Quantum Spatial, Inc.
20201231
Task Name: Glacier Bay Delivery 2 USGS Contract: G16PC00016, Task Order: 140G0219F0200
Lidar Point Cloud
Product: QL1 LAS 1.4
Geographic Extent: This NIR Lidar dataset and derived products encompass an area covering approximately 863,775 acres of South East Alaska. The QL1 project area encompased 124,539 acres of the total area.
Dataset Description:The Glacier Bay 3DEP Lidar project called for the planning, acquisition, and processing of Lidar data collected at an aggregate nominal pulse spacing (ANPS) of 0.35 meters for all QL1 areas. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 1.3. The data was developed based on the NAD83(2011) horizontal datum and NAVD88 (GEOID12B) vertical datum. Data was projected in UTM Zone 8N. All units are in meters. RAW flight line swaths were processed to create 593 classified LAS 1.4 files delineated in 1,000 m x 1,000 m tiles. (Please note tiles GB_01023 and GB_02356 do not include valid point return data as they are entirely over areas of open water and thus have not been included in this submission.) Each LAS file contains Lidar point information, which has been calibrated, controlled, and classified. Additional derived products include hydro-flattened DEMs, Highest Hit DSMs, Intensity Images, and 3D breaklines of rivers and lakes within the study area. Supplemental data includes DZ Orthos, Flightline Shapes, Swath Coverage Shapes, and Ground Survey Shapes.
Ground Conditions: Lidar was collected in summer 2019 and summer 2020, while the presence of snow on the ground was at a minimum and rivers were at or below normal levels. In order to post process the Lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines DOWL, on behalf of QSI, collected a total of 261 ground control points distributed throughout the Glacier Bay Delivery 2 project area. Lidar data was calibrated to these known ground locations. An additional 226 independent accuracy checkpoints, 88 in Bare Earth and Urban landcovers (NVA points) and 138 in Shrub, Tall Grass, and Forest categories (VVA points) were used to assess the vertical accuracy of the project data. These checkpoints were not used to calibrate or post process the data.
The purpose of the Lidar data was to produce a high accuracy 3D dataset that meets all necessary standards laid out by the Glacier Bay contract. The raw Lidar point cloud data were used to create classified Lidar LAS files, hydro-flattened DEMs, Highest Hit DSMs, Intensity Images, and 3D breaklines of rivers and lakes within the study area.
CONTRACTOR: Quantum Spatial, Inc.
Ground Control Points were acquired by DOWL for Quantum Spatial Inc.
2019 Data acquisition was coordinated by Quantum Spatial through Eagle Aerial. Quantum Spatial performed the 2020 data acquisition. All Lidar data calibration, and follow-on processing were completed by Quantum Spatial.
U.S. Geological Survey (USGS) - National Geospatial Program (NGP) Lidar Base Specification v1.3
Riegl VQ-1560i
Unlimited
0.50
4
0.21
22.66
1,830
140
58.5
142 lines per seconds
700
3
0.89
1064
1
0.18
2050
50
National Geodetic Survey (NGS) Geoid12B
0.26
0.073
88
1.4
6
Withheld (ignore) points are identified in these files using the standard LAS Withheld bit.
Overlap points were identified in these files using the standard LAS overlap bit.
16
1
Processed, but Unclassified
2
Bare earth ground
7
Low Noise
9
NIR Water Surface
18
High Noise
20
Ignored Ground Near Breaklines
22
Temporal Exclusion Points
20190628
20200731
ground condition: Acquisition below aircraft free of smoke, fog and cloud cover. Presence of snow on the ground was at a minimum
None Planned
-138.701010
-135.564209
59.250147
58.325708
288665.062317
467000.000122
6568049.791566
6470640.918104
none
model
LAS Point Cloud
remote sensing
Elevation data
Lidar
none
Alaska
Glacier Bay, Gustavus, Johns Hopkins Glacier, Grand Pacific Glacier, Lamplugh Glacier, Reid Glacier, Brady Glacier, Muir Glacier
Glacier Bay Delivery 2
No restrictions apply to these data.
None. However, users should be aware that temporal changes may have occurred since this dataset was collected and that some parts of these data may no longer represent actual surface conditions. Users should not use these data for critical applications without a full awareness of its limitations. Acknowledgment of the U.S. Geological Survey would be appreciated for products derived from these data.
