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

browse graphicThis kmz file shows the extent of coverage for the 2010 USDA Eastern Connecticut lidar data set.
Earth Eye collected LiDAR data for approximately 4,589 square kilometers that partially cover the Connecticut counties of Hartford, Tolland, Windham, Middlesex and New London. The nominal pulse spacing for this project was no greater than 1 point every 0.7 meters. Dewberry used proprietary procedures to classify the LAS according to project specifications: 1-Unclassified, 2-Ground, 7-Noise, 9-Water. Dewberry produced 3D breaklines and combined these with the final LiDAR data to produce seamless hydro flattened DEMs for the 4,840 tiles (1000 m x 1000 m) that cover the project area.
Cite this dataset when used as a source.
Other Access Online access information not available.
Distribution Formats
  • LAZ
Distributor DOC/NOAA/NOS/OCM > Office for Coastal Management, National Ocean Service, National Oceanic and Atmospheric Administration, U.S. Department of Commerce
Dataset Point of Contact Barbara Alexander
USDA/NRCS > Natural Resources Conservation Service, U.S. Department of Agriculture
(860) 871-4046
Associated Resources
  • publication: 2013-11-01
Data Presentation Form: Digital image
Dataset Progress Status Complete
Data Update Frequency: As needed
Purpose: The purpose of this LiDAR data was to produce high accuracy 3D elevation products, including tiled LiDAR in LAS 1.2 format, 3D breaklines, and 1 m cell size hydro flattened Digital Elevation Models (DEMs). This data was produced for the U.S. Corp of Engineers and USDA-NRCS Connecticut for use in projects dealing with conservation planning, design, research, floodplain mapping, dam safety assessments, and hydrologic modeling.
Use Limitations
  • These data depict the elevations at the time of the survey and are only accurate for that time. Users should be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its limitations. Any conclusions drawn from analysis of this information are not the responsibility of NOAA or any of its partners. These data are NOT to be used for navigational purposes.
  • While every effort has been made to ensure that these data are accurate and reliable within the limits of the current state of the art, NOAA cannot assume liability for any damages caused by any errors or omissions in the data, nor as a result of the failure of the data to function on a particular system. NOAA makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty.
  • DOC/NOAA/NOS/OCM > Office for Coastal Management, National Ocean Service, National Oceanic and Atmospheric Administration, U.S. Department of Commerce
  • U.S. Corp of Engineers (USACE)
  • USDA/NRCS > Natural Resources Conservation Service, U.S. Department of Agriculture
  • DOC/NOAA/NOS/OCM > Office for Coastal Management, National Ocean Service, National Oceanic and Atmospheric Administration, U.S. Department of Commerce
Time Period: 2010-11-03 to 2010-12-11
Spatial Reference System: urn:ogc:def:crs:EPSG::4269
Spatial Bounding Box Coordinates:
N: 42.034505
S: 41.296986
E: -71.787609
W: -72.645174
Spatial Coverage Map:
Theme keywords None
  • Topography/Bathymetry
  • Elevation
  • Remote Sensing
  • Light Detection and Ranging
  • Lidar
  • LAS
  • Breaklines
  • Bare earth
Place keywords None
  • USA
  • Connecticut
  • Hartford County
  • Tolland County
  • Windham County
  • Middlesex County
  • New London County
Use Constraints No constraint information available
Fees Fee information not available.
Lineage information for: dataset
  • Earth Eye
  • Dewberry - Geospatial Services Group
  • DOC/NOAA/NOS/OCM > Office for Coastal Management, National Ocean Service, National Oceanic and Atmospheric Administration, U.S. Department of Commerce
  • DOC/NOAA/NESDIS/NCEI > National Centers of Environmental Information, NESDIS, NOAA, U.S. Department of Commerce
Processing Steps
  • 2011-12-01T00:00:00 - 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.
  • 2012-01-01T00:00:00 - 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)
  • 2013-11-01T00:00:00 - 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.
  • 2013-12-31T00:00:00 - 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 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 ( 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 heights.
Last Modified: 2013-12-31
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