| Processing Steps
- Data for the U.S. Corp of Engineers High Resolution LiDAR Data Acquisition & Processing
for Portions of Connecticut project was acquired by Earth Eye, LLC. The project area
included approximately 1,741 contiguous square miles for portions of Connecticut including
a buffer of 200 meters. LiDAR sensor data were collected with an Leica ALS60 sn146
LIDAR System. No imagery was requested or delivered. The data was delivered in the
UTM coordinate system, meters, zone 18, horizontal datum NAD83, vertical datum NGVD88,
Geoid 09. Deliverables for the project included a raw (unclassified) calibrated LiDAR
point cloud, survey control, and a final control report. The calibration process considered
all errors inherent with the equipment including errors in GPS, IMU, and sensor specific
parameters. Adjustments were made to achieve a flight line to flight line data match
(relative calibration) and subsequently adjusted to control for absolute accuracy.
Process steps to achieve this are as follows: Rigorous LiDAR calibration: all sources
of error such as the sensor's ranging and torsion parameters, atmospheric variables,
GPS conditions, and IMU offsets were analyzed and removed to the highest level possible.
This method addresses all errors, both vertical and horizontal in nature. Ranging,
atmospheric variables, and GPS conditions affect the vertical position of the surface,
whereas IMU offsets and torsion parameters affect the data horizontally. The horizontal
accuracy is proven through repeatability: when the position of features remains constant
no matter what direction the plane was flying and no matter where the feature is positioned
within the swath, relative horizontal accuracy is achieved. Absolute horizontal accuracy
is achieved through the use of differential GPS with base lines shorter than 25 miles.
The base station is set at a temporary monument that is 'tied-in' to the CORS network.
The same position is used for every lift, ensuring that any errors in its position
will affect all data equally and can therefore be removed equally. Vertical accuracy
is achieved through the adjustment to ground control survey points within the finished
product. Although the base station has absolute vertical accuracy, adjustments to
sensor parameters introduces vertical error that must be normalized in the final (mean)
adjustment. The minimum expected horizontal accuracy was tested during the boresight
process to meet or exceed the National Standard for Spatial Data Accuracy (NSSDA)
for a Horizontal accuracy of 1 meter RMSE or better and a Vertical Accuracy of RMSE(z)
= 9.25 cm.
- Earth Eye delivered LiDAR swaths to Dewberry that were calibrated and projected to
project specifications. Dewberry processed the data using GeoCue and TerraScan software.
The initial step is the setup of the GeoCue project, which is done by importing a
project defined tile boundary index encompassing the entire project area. The acquired
3D laser point clouds, in LAS binary format, were imported into the GeoCue project
and tiled according to the project tile grid. Once tiled, the laser points were classified
using a proprietary routine in TerraScan. This routine removes any obvious outliers
from the dataset following which the ground layer is extracted from the point cloud.
The ground extraction process encompassed in this routine takes place by building
an iterative surface model. This surface model is generated using three main parameters:
building size, iteration angle and iteration distance. The initial model is based
on low points being selected by a "roaming window" with the assumption is that these
are the ground points. The size of this roaming window is determined by the building
size parameter. The low points are triangulated and the remaining points are evaluated
and subsequently added to the model if they meet the iteration angle and distance
constraints. This process is repeated until no additional points are added within
iterations. A second critical parameter is the maximum terrain angle constraint, which
determines the maximum terrain angle allowed within the classification model. Dewberry
utilizes a variety of software suites for data processing. After the initial ground
classification, each tile was imported into Terrascan and a surface model was created
to examine the ground classification. Dewberry analysts visually reviewed the ground
surface model and corrected errors in the ground classification such as vegetation,
buildings, and bridges that were present following the initial processing. Dewberry
analysts employ 3D visualization techniques to view the point cloud at multiple angles
and in profile to ensure that non-ground points are removed from the ground classification.
After the ground classification corrections were completed, the dataset was processed
through a water classification routine that utilizes breaklines compiled by Dewberry
to automatically classify hydro features. The water classification routine selects
ground points within the breakline polygons and re-classifies them as class 9, water.
The data was classified as follows: Class 1 = Unclassified. This class includes vegetation,
buildings, noise etc. Class 2 = Ground Class 7= Noise Class 9 = Water The LAS header
information was verified to contain the following: Class (Integer) GPS Week Time (0.0001
seconds) Easting (0.01 foot) Northing (0.01 foot) Elevation (0.01 foot) Echo Number
(Integer 1 to 4) Echo (Integer 1 to 4) Intensity (8 bit integer) Flight Line (Integer)
Scan Angle (Integer degree)
- The NOAA Coastal Services Center (CSC) received topographic files in LAS V1.2 format.
The files contained lidar elevation measurements, intensity values, scan angle values,
return information, flightline information, and adjusted standard GPS time. The data
were received in UTM Zone 18N, NAD83 coordinates and were vertically referenced to
NAVD88 using the Geoid09 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 converted from orthometric (NAVD88) heights to ellipsoidal
heights using Geoid09. 2. The topographic las files were converted from a Projected
Coordinate System (UTM Zone 18N) to a Geographic Coordinate System (NAD83). 3. The
topographic las files' horizontal units were converted from meters to decimal degrees.
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.