- Watershed Sciences, Inc.
- DOC/NOAA/NOS/OCM > Office for Coastal Management, National Ocean Service, National
Oceanic and Atmospheric Administration, U.S. Department of Commerce
- DOC/NOAA/NESDIS/NGDC > National Geophysical Data Center, NESDIS, NOAA, U.S. Department
| Processing Steps
- No metadata was provided to NOAA CSC with this data set. The following process step
is derived from the Watershed Sciences, Inc. lidar report. This report may be accessed
Acquisition 1. The lidar data were collected between April 21 - July 13, 2009. 2.
The survey used a Leica ALS50 Phase II and an ALS60 Phase II sensor mounted in a Cessna
Caravan 208B. 3. Near nadir scan angles were used to increase penetration of vegetation
to ground surfaces. 4. Ground level GPS and aircraft IMU were collected during the
flight. Processing 1. Laser point coordinates are computed using the IPAS and ALS
Post Processor software suites based on independent data from the LiDAR system (pulse
time, scan angle), and aircraft trajectory data (SBET). Laser point returns (first
through fourth) are assigned an associated (x, y, z) coordinate along with unique
intensity values (0-255). The data are output into large LAS v. 1.2 files; each point
maintains the corresponding scan angle, return number (echo), intensity, and x, y,
z (easting, northing, and elevation) information. 2. These initial laser point files
are too large to process. To facilitate laser point processing, bins (polygons) are
created to divide the dataset into manageable sizes (less than 500 MB). Flightlines
and LiDAR data are then reviewed to ensure complete coverage of the study areas and
positional accuracy of the laser points. 3. Once the laser point data are imported
into bins in TerraScan, a manual calibration is performed to assess the system offsets
for pitch, roll, heading and mirror scale. Using a geometric relationship developed
by Watershed Sciences, each of these offsets is resolved and corrected if necessary.
4. The LiDAR points are then filtered for noise, pits and birds by screening for absolute
elevation limits, isolated points and height above ground. Each bin is then inspected
for pits and birds manually; spurious points are removed. For a bin containing approximately
7.5 - 9.0 million points, an average of 50 - 100 points are typically found to be
artificially low or high. These spurious non-terrestrial laser points must be removed
from the dataset. Common sources of non-terrestrial returns are clouds, birds, vapor,
and haze. 5. The internal calibration is refined using TerraMatch. Points from overlapping
lines are tested for internal consistency and final adjustments are made for system
misalignments (i.e., pitch, roll, heading offsets and mirror scale). Automated sensor
attitude and scale corrections yield 3 - 5 cm improvements in the relative accuracy.
Once the system misalignments are corrected, vertical GPS drift is then resolved and
removed per flight line, yielding a slight improvement (less than 1 cm) in relative
accuracy. At this point in the workflow, data have passed a robust calibration designed
to reduce inconsistencies from multiple sources (i.e. sensor attitude offsets, mirror
scale, GPS drift) using a procedure that is comprehensive (i.e. uses all of the overlapping
survey data). Relative accuracy screening is complete. 6. The TerraScan software suite
is designed specifically for classifying near-ground points (Soininen, 2004). The
processing sequence begins by removing all points that are not near the earth based
on geometric constraints used to evaluate multi-return points. The resulting bare
earth (ground) model is visually inspected and additional ground point modeling is
performed in site-specific areas (over a 50-meter radius) to improve ground detail.
This is only done in areas with known ground modeling deficiencies, such as: bedrock
outcrops, cliffs, deeply incised stream banks, and dense vegetation. In some cases,
ground point classification includes known vegetation (i.e., understory, low/dense
shrubs, etc.) and these points are reclassified as non-grounds. Ground surface rasters
are developed from triangulated irregular networks (TINs) of ground points.
- The NOAA Coastal Services Center (CSC) received the files in las format. The files
contained LiDAR elevation and intensity measurements. The data were in UTM Zone 10
NAD83(CORS96) projection, NAVD88 (Geoid03) vertical datum and units were in meters.
CSC performed the following processing for data storage and Digital Coast provisioning
purposes: 1. The data were converted from UTM Zone 10 coordinates to geographic coordinates.
2. The data were converted from NAVD88 (orthometric) heights to GRS80 (ellipsoid)
heights using Geoid03. 3. The data were sorted by time. 4. The data were converted
to LAZ format.
- The NOAA National Geophysical Data Center (NGDC) received lidar data files via ftp
transfer from the NOAA Coastal Services Center. The data are currently
being served via NOAA CSC Digital Coast at http://www.csc.noaa.gov/digitalcoast/.
The data can be used to re-populate the system. The data are archived in LAS or LAZ
The LAS format is an industry standard for LiDAR data developed by the American Society
of Photogrammetry and Remote Sensing (ASPRS); LAZ is a loseless compressed version
LAS developed by Martin Isenburg (http://www.laszip.org/). The data are exclusively
in geographic coordinates (either NAD83 or ITRF94). The data are referenced vertically
the ellipsoid (either GRS80 or ITRF94), allowing for the ability to apply the most
up to date geoid model when transforming to orthometric heights.