U.S. Geological Survey
201502
Unknown
LAS
Elevation Data
Leading Edge Geomatics collected LiDAR data for approximately 1,526 square miles of area in west-central Connecticut. The nominal pulse spacing for this project was 0.7 meter. Dewberry used proprietary procedures to classify the LAS according to project specifications: 1-Unclassified, 2-Ground, 7-Noise, 9-Water, 10-Ignored Ground due to breakline proximity. Dewberry produced 3D breaklines and combined these with the final LiDAR data to produce seamless hydro flattened Digital Elevation Models (DEMs) with a 1 meter grid cell size that cover the project area. In addition to the bare earth hydro flattened DEMs, Dewberry also produced intensity imagery with a 0.3 meter cell size.
USGS-NGP Lidar Base Specification V1.0
Riegl 680i
7
0.67
2.2
0.67
2.2
1000
100
60
76
200
5
0.5
1064
0
0.5
1155
50
National Geodetic Survey (NGS) Geoid12A
0.1813
0.175
20
0.133
20
0.190
104
1.2
1
No withheld points were identified in this dataset
No overlap or overedge points were identified in this dataset
16
0
Calibrated, never classified
1
Processed, but unclassified
2
Bare earth, ground
7
Noise
9
Water
10
Ignored ground due to breakline proximity
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).
A complete description of this dataset is available in the Final Project Report that was submitted to the U.S. Geological Survey.
20140427
20140529
ground condition
As needed
-72.593
-72.197
42.049
41.183
None
Elevation
Lidar
LAS
DEM
Hydro Flattened
Breaklines
Bare earth
None
Connecticut
Hurricane Sandy
Hartford County
Litchfield County
Fairfield County
New Haven County
New London County
Middlesex County
None
This data was produced for the U.S. Geological Survey according to specific project requirements. This information is provided "as is". Further documentation of this data can be obtained by contacting: USGS, 1400 Independence Road, Rolla, MO 65401. Telephone (573)308-3587.
U.S. Geological Survey
Program Manager
mailing and physical address
1400 Independence Road
Rolla
MO
65401
USA
(573)308-3810
pemmett@usgs.gov
Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 3; ESRI ArcCatalog 10.0
Data covers the entire tile scheme provided for the project area.
A visual qualitative assessment was performed to ensure data completeness and bare earth data cleanliness. No void or missing data and data passes vertical accuracy specifications.
Lidar source produced to meet 1 meter horizontal accuracy.
Project specifications required a horizontal accuracy of 1 m based on a RMSEr (0.578m) x 1.7308. Only checkpoints photo-identifiable in the intensity imagery can be used to test the horizontal accuracy of the LiDAR. Photo-identifiable checkpoints in intensity imagery typically include checkpoints located at the ends of paint stripes on concrete or asphalt surfaces or checkpoints located at 90 degree corners of different reflectivity, e.g. a sidewalk corner adjoining a grass surface. The xy coordinates of checkpoints, as defined in the intensity imagery, are compared to surveyed xy coordinates for each photo-identifiable checkpoint. These differences are used to compute the tested horizontal accuracy of the LiDAR. As not all projects contain photo-identifiable checkpoints, the horizontal accuracy of the LiDAR cannot always be tested.
1 meter
LiDAR vendors perform calibrations on the LiDAR sensor and compare data to adjoining flight lines to ensure LiDAR meets the 1 meter horizontal accuracy standard at the 95% confidence level.
However, Dewberry tested the horizontal accuracy of the LiDAR by comparing photo-identifiable survey checkpoints to the LiDAR Intensity Imagery. As only thirteen (13) checkpoints were photoidentifiable, the results are not statistically significant enough to report as a final tested value. However, the results are reported below.
Using NSSDA methodology, horizontal accuracy at the 95% confidence level (called Accuracyr) is computed by the formula RMSEr x 1.7308. The dataset for the CT Sandy LiDAR project satisfies the criteria:
Lidar dataset tested 0.660 m horizontal accuracy at 95% confidence level, based on RMSEr (0.381 m) x 1.7308.
Please see the final project report delivered to the U.S. Geological Survey for more details.
