- Fugro EarthData, Inc.
- Fugro EarthData, Inc.
- Fugro EarthData, 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
- 2011-08-04T00:00:00 -
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 contains 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 few sample TIN surfaces
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
- 2011-09-19T00:00:00 -
The boresight for each lift was done individually as the solution may change slightly
from lift to lift. The following steps describe the Raw Data Processing and Boresight
process: 1) Technician processed the raw data to LAS format flight lines using the
final GPS/IMU solution. This LAS data set was used as source data for boresight. 2)
Technician first used commercial software to calculate initial boresight adjustment
angles based on sample areas selected in the lift- mini project. These areas cover
calibration flight lines collected in the lift, cross tie and production flight lines.
These areas are well distributed in the lift coverage and cover multiple terrain types
that are necessary for boresight angle calculation. The technician then analyzed the
result and made any necessary additional adjustment until it is acceptable for the
mini project. 3) Once the boresight angle calculation was done for the mini project,
the adjusted settings were applied to all of the flight lines of the lift and checked
for consistency. The technician utilized commercial and proprietary software packages
to analyze the matching between flight line overlaps for the entire lift and adjusted
as necessary until the results met the project specifications. 4) Once the boresight
adjustment was completed for each lift individually, the technician ran a routine
to check the vertical misalignment of all flight lines in the project and also compared
data to ground truth. The entire dataset was then adjusted to ground control points.
5) The technician ran a final vertical accuracy check between the adjusted data and
surveyed ground control points after the z correction. The result was analyzed against
the project specified accuracy to make sure it meets the project requirements. 6)
The flight lines collected under the following programs: National Coastal Mapping
Program - JALBTCX and Coastal California LiDAR and Digital Imagery for NOAA CSC in
partnership with the SCC were tied together in the boresight process. Control points
are shared in both projects. The overlap between flight lines from both projects was
compared for matching.
- 2011-10-20T00:00:00 -
Once boresighting is complete for the project, the project was set up for classification.
The LiDAR data was cut to production tiles. The flight line overlap points, Noise
points and Ground points were classified automatically in this process. 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) All LAS tiles went through peer review after
the first round of interactive editing was finished. This helps to catch misclassification
that may have been missed by the interactive editing. 5) 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 water
polygons. 6) Upon the completion of finalization of the classified LiDAR point cloud
work tiles, the topographic LiDAR classified point cloud data that was produced under
the JALBTCX and NOAA CSC programs was merged. The following methodology was used:
a) due to the differences in deliverable specifications between the two projects,
the technician re-projected the data covered by JALBTCX to UTM zones 10 and 11 north,
NAD83 (NSRS2007), NAVD88, meters. Once complete, the JALBTCX data was reformatted
to LAS 1.2 format in accordance with the NOAA CSC project requirements. The time stamps
for all points that are stored in GPS Weekly Time were converted to Adjusted Standard
GPS time using proprietary software developed by Fugro EarthData, Inc. The data collection
date and the current GPS time stamp were used in calculating the Adjusted Standard
GPS time. The technician applied the same time stamp conversion to the flight lines
collected and processed for JALBTCX project that were used in NOAA CSC project; b)
the technician clipped the NOAA CSC dataset to the inland 500 meter boundary line
used in the JALBTCX project. There were not any gaps or overlap between the coverage
from these two projects; c) once the process finished, the reformatted JALBTCX data
and final NOAA CSC LiDAR classified point cloud data were packaged into NAD83 (NSRS2007),
UTM zones 10 and 11 north, meters; NAVD88, meters, using GEOID09 together for delivery.
The data was also cut to the approved 1500 meter by 1500 meter tile layout and clipped
to the approved project boundary. The technician checked the output LAS files for
coverage and format; d) the technician then QC'ed the merged dataset for quality assurance
and enhanced the Bare Earth classification in the JALBTCX area for consistent data
quality; e) these final LiDAR tiles were then used in the hydro flattening process.
Water classification in some JALBTCX areas was modified in order to achieve the best
hydro flattening result. 7) The classified LiDAR point cloud data were delivered in
LAS 1.2 format: 1 unclassified, 2 ground, 7 low points, 9 water, 10 mudflats, and
12 overlap points.
- 2012-01-01T00:00:00 -
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 Zones 10
and 11 coordinates and NAVD88 Geoid 09 vertical datum. Only points classified as Unclassified
(1), Ground (2), Water (9), and Overlap (12) were made available for download. CSC
performed the following processing for data storage and Digital Coast provisioning
purposes: 1. The data were converted from UTM coordinates to geographic coordinates.
2. The data were converted from NAVD88 (orthometric) heights to GRS80 (ellipsoid)
heights using Geoid 09. 3. The data were filtered to remove outliers. 4. The LAS data
were sorted by latitude and the headers were updated.
- 2012-02-13T00:00:00 -
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
Aerial Acquisition of Coastal California LiDAR
- Description of Source: Source Contribution: Raw lidar data. Fugro EarthData, Inc. collected ALS60-derived
LiDAR over Coastal California with a 1 meter, nominal post spacing using two Piper
Navajo twin engine aircrafts. The collection for the entire project area was accomplished
between October 2009 and August 2011; 1,546 flight lines were acquired in 108 lifts.
The lines were flown at an average of 6,244 feet above mean terrain using a pulse
rate of 121,300 pulses per second. The collection was performed using Leica ALS60
MPiA LiDAR systems, serial numbers 113 and 142. Source Type: External hard drive
- Temporal extent used:
Report of Survey California Coast Ground Control for LiDAR
- Description of Source: Source Contribution: Ground control. TerraSurv under contract to Fugro EarthData,
Inc. successfully established ground control for Coastal California LiDAR. A total
of 307 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: