U.S. Corp of Engineers
201109
Unknown
Inland_Ponds_and_Lakes
vector digital data
Earth Eye collected LiDAR data for approximately 4,589 square kilometers that either fully or partially cover the Connecticut counties of Tolland, Windham, Hartford, 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. Separate LiDAR files were created for bare earth only points, model key points, first echo return only points, and last echo return only points.
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.
A complete description of this dataset is available in the Final Project Report submitted to the both the U.S. Corp of Engineers and USDA-NRCS Connecticut.
20101103
20101211
ground condition
As needed
-72.654199
-71.764992
42.053551
41.313609
None
DTM
Elevation
Lidar
LAS
DEM
Hydro Flattened
Breaklines
First Return
Last Return
Bare earth
Model Key Points
None
Connecticut
Tolland County
Windham County
Middlesex County
Hartford County
New London County
None
This data was produced for the US Corp of Engineers according to specific project requirements. This information is provided "as is". Further documentation of this data can be obtained by contacting: US Corp of Engineers, 1222 Spruce St. St. Louis, MO 63103. Telephone (314) 331-8385.
U.S. Corp of Engineers
Program Manager
mailing and physical address
1222 Spruce St.
St. Louis
MO
63103
USA
(314) 331-8385
robert.d.mesko@usace.army.mil
Microsoft Windows Vista Version 6.1 (Build 7600) ; ESRI ArcCatalog 9.3.1.1850
Data covers the tile scheme provided for the project area.
A visual qualitative assessment was performed to ensure the data completness against the intensity images derived from Lidar points.
The breaklines are derived from the LiDAR. Horizontal accuracy is not assessed on the breaklines. Lidar source compiled to meet 1 meter horizontal accuracy.
1 meter
Dewberry does not perform independent horizontal accuracy testing on the breaklines or LiDAR. The breaklines are derivd from the LiDAR. LiDAR vendors perform calibrations on the LiDAR sensor and compare data to adjoing flight lines to ensure LiDAR meets the 1 meter horizontal accuracy standard at the 95% confidence level. Please see the final project report delivered to the USGS for more details.
The breaklines are derived from the LiDAR. Breakline elevations are compared to LiDAR elevations to ensure accurate breakline elevations. However, vertical accuracy of the breaklines is not tested.
The vertical accuracy of the LiDAR was tested by Dewberry with 62 independent survey checkpoints. The survey checkpoints were evenly distributed throughout the project area and were located in areas of open terrain (22), grass/weeds/crops (20), or forest (20).
Checkpoints in open terrain were used to compute the Fundamental Vertical Accuracy (FVA). Project specifications required a FVA of 0.185 m based on a RMSEz (0.0925 m) x 1.9600. All checkpoints were used to compute the Consolidated Vertical Accuracy (CVA). Project specifications required a CVA of 0.185 m based on the 95th percentile.
0.09 m
The breaklines are derived from the LiDAR. Breakline elevations are compared to LiDAR elevations to ensure accurate breakline elevations. However, vertical accuracy of the breaklines is not tested.
Based on the vertical accuracy testing conducted by Dewberry, using NSSDA and FEMA methodology, vertical accuracy at the 95% confidence level (called Accuracyz) is computed by the formula RMSEz x 1.9600. The dataset for the Connecticut LiDAR project satisfies the criteria:
Lidar dataset tested 0.09 m vertical accuracy at 95% confidence level in open terrain, based on RMSEz (0.05 m) x 1.9600.
Based on the vertical accuracy testing conducted by Dewberry, using NDEP and ASPRS methodology, consolidated vertical accuracy at the 95% confidence level is computed using the 95th percentile method. The dataset for the Connecticut LiDAR project satisfies the criteria:
Lidar dataset tested 0.17 m vertical accuracy at 95% confidence level in all land cover categories combined.
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 1741 contiguous square miles for portions of Connecticut including a buffer of 200 meters. LiDAR sensor data were collected with the Leica ALS60 sn146. 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
UTM coordinate system, meters, zone 18, horizontal datum NAD83, vertical datum NGVD88, Geoid 09
Airborne Global Positioning System Data
Inertial Measurement Unit
201012
Calibrated LiDAR Point Cloud LAS 1.2 format
Earth Eye
mailing and physical address
3680 Avalon Park Blvd. East, Suite 200
Orlando
FL
32828
USA
(407)608-7202
(407)382-5420
Monday to Friday, 8 - 5, EST
Dewberry utilizes a variety of software suites for inventory management, classification, and data processing. All LiDAR related processes begin by importing the data into the GeoCue task management software. The swath data is tiled according to project specifications (1,000 m x 1,000 m). The tiled data is then opened in Terrascan where Dewberry uses proprietary ground classification routines to remove any non-ground points and generate an accurate ground surface. The ground routine consists of three main parameters (building size, iteration angle, and iteration distance); by adjusting these parameters and running several iterations of this routine an initial ground surface is developed. The building size parameter sets a roaming window size. Each tile is loaded with neighboring points from adjacent tiles and the routine classifies the data section by section based on this roaming window size. The second most important parameter is the maximum terrain angle, which sets the highest allowed terrain angle within the model. Once the ground routine has been completed a manual quality control routine is done using hillshades, cross-sections, and profiles within the Terrasolid software suite. After this QC step, a peer review and supervisor manual inspection is completed on a percentage of the classified tiles based on the project size and variability of the terrain. 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 hydrographic features. The water classification routine selects ground points within the breakline polygons and automatically classifies them as class 9, water. In addition to classes 1, 2, and 9, there is a Class 7, noise points. This class was only used if needed when points could manually be identified as low/high points.
