Data Management Plan

Lidar based surface elevation data collection project in WOH (NYSDEP), collected in 2009. Products generated include LiDAR point data in LAS Binary format v1.1.

The final LiDAR LAS 1.1 was created in UTM Zone 18 North, referenced to NAD83 and NAVD 88, in meters. The final LiDAR DEM was verified against FEMA checkpoints in order to perform a redundency check against the GPS solutions. These accuracy checks also verified that the data meets the guidelines outlined in FEMA's Guidelines and Specifications for Flood Hazard Mapping Partners and Appendix 4B, Airborne Light Detection and Ranging Systems.

The areas of interest were flown at an altitude of 1200 meters (3937 feet) above mean terrain.

Airspeed - 120 knots,

Laser Pulse Rate - 50,000 Hz,

Full Field of View - 60 degrees,

Scane Rate - 32 Hz,

Swath Width - 1300 meters.

Process Steps:

• 2009-01-01 00:00:00 - Data collection: Using Sanborn's Leica ALTM_SN40 and ALTM_SN49 Light Detection And Ranging (LiDAR) system, 428 flight lines of standard density (1.0 meter ground sample distance) data were collected over areas in WOH (NYSDEP) 2009 (approximately 1996.18 square miles). Two returns were recorded for each laser pulse along with an intensity value for each return. The data acquisition occurred in 45 missions between April 16, 2009 , and June 25, 2009. During the LiDAR campaign, the Sanborn field crew conducted a GPS field survey to establish final coordinates of the ground control stations for final processing of the base-remote GPS solutions.
• 2009-01-01 00:00:00 - Airborne GPS processing: Airborne GPS data was differentially processed and integrated with the post processed IMU data to derive a smoothed best estimate of trajectory (SBET). The SBET was used to reduce the LiDAR slant range measurements to a raw georeferenced point. Airborne GPS is differentially processed using the GrafNAV v7.50 software by Waypoint Consulting of Calgary, Alberta, Canada.
• 2009-01-01 00:00:00 - IMU data processing: IMU data provides information concerning roll, pitch and yaw of collection platform during collection event. IMU information allows the pulse vector to be properly placed in 3D space allowing the distance from the aircraft reference point to be properly positioned on the elevation model surface. IMU data is processed using the POSPac v4.2 software by Applanix Corporation of Richmond Hill, Ontario, Canada.
• 2009-01-01 00:00:00 - LiDAR point classification The classification and quality control (QC) of LiDAR data is carried out using TerraScan software v. 8.003 by Terrasolid Limited of Helinski, Finland. The bare earth extraction from the point cloud is the result of a morphological processing routine run in TerraScan. A set of user-defined distances and angles are used by the software to build a ground surface from established 'aerial low seed points'. The reclassifying of the data in areas of overlapping scans is done before the classification of the LAS ground points (DEM). This means the point cloud from which the ground points are extracted is more uniform in terms of point density. The 'cut-overlap' process is performed with the aid of the aircraft trajectory (reduced to the sensor's trajectory) and the scan angle value within the LAS data. For this project, the value used for cutting the overlap was 25 degrees. This means that data from a single scan greater than 12.5 degrees off nadir was classified to class 12 overlap. Using the trajectory and embedded angle information, the software (TerraScan) is able to properly reclassify the overlap points so that the remaining point cloud is edge-matched. That is to say, there are no data voids within the point cloud with class 12 overlap points turned off.
• 2009-01-01 00:00:00 - Output LAS files The tiling and final LAS file creation was performed using LiDAR CuePac v5.0 from GeoCue Corporation of Madison, Alabama, USA. By client specification, the LiDAR point cloud data were cut to square, 750 x 750 meter (~56 Ha, 140 acres) tiles. The naming convention used for the tiles is based on the truncated grid coordinate at the southwest corner point of origin of the tile.
• 2009-01-01 00:00:00 - Summary and algorithms for filtering data: The classification algorithms used on the LiDAR point cloud involved several iterative steps including the removal of low points and other outlyers, the culling of overlap data, and finally the classification of the LiDAR DEM. This process begins with automated routines and ends with a 100% manual edit and QC check of the data. Once the data set classification accuracy was deemed sufficient and no quality issues were found, a final vertical accuracy assessment was performed on the LiDAR DEM.
• 2009-01-01 00:00:00 - Data Validation - The final LiDAR LAS 1.1 was created in UTM Zone 18 North, referenced to NAD83 and NAVD 88, in meters. The final LiDAR DEM was verified against FEMA checkpoints in order to perform a redundency check against the GPS solutions. These accuracy checks also verified that the data meets the guidelines outlined in FEMA's Guidelines and Specifications for Flood Hazard Mapping Partners and Appendix 4B, Airborne Light Detection and Ranging Systems.
• 2020-10-04 00:00:00 - NOAA OCM received the lidar data in 8,909 LAS format binary files. No project report was delivered with the data. The data were in UTM Zone 18N NAD83 meters coordinates and NAVD88 (Geoid03) elevations in meters. 1. An internal OCM script was run to check the number of points by classification and by flight ID and the gps and intensity ranges. It was determined that, in addition to the lidar point classifications specified in the metadata of 1 - Unclassified, 2 - Bare Earth, 7 - Low Points (noise), and 12 - Overlap, classes 3 - Low Vegetaion, 4 - Medium Vegetation, 5 - High Vegetation and 6 - Building were also present. 2. Internal OCM scripts were run on the las files to convert to laz format, to convert from orthometric (NAVD88) elevations to NAD83 (2011) ellipsoid elevations using the Geoid 03 model, to convert from UTM Zone 18 North NAD83 (2007) coordinates in meters to geographic coordinates, to assign the geokeys, to sort the data by gps time and zip the data to database and to http. All point classifications were processed through.

Data is available online for bulk or custom downloads

Data is backed up to tape and to cloud storage.