2D LiDAR georeferencing in Python
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georeference starting on uncertainty computation Apr 25, 2018
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README.md Update README.md Mar 2, 2017
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README.md

LiDAR_georeference

Open source code implementing the basic lidar georeferencing functions described in Baltsavias (1999),and more recently along with propagation of uncertanties for LiDAR points in Glennie (2007)[1] and Schaer et al (2007) [2].

Based on MATLAB code developed for a PhD project - which can still be found in ./MATLAB. Future development will be in Python, unless someone wants to take up making a C version - although part of the point is to make the process fairly easy to understand.

If you want to contribute, use what's in ./MATLAB as a base, and if you don't see it's equivalent in Python then give it a shot. Or, if you can make any Python code you see here better/faster/more efficient/more functional please do so!

Rough plan:

  • implement the basic equations for 2D and 3D scanners in Python underway
  • implement uncertainty propagation using SymPy to handle deriving the required partial derivatives (q2 2017)
  • implement output to .LAS, or postgres-pointcloud (q2 2017). Las is trickier because of user defined fields which will be required (see point above)
  • ...and implement output to an Entwine index, skipping the standard output to LAS/LAZ tiles entirely. All these outputs will depend on PDAL (http://pdal.io)
  • implement binary reading of Reigl LiDAR scanner output (q3 2017)

pipe dreams:

  • read trajectory input from Novatel .bin files output from Inertial explorer
  • read trajectory input from binary OxTS NCOM files, will need proj.4 to project (once) from an ECEF frame to some cartesian frame.
  • Schaer (2007)[2] Q-factors
  • faster implementation for real-time point generation and QA.
  • maybe even it's own kalman filter implementation to do tightly-coupled GPS+inertial trajectory determination, avoiding the proprietary blackbox step currently required (beyond my skills at present)

[1] Glennie, C. (2007). Rigorous 3D error analysis of kinematic scanning LIDAR systems. Journal of Applied Geodesy, 1, 147–157. http://doi.org/10.1515/JAG.2007.

[2] Schaer, P., Skaloud, J., Landtwing, S., & Legat, K. (2007). Accuracy estimation for laser point cloud including scanning geometry. In Mobile Mapping Symposium 2007, Padova.