Data Acquisition:

Airborne Laser Scanner (ALS) data was acquired from a fixed wing aircraft from 23 March 2021 to 27 March 2021, using AAM's Optech Galaxy Prime 473 LiDAR system.

Survey Specification:

- Scanner: Optech Galaxy Prime 473

- Flying height: 1850 m AGL

- Scan angle: 9 degrees

- Pulse rate: 450 kHz

- Swath overlap: 60%

- Swath points per M^2: 8 with overlap flag to achieve 16 pts per sq m.

Data Processing:

Laser strikes were classified into ground and non-ground points using a single algorithm across the project area. Manual checking and editing of the data classification further improved the quality of the ground point classification.The definition of the ground may be less accurate in isolated pockets of dissimilar terrain/vegetation combinations.

AAM uses proprietary ground classification routines to provide the initial automated ground / non-ground classification and generate the initial ground surface. The classification is then manually edited to improve the ground classification to ICSM level 2 standard. Following this process, further automated techniques are used to classify the other classes shown above to ICSM level 1 standard.

RTX processing was used to calculate the GPS trajectory solution. Trimble CenterPoint® RTX™ is a proprietary GPS, GLONASS, BeiDou, and QZSS enabled technology that provides high accuracy GNSS positioning worldwide without the use of traditional local base stations or a VRS network. By combining real-time data from a global reference station infrastructure with innovative positioning and compression algorithms, Trimble RTX technology computes centimeter-level positions based on satellite orbit and clock information. Ground surveyed test point sites were acquired by WSP, these allowed an assessment of the accuracy of the ALS point cloud data.

Ground data in this volume has been compared to test points obtained by field survey and assumed to be error-free. The test points were located on open clear ground. Comparison of the field test points with elevations interpolated from measured data, after removing the mean offset of -0.118m yielded the following accuracy assessment:

- Test point sites: 5

- No. Points: 154

- Mean Difference: 0.00

- Std Deviation (m): 0.023

- RMS (m): 0.023

All product deliverables supplied in terms of NZTM map projection and NZVD2016 vertical datum.

Classification of the point cloud followed the classifications scheme below:

1- Unclassified

2 - Ground

3 - Low Vegetation

4 - Medium Vegetation

5 - High Vegetation

6 - Buildings

7 - Low Noise

9 - Water

11 - Road surface

17 - Bridge deck

18 - High Noise

The Paved Ground classification has been applied manually, transferring the existing paved classification from the 2015 Hutt CC LiDAR, and using the Hutt CC road surface assets to capture new roads, parking and paths.

Paved ground (22) and Bridges (10) as detailed in the survey report have been reclassified to 11 and 17 respectively, to match the ASPRS guidelines for file format 1.4(6).

The DEM was generated using ground and paved ground classes.

The DSM was generated using ground and non-ground classes.

Elevation Grids were derived using the LAStools las2dem command. This tool reads LIDAR points from the LAS/LAZ format (or some ASCII formats) and triangulates them temporarily into a TIN with a user defined interpolation distance. LAStools then applies a TIN to raster conversion to create the 1m DEM raster dataset.

The main Hutt River system in the DEM has been Hydro-flattened/hydro-sloped.

The deliverables to LINZ were:

1m gridded bare earth digital elevation model (DEM)

1m gridded digital surface model (DSM)

Classified point cloud