New York City Department of Information Technology and Telecommunications
20181109
New York City 2017 LiDAR; Classified Point Cloud
Lidar point cloud
Product: Calibrated LiDAR version 1.4 .las tiles, classified for subsequent derivatives.
Geographic Extent: New York, Bronx, Kings, Queens, and Richmond Counties in New York plus an additional 100 m buffer.
Dataset Description: In May 2017, Quantum Spatial (QSI) was contracted by Applied Geographics (AppGeo) to collect topographic and topobathymetric Light Detection and Ranging (LiDAR) data for the City of New York (NYC). QSI collected and processed traditional (near infrared wavelength, Leica ALS80 sensor) LiDAR over the topographic AOI, and spliced together NIR and bathymetric LiDAR (green wavelength, Riegl VQ-880-G sensor) for the topobathymetric AOI. LiDAR point data are delivered in 2,500 X 2,500 ft tiles.
Ground Conditions: Topographic LiDAR was collected in May 2017 with approximately 50% leaf-off conditions. Bathymetric data was collected in July 2017 during low tide time windows. Ground control data were used to geospatially correct the LiDAR point cloud and used to perform quality assurance checks on the final products. In addition, Continuously Operating Reference Stations (CORS) from the New York State Spatial Reference Network (NYSNet) were used to geospatially correct the aircraft positional coordinate data and as base stations for GSP collection. All ground survey work to support the topobathymetric LiDAR acquisition was conducted during the NIR LiDAR collection window. Land cover class check points were also collected throughout the study area to evaluate vertical accuracy.
Data were collected to help support the City’s many agencies in planning and analysis related to their key initiatives. LiDAR derived DEMs will be crucial for long-term land use planning and assessing the impacts of sea level rise.
As part of a federal Disaster Recovery Community Development Block Grant ("CDBG-DR"), the New York City (NYC) Mayor’s Office of Recovery and Resiliency (ORR), Department of Information Technology and Telecommunications (DoITT) and Department of Parks and Recreation (Parks) contracted with AppGeo for the acquisition of Light Detection and Ranging (LiDAR) data, developing LiDAR-derived products, and generating high-resolution land cover. Quantum Spatial Inc. was subcontracted for acquisition and processing of the LiDAR data.
USGS-NGP Base Lidar Specification v1.4
Leica ALS80 (Topographic)/Riegl VQ-880-G (Bathymetric)
unlimited
0.313/0.256
10.24/15.24
0.313/0.256
10.24/15.24
1800/450
145/120
30/40
48/80
314.8/245
2.5/1.5
.396/.45
1064/532
1/1
22/0.7
898/327.5
6060
NAD 1983 New York Long Island (ftUS)
National Geodetic Survey (NGS) Geoid12B
Not calculated. Inferred 13.1 cm RMSE
0.007/0.010
151/115
1.4
6
Withheld (ignore) points were identified in these files using the standard LAS Withheld bit.
Swath "overage" 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
Water
10
Ignored Ground
17
Bridge Decks
25
Subway/Transit stairwells
40
Bathymetric Bottom
41
Green Near Water Surface
45
Water Column
20170503
20170726
ground condition
As needed
-74.257499
-73.698030
40.916459
40.491252
None
LAS Point Cloud
Elevation Data
Lidar
None
New York City
New York County
Bronx County
Kings County
Queens County
Staten Island County
No restrictions apply to these data.
In some areas of heavy vegetation or forest cover, there may be relatively few points in the LiDAR data.
Data covers the entire area specified for this project.
The classified point cloud was inspected and passed accuracy specifications.
The following outlines the processing of the point cloud data:
1. Flightlines and data were reviewed to ensure complete coverage of the study area and positional accuracy of the laser points.
2. Laser point return coordinates were computed using Waypoint Inertial Explorer and Leica Cloudpro software based on independent data from the LiDAR system, IMU, and aircraft.
3. The raw LiDAR file was assembled into flight lines per return with each point having an associated x, y, and z coordinate.
4. Visual inspection of swath to swath laser point consistencies within the study area were used to perform manual refinements of system alignment.
5. Custom algorithms were designed to evaluate points between adjacent flight lines. Automated system alignment was computed based upon randomly selected swath to swath accuracy measurements that consider elevation, slope, and intensities. Specifically, refinement in the combination of system pitch, roll, and yaw offset parameters optimize internal consistency.
6. Noise (e.g., pits and birds) was filtered using post-processing software, based on known elevation ranges and included the removal of any cycle slips.
7. Using TerraScan and Microstation, ground classifications utilized custom settings appropriate to the study area.
8. The corrected and filtered return points were compared to the ground survey points collected to verify the vertical accuracy.
2018
Point
NAD 1983 StatePlane New York Long Island FIPS 3104 Feet
40.66666666666666
41.03333333333333
-74.0
40.16666666666666
984250.0
0.0
coordinate pair
0.00000002687262634637478
0.00000002687262634637478
foot_us
D North American 1983
GRS 1980
6378137.0
298.257222101
20181121
New York City Department of Information Technology and Telecommunications
mailing and physical
2 Metrotech
Brooklyn
NY
11201
USA
(718)403-8214
FGDC Content Standard for Digital Geospatial Metadata
FGDC-STD-001-1998