Applanix PosPac 7.1, Microstation Version 8.0, TerraScan Version 19, TerraModeler Version 19, TerraMatch Version 19, ESRI ArcGIS 10.5, Windows 10 Operating System
Classified LAS files were tested by QSI for both vertical and horizontal accuracy. All data is seamless from one tile to the next, no gaps or no data areas.
These LAS data files include all data points collected. No points have been removed or excluded. A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. The raw point cloud is of good quality and data passes Non-Vegetated Vertical Accuracy specifications.
This data set was produced to meet ASPRS Positional Accuracy Standard for Digital Geospatial Data (2014) for a 10-cm RMSEz Vertical Accuracy Class. The NVA was tested against ground classified points with 88 checkpoints located in bare earth and urban (non-vegetated) areas. Project specifications also call for VVA reporting for "shrubland", "tall grass", and "forested" land cover classes. The target VVA is: 29.4 cm at the 95th percentile, based on the 95th percentile error in all vegetated land cover classes combined. This is a target accuracy. The VVA was tested against ground classified points with 138 checkpoints located in shrubland, tall grass, and forested areas. The checkpoints were distributed throughout the project area and were surveyed using GPS techniques. See survey report for additional survey methodologies. AccuracyZ has been tested to meet 19.6 cm or better Non-Vegetated Vertical Accuracy at 95% confidence level using RMSE(z) x 1.9600 as defined by the National Standards for Spatial Data Accuracy (NSSDA); assessed and reported using National Digital Elevation Program (NDEP)/ASRPS Guidelines.
0.073
Tested 0.073 meters NVA at a 95% confidence level using RMSE(z) x 1.9600 as defined by the National Standards for Spatial Data Accuracy (NSSDA). The NVA of the classified lidar point cloud was calculated using 88 independent checkpoints located in the Bare Earth and Urban land cover categories with a resulting RMSE of 0.036 meters.
0.211
Tested 0.211 meters VVA at the 95th percentile. The VVA of the of the classified lidar point cloud was calculated using 138 independent checkpoints located in forest, shrub, and tall grass land cover classes.
Lidar Pre-Processing:
1. Review flight lines and data to ensure complete coverage of the study area and positional accuracy of the laser points.
2. Resolve kinematic corrections for aircraft position data using kinematic aircraft GPS and static ground GPS data.
3. Develop a smoothed best estimate of trajectory (SBET) file that blends post-processed aircraft position with sensor head position and attitude recorded throughout the survey.
4. Calculate laser point position by associating SBET position to each laser point return time, scan angle, intensity, etc. Create raw laser point cloud data for the entire survey in *.las format. Convert data to orthometric elevations by applying a geoid correction.
5. Import raw laser points into manageable blocks to perform manual relative accuracy calibration and filter erroneous points. Classify ground points for individual flight lines.
6. Using ground classified points per each flight line, test the relative accuracy. Perform automated line-to-line calibrations for system attitude parameters (pitch, roll, heading), mirror flex (scale) and GPS/IMU drift. Calculate calibrations on ground classified points from paired flight lines and apply results to all points in a flight line. Use every flight line for relative accuracy calibration.
7. Adjust the point cloud by comparing ground classified points to supplemental ground control points.
Base_Station_Control, SBETs, GCPs, RAW_Lidar
20201231
Lidar Post-Processing:
1. Classify data to ground and other client designated classifications using proprietary classification algorithms.
2. Manually QC data classification
3. After completion of classification and final QC approval, calculate NVA and VVA, and density information for the project using ground control quality check points. For Ql1 areas single swath nominal pulse spacing (NPS) was designed to be 0.50 at nadir and the aggregate Nominal Pulse Spacing (ANPS) was calculated to be 0.21 using all valid first return points.
20201231
Vector
Point
14,562,633,443
Universal Transverse Mercator
8
0.9996
135.000000
0.0
500000
0.0
coordinate pair
0.01
0.01
meters
North American Datum of 1983 (2011)
Geodetic Reference System 80
6378137
298.257222101
North American Vertical Datum of 1988 Geoid 12B
0.01
Meters
Explicit elevation coordinate included with horizontal coordinates
20201231
20201231
Quantum Spatial, Inc.
mailing and physical
1100 NE Circle Blvd., Suite 126
Corvallis
OR
97330
USA
541-752-1204
FGDC Content Standard for Digital Geospatial Metadata
FGDC-STD-001-1998
None
None
None
Unclassified
None
None
None