2010 U.S. Department of Agriculture- Natural Resources Conservation Service (USDA-NRCS) Topographic Lidar: Eastern Connecticut

Create custom data files by choosing data area, product type, map projection, file format, datum, etc.

Simple download of data files.

This graphic shows the lidar coverage for Hartford, Tolland, Windham, Middlesex and New London Counties, Connecticut.

Date that the source FGDC record was last modified.

Converted from FGDC Content Standards for Digital Geospatial Metadata (version FGDC-STD-001-1998) using 'fgdc_to_inport_xml.pl' script. Contact Tyler Christensen (NOS) for details.

Partial upload of Positional Accuracy fields only.

Partial upload to move data access links to Distribution Info.

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 Office for Coastal Management (OCM) 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. OCM 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.