| Processing Steps
- Using an Optech Gemini lidar sensor, 11 flight lines of high-density data, at a nominal
pulse spacing (NPS) of 1 meter, were collected by Woolpert along the southern shore
of Long Island, New York (approximately 15 square miles). Data Acquisition Height
= 3,500 feet Above Ground Level (AGL) - Aircraft Speed = 125 Knots. Multiple returns
were recorded for each laser pulse along with an intensity value for each return.
A total of one mission was flown on November 5th. Two airborne global positioning
system (GPS) base stations were used in support of the lidar data acquisition. Eight
ground control points were surveyed through static methods. The GEOID used to reduce
satellite-derived elevations to orthometric heights was GEOID96. Data for the task
order is referenced to the UTM Zone 18N, North American Datum of 1983 (NAD83), and
North American Vertical Datum of 1988 (NAVD88), in meters. Airborne GPS data was differentially
processed and integrated with the post-processed inertial measurement unit (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 reflective surface for each flight line.
The coverage was classified to extract a bare earth digital elevation model (DEM)
and separate last returns. In addition to the LAS deliverables, one layer of coverage
was delivered in the ERDAS Imagine (IMG) Format: bare earth.
- The lidar calibration and system performance are verified on a periodic basis using
Woolpert's calibration range. The calibration range consists of a large building and
runway. The edges of the building and control points along the runway have been located
using conventional survey methods. Inertial measurement unit (IMU) misalignment angles
and horizontal accuracy are calculated by comparing the position of the building edges
between opposing flight lines. The scanner scale factor and vertical accuracy are
calculated through comparison of lidar data against control points along the runway.
Field calibration is performed on all flight lines to refine the IMU misalignment
angles. IMU misalignment angles are calculated from the relative displacement of features
within the overlap region of adjacent (and opposing) flight lines. The raw lidar data
are reduced using the refined misalignment angles.
- Once the data acquisition and GPS processing phases are complete, the lidar data were
processed immediately by Woolpert to verify the coverage had no voids. The GPS and
IMU data were post-processed using differential and Kalman filter algorithms to derive
a best estimate of trajectory. The quality of the solution was verified to be consistent
with the accuracy requirements of the project.
- The individual flight lines were inspected by Woolpert to ensure the systematic and
residual errors have been identified and removed. Then, the flight lines were compared
to adjacent flight lines for any mismatches to obtain a homogenous coverage throughout
the project area. The point cloud underwent a classification process to determine
bare-earth points and non-ground points utilizing "first and only" as well as "last
of many" lidar returns. This process determined Default (Class 1), Ground (Class 2),
Noise (Class 7), Water (Class 9), Ignored Ground (Class 10), Overlap Default (Class
17), and Overlap Ground (Class 18) classifications. The bare-earth (Class 2 - Ground)
lidar points underwent a manual QA/QC step to verify that artifacts have been removed
from the bare-earth surface. The surveyed ground control points are used to perform
the accuracy checks and statistical analysis of the lidar dataset.
- Photo Science, Inc. located a total of 29 calibration control points used in the post
processing of the lidar data. The points were located on relatively flat terrain on
surfaces that generally consisted of grass, gravel, or bare earth. Applanix software
(PosPAC MMS) was used in the post processing of the airborne GPS and inertial data,
which are critical to the positioning and orientation of the sensor during all flights.
POSPac MMS provides the smoothed best estimate of trajectory (SBET) that is necessary
for the post processor to develop the point cloud from the lidar missions. The point
cloud is the mathematical three-dimensional collection of all returns from all laser
pulses as determined from the aerial mission. The GEOID used to reduce satellite derived
elevations to orthometric heights was GEOID96. Data for the task order is referenced
to the UTM Zone 18N, NAD83, and NAVD88, in meters. At this point the data are ready
for analysis, classification, and filtering to generate a bare-earth surface model
in which the above ground features are removed from the data set. The point cloud
was manipulated by the Optech or Leica software; GeoCue, TerraScan, and TerraModeler
software were used for the automated data classification, manual cleanup, and bare-earth
generation from the data. Project specific macros were used to classify the ground
and to remove the side overlap between parallel flight lines. All data were manually
reviewed and any remaining artifacts removed using functionality provided by TerraScan
and TerraModeler. All ground (ASPRS Class 2) lidar data inside of the Lake Pond and
Double Line Drain hydro flattening breaklines were then classified to water (ASPRS
Class 9) using TerraScan macro functionality. All Lake Pond and Double Line Drain
Island features were checked to ensure that the ground (ASPRS Class 2) were reclassified
to the correct classification after the automated classification was completed. All
overlap data were processed through automated functionality provided by TerraScan
to classify the overlapping flight line data to approved classes by USGS. The overlap
data were classified to Class 17 (USGS Overlap Default) and Class 18 (USGS Overlap
Ground). These classes were created through automated processes only and were not
verified for classification accuracy. Data were then run through additional macros
to ensure deliverable classification levels matching the ASPRS LAS Version 1.2 Classification
structure. GeoCue functionality was then used to ensure correct LAS Versioning. In-house
software was used as a final QA/QC check to provide LAS Analysis of the delivered
tiles. QA/QC checks were performed on a per tile level to verify final classification
metrics and full LAS header information.
- All Woolpert, Inc. LAZ files were extracted to LAS and converted to ASCII xyz point
files using LASTools las2las.exe. The ASCII point files were then written to netcdf
format using MATLAB 188.8.131.523.
- The NOAA Coastal Services Center (CSC) received topographic files in LAS format. The
files contained lidar elevation and intensity measurements. The data were received
in UTM Zone 18N coordinates and were vertically referenced to NAVD88 using the Geoid96
model. The vertical units of the data were meters. CSC performed the following processing
for data storage and Digital Coast provisioning purposes: 1. The topographic las files
were horizontally converted from UTM Zone 18N to Geographic Coordinates. 2. The horizontal
units of the data were converted from meters to decimal degrees. 3. The topographic
las files were vertically converted from orthometric (NAVD88) heights to ellipsoidal
(NAD83) heights. 4. Classes 11 (Unknown), 15 (Unknown) and 17 (Default Overlap) were
combined to Class 12 (Overlap). Class 11 points were assigned a User Data value of
'1', Class 15 points were assigned a User Data value of '2', and Class 17 points were
assigned a User Data value of '3'. 5. 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.