Thesis subject

MSc thesis topic: Optimizing UAV flight patterns for forest reconstruction – comparison with UAV LiDAR

Unmanned aerial vehicles (UAVs) are used more and more to measure forest properties like tree height and canopy openness. LiDAR is the most direct way to measure those properties, but this technology is rather expensive and therefore sparsely available.

Photogrammetry can be an alternative for measuring forest canopies. Since this can be done from relatively cheap platforms it is much more accessible than UAV-Lidar. However, the flight pattern strongly influences the quality of the reconstruction. Some research has been done to optimise those parameters, but the quality of the reconstructions is usually not compared to real geometric measurements, which are done with LiDAR.

In this thesis project we want to investigate the influence of different flight patterns on the photogrammetric reconstruction of forests and compare the quality of the reconstruction with UAV-LiDAR measurements.

As a result we hope to come up with optimized flight patterns for UAV photogrammetry for forest plots.

Relevance

  • Optimising flight patterns for forest inventories and evaluating the actual accuracy is for example relevant for the Nationale Bos Inventarisatie and related fields.

Objectives

  • Review literature on UAV photogrammetry for forestry applications, with focus on flight pattern optimisation
  • Collect UAV data over selected forest sites, with different flight patterns/configurations
  • Evaluate the quality of photogrammetric reconstruction of forest and compare this to UAV-LiDAR measurements

Requirements

  • Scripting skills (e.g. R, Python) are a preference
  • Completion GRS-32306 Advanced Earth Observation
  • For fieldwork it may be handy to have a Dutch drivers license

Theme(s): Sensing & measuring