2007 USGS Lidar: Canyon Fire (CA)

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This graphic shows the lidar coverage of the canyon fire area in California from 2007.

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.

Partial upload of Positional Accuracy fields only.

Partial upload to move data access links to Distribution Info.

- Airborne GPS Kinematic

Airborne GPS kinematic data was processed on-site using GrafNav 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 30 km while the mean is 6.8 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 than10 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 Dashmap, 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 495 USGS DOQQ derived 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 oint 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.

- 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 128 tiles.

>LAS 1.1 Files

LiDAR point data in LAS 1.1

ASPRS classfication scheme

Class 1 Non-ground

Class 2 Ground

Class 7 Noise

Class 9 Water

Contains the following fields of information: Class, GPS WeekTime, Easting, Northing, Elevation, Echo Number, Echo, Intensity, Flightline, Scan Angle

All points outside project area were assigned to Class 1 - Non-Ground (Unclassified).

The NOAA Office for Coastal Management (OCM) received topographic files in LAS format. The files contained lidar elevation and intensity measurements. The data were received in NAD83 UTM Zone 15 Coordinates and were vertically referenced to NAVD88 using the Geoid09 model. The vertical units of the data were meters. OCM performed the following processing for data storage and Digital Coast provisioning purposes:

1. The LAS files were converted from orthometric (NAVD88) heights to ellipsoidal heights using Geoid03.

2. The LAS files were converted from UTM Zone 11 (meters) to Geographic coordinates (decimal degrees).

3. The LAS files were converted to Adjusted GPS time rather than the delivered GPS week seconds (1457).