2017 NYC Topobathy Lidar: New York City

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.

The following are the USGS lidar fields in JSON:

{

"ldrinfo" : {

"ldrspec" : "USGS-NGP Base Lidar Specification v1.4",

"ldrsens" : "Leica ALS80 (Topographic)/Riegl VQ-880-G (Bathymetric)",

"ldrmaxnr" : "unlimited",

"ldrnps" : "0.313/0.256",

"ldrdens" : "10.24/15.24",

"ldranps" : "0.313/0.256",

"ldradens" : "10.24/15.24",

"ldrfltht" : "1800/450",

"ldrfltsp" : "145/120",

"ldrscana" : "30/40",

"ldrscanr" : "48/80",

"ldrpulsr" : "314.8/245",

"ldrpulsd" : "2.5/1.5",

"ldrpulsw" : ".396/.45",

"ldrwavel" : "1064/532",

"ldrmpia" : "1/1",

"ldrbmdiv" : "22/0.7",

"ldrswatw" : "898/327.5",

"ldrswato" : "6060",

"ldrcrs" : "NAD 1983 New York Long Island (ftUS)",

"ldrgeoid" : "National Geodetic Survey (NGS) Geoid12B"

},

"ldraccur" : {

"ldrchacc" : "Not calculated. Inferred 13.1 cm RMSE",

"rawnva" : "0.007/0.010",

"rawnvan" : "151/115"

},

"lasinfo" : {

"lasver" : "1.4",

"lasprf" : "6",

"laswheld" : "Withheld (ignore) points were identified in these files using the standard LAS Withheld bit.",

"lasolap" : "Swath "overage" points were identified in these files using the standard LAS overlap bit.",

"lasintr" : "16",

"lasclass" : {

"clascode" : "1",

"clasitem" : "Processed, but Unclassified"

},

"lasclass" : {

"clascode" : "2",

"clasitem" : "Bare Earth Ground"

},

"lasclass" : {

"clascode" : "7",

"clasitem" : "Low Noise"

},

"lasclass" : {

"clascode" : "9",

"clasitem" : "Water"

},

"lasclass" : {

"clascode" : "10",

"clasitem" : "Ignored Ground"

},

"lasclass" : {

"clascode" : "17",

"clasitem" : "Bridge Decks"

},

"lasclass" : {

"clascode" : "25",

"clasitem" : "Subway/Transit stairwells"

},

"lasclass" : {

"clascode" : "40",

"clasitem" : "Bathymetric Bottom"

},

"lasclass" : {

"clascode" : "41",

"clasitem" : "Green Near Water Surface"

},

"lasclass" : {

"clascode" : "45",

"clasitem" : "Water Column"

}

}}

Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office for Coastal Management or its partners

Data is available online for bulk or custom downloads

None

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.

Absolute accuracy was assessed using Non-vegetated Vertical Accuracy (NVA) reporting designed to meet guidelines presented in the FGDC National Standard for Spatial Data Accuracy. NVA compares known ground quality assurance point data collected on open, bare earth surfaces with level slope (<20 degrees) to the triangulated surface generated by the LiDAR points. NVA is a measure of the accuracy of LiDAR point data in open areas where the LiDAR system has a high probability of measuring the ground surface and is evaluated at the 95% confidence interval (1.96 * RMSE).

The mean and standard deviation (sigma) of divergence of the ground surface model from ground check point coordinates are also considered during accuracy assessment. These statistics assume the error for x, y and z is normally distributed, and therefore the skew and kurtosis of distributions are also considered when evaluating error statistics. For the New York City Topographic and Topobathymetric LiDAR survey, 151 ground check points were withheld from the calibration and post-processing of the LiDAR point cloud, resulting in a non-vegetated vertical accuracy of 0.242 feet (0.074 meters), with 95% confidence. RMSE = 0.038 meters.

Bathymetric (submerged or along the water’s edge) check points were also collected in order to assess the submerged surface vertical accuracy. Assessment of 115 bathymetric check points resulted in a vertical accuracy of 0.208 feet (0.064 meters), evaluated at the 95th percentile.

QSI also assessed absolute accuracy using 2,416 ground control points. Although these points were used in the calibration and post-processing of the LiDAR point cloud, they still provide a good indication of the overall accuracy of the LiDAR dataset, and therefore have been provided in the Project Report, linked elsewhere in the metadata record.

The classified point cloud was inspected and passed accuracy specifications.

Data covers the entire area specified for this project.

Data is backed up to tape and to cloud storage.

Data were collected and processed by Quantum Spatial, Inc. for the New York City Department of Information Technology and Telecommunications. The data were retrieved from the New York State GIS FTP website [ address: ftp://ftp.gis.ny.gov/elevation/LIDAR/NYC_TopoBathymetric2017/ ] by the NOAA Office for Coastal Management (OCM), where the data were processed to make it available for custom download from the Data Access Viewer (DAV) and bulk download from https