The fully classified dataset is then processed through Dewberry's comprehensive quality control program.
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)
Calibrated LiDAR Point Cloud LAS 1.2 format
201108
Final Tiled LiDAR datasets
Brian Mayfield
Dewberry - Geospatial Services Group
Project Manager
mailing and physical address
1000 N. Ashley Drive, Suite 801
Tampa
FL
33602
USA
813.421.8628
813.225.1385
bmayfield@dewberry.com
8:00 - 5:00 EST
Dewberry used GeoCue software to develop raster stereo models from the LiDAR intensity. The raster resolution was 0.3 m.
Final Tiled LiDAR datasets
201106
Lidar Intensity Stereopairs
Brian Mayfield
Dewberry - Geospatial Services Group
Project Manager
mailing and physical address
1000 N. Ashley Drive, Suite 801
Tampa
FL
33602
USA
813.421.8628
813.225.1385
bmayfield@dewberry.com
8:00 - 5:00 EST
LiDAR intensity stereopairs were viewed in 3-D stereo using Socet Set for ArcGIS softcopy photogrammetric software. The breaklines are collected directly into an ArcGIS file geodatabase to ensure correct topology. The LiDARgrammetry was performed under the direct supervision of an ASPRS Certified Photogrammetrist. The breaklines were stereo-compiled in accordance with the Data Dictionary.
The data dictionary defines Inland Ponds and Lakes as a closed water body feature that is at a constant elevation. These polygon features should be collected at the land/water boundaries of constant elevation water bodies such as lakes, reservoirs, and ponds. Features shall be defined as closed polygons and contain an elevation value that reflects the best estimate of the water elevation at the time of data capture. Water body features will be captured for features 2 acres in size or greater. Donuts will exist where there are islands greater than 1/2 acre in size within a closed water body. Breaklines must be captured at or just below the elevations of the immediately surrounding terrain. Under no circumstances should a feature be elevated above surrounding LiDAR points. The compiler shall take care to ensure that the z-value remains consistent for all vertices placed on the water body.
Lidar Intensity Stereopairs
201107
3D breaklines
Brian Mayfield
Dewberry - Geospatial Services Group
Project Manager
mailing and physical address
1000 N. Ashley Drive, Suite 801
Tampa
FL
33602
USA
813.421.8628
813.225.1385
bmayfield@dewberry.com
8:00 - 5:00 EST
Vector
G-polygon
897
Universal Transverse Mercator
18
0.999600
-75.000000
0.000000
500000.000000
0.000000
coordinate pair
0.000100
0.000100
meters
North American Datum of 1983
Geodetic Reference System 80
6378137.000000
298.257222
North American Vertical Datum of 1988
0.000100
meters
Explicit elevation coordinate included with horizontal coordinates
Inland_Ponds_and_Lakes
Waterbody polygon.
US Corp of Engineers Connecticut LiDAR Project Data Dictionary
OBJECTID
Internal feature number.
ESRI
Sequential unique whole numbers that are automatically generated.
SHAPE
Feature geometry.
ESRI
Coordinates defining the features.
SHAPE_Length
Length of feature in internal units.
ESRI
Positive real numbers that are automatically generated.
SHAPE_Area
Area of feature in internal units squared.
ESRI
Positive real numbers that are automatically generated.
U.S. Corp of Engineers
Program Manager
mailing and physical address
1222 Spruce St.
St. Louis
MO
63103
USA
(314) 331-8385
robert.d.mesko@usace.army.mil
Downloadable Data
This data was produced for the US Corp of Engineers according to specific project requirements. This information is provided "as is". Further documentation of this data can be obtained by contacting: US Corp of Engineers, 1222 Spruce St. St. Louis, MO 63103. Telephone (314) 331-8385.
20110903
U.S. Corp of Engineers
Robert Mesko
Program Manager
mailing and physical address
1222 Spruce St.
St. Louis
MO
63103
USA
(314) 331-8385
robert.d.mesko@usace.army.mil
FGDC Content Standards for Digital Geospatial Metadata
FGDC-STD-001-1998
local time
http://www.esri.com/metadata/esriprof80.html
ESRI Metadata Profile
201109081331470020110908