are evaluated and subsequently added to the model if they meet the iteration angle and distance constraints. This process is repeated until no additional points are added within an iteration. A second critical parameter is the maximum terrain angle constraint, which determines the maximum terrain angle allowed within the classification model. The data is then manually quality controlled with the use of hillshading, cross-sections and profiles. Any points found to be of class vegetation, building or error during the quality control process, are removed from the ground model and placed on the appropriate layer. An integrity check is also performed simultaneously to verify that ground features such as rock cuts, elevated roads and crests are present. Once data has been cleaned and complete, it is then by a supervisor via manual inspection and through the use of a hillshade mosaic of the entire project area.
• 2008-02-01 00:00:00 - >Deliverable Product Generation -Deliverable Tiling Scheme All files were converted to LAS 1.1, in the specified projection and units and were delivered in the client provided tiling scheme with a total of 409 tiles. -LAS 1.1 Files LiDAR point data in LAS 1.1, classified according to the following classification scheme: Class 1 Non-ground/Extracted Features Last Pulse Class 2 Bare Earth Ground Features Last Pulse Class 3 Extracted Features First Pulse Class 4 Bare Earth Ground Features First Pulse The data contains the following fields of information (Precision reported in brackets): Class (Integer), GPS WeekTime (0.0001 seconds), Easting (0.01 meter), Northing (0.01 meter), Elevation (0.01 meter), Echo Number (Integer 1 to 2), Echo (Integer 1 to 2), Intensity (12 Bit Dynamic), Flightline, Scan Angle (Integer Degree) All points outside project area were assigned to Class 1 - Non-Ground. -GPS Trajectory Files GPS Trajectory Files were provided in digital copy -ABGPS/IMU Positions ABGPS/IMU combined files containing time,x,y,z,kappa,phi,omega were provided in ASCII format. All positions were provided in NAD83 UTM18, NAVD88(Geoid03), GPS seconds (reported to a 10th of a millisecond), meters (reported to a centimeter) for the XYZ and degrees for the kappa,phi,omega (reported to 6 decimals of a degree).
• 2010-08-27 00:00:00 - The NOAA Office for Coastal Management (OCM) received the files in las format. The files contained Lidar elevation and intensity measurements. The data were in projected in UTM coordinates, Zone 18 (NAD83), and referenced to the orthometric datum of NAVD88 utilizing Geoid 03. OCM performed the following processing to the data to make it available within the Digital Coast: 1. The data were converted from UTM Zone 18 (NAD83) coordinates to geographic coordinates (NAD83). 2. The data were converted from NAVD88 (orthometric) heights to GRS80 (ellipsoid) heights using Geoid 03. 3. The LAS data were reclassifed from 4 to 2 classes: - Class 1, Non-ground/Extracted Features Last Pulse; Extracted Features First Pulse - Class 2, Bare Earth Ground Features Last Pulse; Bare Earth Ground Features First Pulse 4. The LAS data were sorted by latitude and the headers were updated.

This data can be obtained on-line at the following URL: https://coast.noaa.gov/dataviewer;