Aerial Acquisition of Northern San Francisco Bay, California LiDAR
- Description of Source: Source Contribution: Aerial LiDAR Acquisition. Fugro EarthData, Inc. collected ALS60-derived
LiDAR over northern San Francisco Bay, CA with a 1 m, nominal post spacing using a
Piper Navajo twin engine aircraft. The collection for the entire project area was
accomplished on February 25, 26, and 28; March 1, 24, and 26; and April 3, 15, and
16, 2010. The collection was performed by Fugro EarthData, Inc., using a Leica ALS60
MPiA LiDAR system, serial number 113, including an inertial measuring unit (IMU) and
a dual frequency GPS receiver. This project required 9 lifts of flight lines to be
collected. The lines were flown at an average of 6,250 feet above mean terrain using
a pulse rate of 121,300 pulses per second. Source Type: External hard drive
- Temporal extent used:
Northern San Francisco Bay, Report of Survey
- Description of Source: Source Contribution: Ground Control. TerraSurv under contract to Fugro EarthData,
Inc. successfully established ground control for Northern San Francisco Bay, CA. A
total of 41 ground control points were acquired. GPS was used to establish the control
network. The horizontal datum was the North American Datum of 1983 (NAD83, NSRS2007).
The vertical datum was the North American Vertical Datum of 1988 (NAVD88). Source
Type: electronic mail system
- Temporal extent used:
|| Lineage statement not available.
- Fugro EarthData, Inc.
- Fugro EarthData, Inc
- DOC/NOAA/NESDIS/NGDC > National Geophysical Data Center, NESDIS, NOAA, U.S. Department
| Processing Steps
- All acquired LiDAR data went through a preliminary review to assure that complete
coverage was obtained and that there were no gaps between flight lines before the
flight crew left the project site. Once back in the office, the data is run through
a complete iteration of processing to ensure that it is complete, uncorrupted, and
that the entire project area has been covered without gaps between flight lines. There
are essentially three steps to this processing; 1. GPS/IMU Processing. Airborne GPS
and IMU data was immediately processed using the airport GPS base station data, which
was available to the flight crew upon landing the plane. This ensured the integrity
of all the mission data. These results were also used to perform the initial LiDAR
system calibration test. 2. Raw LiDAR Data Processing. Technicians processed the raw
data to LAS format flight lines with full resolution output before performing QC.
A starting configuration file was used in this process, which contain the latest calibration
parameters for the sensor. The technician also generated flight line trajectories
for each of the flight lines during this process. 3. Verification of Coverage and
Data Quality. Technicians checked flight line trajectory files to ensure completeness
of acquisition for project flight lines, calibration lines, and cross flight lines.
The intensity images were generated for the entire lift at the required post spacing
for the project. The technician visually checked the intensity images against the
project boundary to ensure full coverage. The intensity histogram was analyzed to
ensure the quality of the intensity values. The technician also thoroughly reviewed
the data for any gaps in project area. The technician generated a sample TIN surface
to ensure no anomalies were present in the data. Turbulence was inspected for and
if it affected the quality of the data, the flight line was rejected and reflown.
The technician also evaluated the achieved post spacing against project specified
- The following steps describe the Raw Data Processing and Boresight process; 1. The
calibration flight lines were first processed with the starting configuration file
which contains the latest calibration parameters for the sensor. The boresight for
each lift was done individually as the solution may change slightly from lift to lift.
2. Lift boresighting was accomplished using the tri-directional calibration flight
lines over the project area. 3. Once the boresighting was done for the calibration
flight lines, the adjusted settings were applied on all of the flight lines of the
lift and checked for consistency. The technician selected a series of areas in the
dataset to be inspected where adjacent flight lines overlay. A routine was run to
calculate the misalignment of the adjacent flight lines and a statistical report was
generated. The technician analyzed the result and applied more adjustment if necessary
to optimize the result for the entire lift. Color coded elevation difference images
were generated for all flight line overlaps including cross ties in the lift once
the boresight adjustment was complete. The technician reviewed these images to ensure
that systematic errors were eliminated for the lift and the results met the project
specifications. 4. Once the boresight adjustment was completed for each lift individually,
the technician checked and corrected the vertical misalignment of all flight lines
and also the matching between data and ground truth. This process included calculating
the z bias value for each flight line so that all flight lines are aligned vertically.
The entire dataset was then matched to ground control points within the project specified
accuracy range. 5. The technician ran a final vertical accuracy check after the z
correction. The result was analyzed against the project specified accuracy to make
sure it met the project requirements.
- Fugro EarthData, Inc. has developed a unique method for processing LiDAR data to identify
and re-classify elevation points falling on vegetation, building, and other above
ground structures into separate data layers. The steps are as follows; 1. Fugro EarthData,
Inc. utilized commercial software as well as proprietary software for automatic filtering.
The parameters used in the process were customized for each terrain type to obtain
optimum results. 2. The Automated Process typically re-classifies 90-98% of points
falling on vegetation depending on terrain type. Once the automated filtering was
completed, the files were run through a visual inspection to ensure that the filtering
was not too aggressive or not aggressive enough. In cases where the filtering was
too aggressive and important terrain features were filtered out, the data was either
run through a different filter or was corrected during the manual filtering process.
3. Interactive editing was completed in 3D visualization software which also provides
manual and automatic point classification tools. Fugro EarthData, Inc. used commercial
and proprietary software for this process. Vegetation and artifacts remaining after
automatic data post-processing were reclassified manually through interactive editing.
The hard edges of ground features that were automatically filtered out during the
automatic filtering process were brought back into ground class during manual editing.
Auto-filtering routines were utilized as much as possible within fenced areas during
interactive editing for efficiency. The technician reviewed the LiDAR points with
color shaded TINs for anomalies in ground class during interactive filtering. 4. Upon
the completion of peer review and finalization of bare earth filtering, the classified
LiDAR point cloud work tiles went through a water classification routine based on
the collected hydro-flattened water polygons. 5. Upon the completion of peer review
and finalization of the classified LiDAR point cloud work tiles, the tiles were reprojected
to NAD83 (NSRS2007), UTM zone 10 north, meters; NAVD88, meters, using GEOID09. The
data was also cut to the approved tile layout. The classified LiDAR point cloud data
is in LAS format after this process. The technician checked the output LAS files for
coverage and format. 6. The classified LiDAR point cloud data were delivered in LAS
1.2 format; 2 - ground, 1 - unclassified, 9 - water, 7 - low points/noise, and 12
- overlap points.
- The NOAA Coastal Services Center (CSC) received the lidar files in las format. The
files contained lidar intensity and elevation measurements. CSC performed the following
processing for data storage and Digital Coast provisioning purposes: 1. Data converted
from UTM Zone 10 coordinates to geographic coordinates. 2. Data converted from NAVD88
heights to ellipsoid heights using GEOID09. 3. The LAS data were sorted by latitude
and the headers were updated.
- 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 format. 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 of 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 to the ellipsoid (either GRS80 or ITRF94), allowing for
the ability to apply the most up to date geoid model when transforming to orthometric