The vertical accuracy of the LiDAR was tested by Dewberry with 104 independent survey checkpoints. The survey checkpoints are evenly distributed throughout the project area and are located in areas of bare earth and open terrain (20), urban terrain (21), forest (21), brushland and trees (21), and high grass (21). The vertical accuracy is tested by comparing survey checkpoints to a triangulated irregular network (TIN) that is created from the LiDAR ground points. Checkpoints are always compared to interpolated surfaces created from the LiDAR point cloud because it is unlikely that a survey checkpoint will be located at the location of a discrete LiDAR point.
Checkpoints in open terrain were used to compute the Fundamental Vertical Accuracy (FVA). Project specifications required a FVA of 18.13 cm based on a RMSEz (9.25 cm) x 1.9600. All checkpoints will be used to compute the Consolidated Vertical Accuracy (CVA). Project specifications require a CVA of 26.9 cm based on the 95th percentile. Supplemental Vertical Accuracy (SVA) will be computed on each individual land cover category other than open terrain. Target specifications for SVA are 26.9 cm based on the 95th percentile. NDEP and ASPRS testing methodologies allow individual SVA's to fail as long as the mandatory CVA passes project specifications.
0.133 m
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 Sandy LiDAR project satisfies the criteria:
Lidar dataset tested 0.133 m vertical accuracy at 95% confidence level in open terrain, based on RMSEz (0.068 m) x 1.9600.
0.190 m
Based on the vertical accuracy testing conducted by Dewberry, using NDEP and ASPRS methodology, consolidated vertical accuracy (CVA) is computed using the 95th percentile method. The dataset for Connecticut Sandy LiDAR project tested 0.190 m consolidated vertical accuracy at 95th percentile in all land cover categories combined. The 5% outliers consisted of 6 checkpoints that are larger than the 95th percentile. These checkpoints have DZ values ranging between 0.192 and 0.237 m.
0.096 m
Based on the vertical accuracy testing conducted by Dewberry, using NDEP and ASPRS methodology, supplemental vertical accuracy (SVA) is computed using the 95th percentile method. The dataset for the Connecticut Sandy LiDAR project satisfies the criteria:
Lidar dataset tested 0.096 m supplemental vertical accuracy at 95th percentile in the urban land cover category.
0.192 m
Based on the vertical accuracy testing conducted by Dewberry, using NDEP and ASPRS methodology, supplemental vertical accuracy (SVA) is computed using the 95th percentile method. The dataset for the Connecticut Sandy LiDAR project satisfies the criteria:
Lidar dataset tested 0.192 m supplemental vertical accuracy at 95th percentile in the forested and fully grown land cover category.
0.198 m
Based on the vertical accuracy testing conducted by Dewberry, using NDEP and ASPRS methodology, supplemental vertical accuracy (SVA) is computed using the 95th percentile method. The dataset for the Connecticut Sandy LiDAR project satisfies the criteria:
Lidar dataset tested 0.198 m supplemental vertical accuracy at 95th percentile in the brush lands and trees land cover category.
0.198 m
Based on the vertical accuracy testing conducted by Dewberry, using NDEP and ASPRS methodology, supplemental vertical accuracy (SVA) is computed using the 95th percentile method. The dataset for the Connecticut Sandy LiDAR project satisfies the criteria:
Lidar dataset tested 0.198 m supplemental vertical accuracy at 95th percentile in the tall weeds and crops land cover category.
Data for the USGS Connecticut Sandy LiDAR project was acquired by Leading Edge Geomatics (LEG)
The project area included approximately 1,526 contiguous square miles for portions of Connecticut. LiDAR sensor data were collected with the Riegl 680i LiDAR system. The data was delivered in UTM Zone 18, horizontal datum NAD83(2011), vertical datum NAVD88, Geoid 12A. Deliverables for the project included a raw (unclassified) calibrated LiDAR point cloud, survey control, and a final acquisition/calibration report.
A preliminary RMSEz error check is performed at this stage of the project life cycle in the raw LiDAR dataset against GPS static and kinematic data and compared to RMSEz project specifications. The LiDAR data is examined in open, flat areas away from breaks. Lidar ground points for each flightline generated by an automatic classification routine are used.
Overall the LiDAR data products collected by LEG meet or exceed the requirements set out in the Statement of Work. The quality control requirements of LEGs quality management program were adhered to throughout the acquisition stage fo this project to ensure product quality.
