| | 1 | = Lidar Processing Protocol = |
| | 2 | |
| | 3 | 1. Copy data onto windows machine |
| | 4 | |
| | 5 | 2. Process the navigation (IPAS and GrafNav) |
| | 6 | Check roll vs time graph in IPAS (stick in ticket for future reference) |
| | 7 | Check PDOP and Combined Separation |
| | 8 | Iterate until we get the best trajectory we can |
| | 9 | |
| | 10 | 3. Process the LIDAR using the finalised calibration parameters |
| | 11 | |
| | 12 | In the case of images that exhibit roll offsets AFTER application of the boresight parameters then apply the following procedure: |
| | 13 | * A) Opposing flight lines (fully overlapping) |
| | 14 | * Can observe profiles across track ideally for an area of flat terrain for each pair of images and manually tweak the roll values to remove bias |
| | 15 | * Record the final “tweaks” in file XYZW |
| | 16 | |
| | 17 | * B)Parallel flight lines (semi-overlap, all same direction) |
| | 18 | * Using overlap region for each pair of images can manually tweak roll until bias removed |
| | 19 | * Record the final “tweaks” in file XYZW |
| | 20 | |
| | 21 | * C) Parallel flight lines (semi-overlap, opposing direction) |
| | 22 | * Look for zig zagging elevations on all flight lines eg /\/\/\ (beware of true sloping terrain) |
| | 23 | * tweak roll manually until flight lines look more like ------ |
| | 24 | * Record the final “tweaks” in file XYZW |
| | 25 | |
| | 26 | * D) Non overlapping flightlines |
| | 27 | * If we have a roll offset model (produced by analyzing the tweaks and other info noted in A to C above) that we know corrects the data then use this |
| | 28 | * Else deliver as is informing PI there is possible (probable) bias in the data, and give an estimate of the magnitude if possible. |
| | 29 | |
| | 30 | '''For each image in each data set note the following:''' |
| | 31 | * Calibration file used |
| | 32 | * Flight height and direction |
| | 33 | * Roll correction used |
| | 34 | * Approx position (in E/N?) |
| | 35 | * Time (from take off) of start of acquisition |
| | 36 | |
| | 37 | 4. Collate the data and analyse it – look for trends within the flight data sets (per project) and also the complete set of data (all projects together). |