2014 NJMC Lidar: Hackensack Meadowlands

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This project footprint shows the coverage for the 2014 collection over the New Jersey Meadowlands.

Date that the source FGDC record was last modified.

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In preparation for data collection, QSI reviewed the project area and developed a specialized flight plan to ensure complete coverage of the Hackensack Meadowlands LiDAR study area at the target point density of equal-to-less-than 8.0 points/m2 (0.74 points/ft2). Acquisition parameters including orientation relative to terrain, flight altitude, pulse rate, scan angle, and ground speed were adapted in order to optimize flight paths and flight times while meeting all contract specifications.

Factors such as satellite constellation availability and weather windows must be considered during the planning stage. Logistical considerations including private property access and potential air space restrictions were reviewed. Water levels and tidal conditions along the Hackensack River and surrounding Meadowlands were monitored to ensure airborne acquisition was completed during tidal periods below predicted Mean Sea Level (MSL). Any weather hazards or conditions affecting the flight were continuously monitored due to their potential impact on the daily success of airborne and ground operations

The Hackensack Meadowlands LiDAR survey was accomplished using a Leica ALS50 phase II system mounted in a Cessna Caravan. Table 3 summarizes the settings used to yield an average pulse density of less than 8.0 pulses/m2 (0.74 pulses/ft2) over the Hackensack Meadowlands project area. The Leica laser system records up to four range measurements (returns) per pulse. It is not uncommon for some types of surfaces (e.g., dense vegetation or water) to return fewer pulses to the LiDAR sensor than the laser originally emitted. The discrepancy between first return and overall delivered density will vary depending on terrain, land cover, and the prevalence of water bodies. All discernible laser returns were processed for the output dataset.

1. Resolve kinematic corrections for aircraft position data using kinematic aircraft GPS and static ground GPS data. 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.

2. 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 (ASPRS v. 1.3) format. Convert data to orthometric elevations by applying a geoid12a correction.

3. Import raw laser points into manageable blocks (less than 500 MB) to perform manual relative accuracy calibration and filter erroneous points. Classify ground points for individual flight lines.

4. 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.

5. Classify resulting data to ground and other client designated ASPRS classifications. Assess statistical absolute accuracy via direct comparisons of ground classified points to ground control survey data.

6. Generate bare earth models as triangulated surfaces. Generate highest hit models as a surface expression of all classified points. Export all surface models as ESRI GRIDs in EDRAS Imagine (.img) format at a 2.0 foot pixel resolution.

7. Correct intensity values for variability and export intensity images as GeoTIFFs at a 2.0 foot pixel resolution.

The NOAA Office for Coastal Management (OCM) received LAS point clouds from the New Jersey Office of Information Technology in February 2015. The files contained lidar elevation and intensity measurements. The data were in New Jersey State Plane coordinates (ft) and orthometric elevations (ft). OCM performed the following processing for data storage and Digital Coast provisioning purposes:

1. LAS files were compressed to LAZ format using laszip.

2. LAS files were voided of points below -25 m and as assumed to be error.

3. LAS points were converted to adjusted GPS time.

4. LAS files were transformed from New Jersey State Plane horizontal coordinates (ft) and NAVD88 orthometric vertical heights (ft) to geographic coordinates (decimal degrees) and ellipsoidal heights (meters).