LIDAR acquisition began on April 27, 2014 and was completed on May 29, 2014. A total of 40 survey missions were flown to complete the project. LEG utilized an Riegl 680i LiDAR system for the acquisition. The flight plan was flown as planned with no modifications. There were no unusual occurrences during the acquisition and the sensor performed within specifications. There were 428 flight lines required to complete the project.
The initial step of calibration is to verify availability and status of all needed GPS and Laser data against field notes and compile any data if not complete.
Subsequently the mission points are output using Trimble Business Center (TBC), initially with default
values from Trimble or the last mission calibrated for system. The initial point generation
for each mission calibration is verified within Microstation/Terrascan for calibration errors.
If a calibration error greater than specification is observed within the mission, the roll pitch
and scanner scale corrections that need to be applied are calculated. The missions with the
new calibration values are regenerated and validated internally once again to ensure
quality.
All missions are validated against the adjoining missions for relative vertical biases and
collected GPS validation points for absolute vertical accuracy purposes.
On a project level, a supplementary coverage check is carried out to ensure no data voids
unreported by Field Operations are present.
The initial points for each mission calibration are inspected for flight line errors, flight line overlap, slivers or gaps in the data, point data minimums, or issues with the LiDAR unit or GPS. Roll, pitch and scanner scale are optimized during the calibration process until the relative accuracy is met.
Relative accuracy and internal quality are checked using at least 3 regularly spaced QC blocks in which points from all lines are loaded and inspected. Vertical differences between ground surfaces of each line are displayed. Color scale is adjusted so that errors greater than the specifications are flagged. Cross sections are visually inspected across each block to validate point to point, flightline to flightline and mission to mission agreement.
For this project the specifications used are as follow:
Relative accuracy <= 7cm RMSEZ within individual swaths and <=10 cm RMSEZ or within swath overlap (between adjacent swaths).
UTM coordinate system, meters, zone 18, horizontal datum NAD83(2011), vertical datum NAVD88, Geoid 12A
Airborne Global Positioning System Data
Inertial Measurement Unit
201405
Calibrated LiDAR Point Cloud LAS 1.2 format
Leading Edge Geomatics (LEG)
mailing and physical address
2384 Route 102
Lincoln
NB
E3B 7G1
Canada
(506) 446-4403
Monday to Friday, 8 - 5, AST
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 (1,500 m x 1,500 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. During this water classification routine, points that are within 1 meter of the hydrographic features are moved to class 10, an ignored ground due to breakline proximity. In addition to classes 1, 2, 9, and 10, there is a Class 7, noise points . This class was used for both low and high noise 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
Class 10 = Ignored
The LAS header information was verified to contain the following:
Class (Integer)
Adjusted GPS Time (0.0001 seconds)
Easting (0.003 m)
Northing (0.003 m)
Elevation (0.003 m)
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
201407
Final Tiled LiDAR datasets
Dewberry - Geospatial Services Group
Keith Patterson
Project Manager
mailing and physical address
1000 N. Ashley Drive, Suite 801
Tampa
FL
33602
USA
813.421.8635
813.225.1385
kpatterson@dewberry.com
8:00 - 5:00 EST
Vector
Point
43497937966
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(2011)
Geodetic Reference System 80
6378137.0
298.257222
North American Vertical Datum of 1988 (Geoid 12A)
0.000100
meters
Explicit elevation coordinate included with horizontal coordinates
LiDAR points in LAS 1.2 format
none
U.S. Geological Survey
Program Manager
mailing and physical address
1400 Independence Road
Rolla
MO
65401
USA
(573) 308-3810
pemmett@usgs.gov
Downloadable Data
This data was produced for the U.S. Geological Survey according to specific project requirements. This information is provided "as is". Further documentation of this data can be obtained by contacting: USGS, 1400 Independence Road, Rolla, MO 65401. Telephone (573) 308-3612.
20150205
U.S. Geological Survey
Patrick Emmett
Program Manager
mailing and physical address
1400 Independence Road
Rolla
MO
65401
USA
(573)308-3810
pemmett@usgs.gov
FGDC Content Standards for Digital Geospatial Metadata
FGDC-STD-001-1998
local time
http://www.esri.com/metadata/esriprof80.html
ESRI Metadata Profile