Marlborough LiDAR Index Tiles (2020-2021)

Data Acquisition:

Airborne Laser Scanner (ALS) data was acquired from a fixed wing aircraft between 10 February 2020, 1 March 2020, 29/30 April 2020, 6/7 May 2020, 8/9/14 June 2020, 3/14 July 2020, 11/14/17 August 2020, 18 December 2020, 23 January 2021, 26 March 2021, 7/18/19 April 2021, 4/6/21 May 2021, 2 July 2021, using Aerial Surveys Optech Orion Galaxy PRIME system.



Survey Specification:
 Scanner: Optech Galaxy PRIME
 Flying Height: 2925 m AMGL
 Scan Angle FOV: 52 degrees
 Scan Frequency: 45 Hz
 Pulse Rate: 400 kHz
 Swath Overlap: 55%
 Swath Points Per M2: 4


Data Processing:

The LiDAR sensor positioning and orientation (POS) was determined using the collected GPS/IMU datasets and Applanix POSPac software.

Base Station Positions: PPRTX.

The POS data was combined with the LiDAR range files and used to generate LIDAR point clouds in NZTM and ellipsoidal heights. This process was undertaken using Optech LMS LiDAR processing software. The data was checked for completeness of coverage. The relative fit of data in the overlap between strips was also checked.


The height accuracy of the ground classified LiDAR points was checked using open land-cover survey check site data collected by Sounds Surveying Ltd. This was done by calculating height differences statistics between a TIN of the LiDAR ground points and the checkpoints. The standard deviation statistic is 0.046 m; a RMS of 0.059 m; a CI95 of 0.116m and the average difference is -0.038 m. LiDAR is relative to the control check points.

The positional accuracy of the LiDAR data has been checked by overlaying Sounds Surveying Ltd surveyed data over the LiDAR data displayed coded by intensity. The data was found to fit well in position.


All spatial data for this project provided in terms of NZTM2000 horizontal and NZVD2016 vertical datum. The data was converted from NZGD2000 ellipsoidal heights into the orthometric height system using the LINZ NZGeoid16 separation model.

The point cloud data was then classified with TerraSolid LiDAR processing software into ground and above ground returns usin g a sparse triangular irregular network (TIN) from the supplied LiDAR points and then classified according to required classes by using automatic iterative process followed by manual correction. Terrascan’s inbuilt macros with different parameters were used to classify low points, ground points, buildings, temporary features and finally vegetation.


Classification of the point cloud followed the classification scheme below:

1 - Unclassified

2 - Ground

3 - Low Vegetation

4 - Medium Vegetation

5 - High Vegetation

6 - Buildings
7 - Low Noise

9 - Water
18 - High Noise

The Digital Elevation Model (DEM) was derived from ground (2) class points using a point to TIN and TIN to Raster process, with a Natural Neighbour interpolation and resolution of 1 m. Hydro-flattening was performed as per part 7 of PGF version New Zealand National Aerial Lidar Base Specification Jan 2020.



The Digital Surface Model (DSM) was generated from a triangulated model of the first return points after removal of noise, then converted to a raster with a resolution of 1 m.

The deliverables to LINZ were:

1m gridded bare earth digital elevation model (DEM)
1m gridded digital surface model (DSM)

Classified point cloud