MSc thesis subject: Assessing the forest structure along a tropical forest to savanna transect in Ghana, using UAV based structure for motion techniques

Constant monitoring of tropical forests is important to increase our knowledge on effects of climate change. However, mapping aspects like forest structure, degradation and deforestation is time-consuming and expensive. Innovative high-tech approaches like Terrestrial Lidar Scanning (TLS) and Hyperspectral Sensing from Unmanned Aerial Vehicles (UAV) may revolutionize the way we monitor our forests.

The Wageningen UR - Unmanned Aerial Remote Sensing Facility (UARSF) was involved in a Ghana campaign to investigate the use of innovative technologies for mapping the plant traits of tropical forest. In this approach, UAV based sensing is allowing for multi-scale observations and filling the gap between ground based sampling and satellite based observations. With a DJI Phantom 3 we observed the forest structural information, which can be derived from the 3D point cloud data. This was done along a transect from the tropical forest in the south of Ghana to the Savanna forest in the centre of the country.
However, the different forest types do influence the quality of the derived model of the top of the canopy. Therefore, it first has to be assessed how well the structure for motion (sfm) technology works in these different biomes. If the processing can be improved to a level where reliable models of the top of canopy can be derived, more ecological questions may be answered.


  • Create 3D surface models of the top of the canopy using UAV RGB images
  • Evaluate the performance of these models over a range of biomes
  • Derive ecological parameters of the derived 3D surface models

Theme(s): Sensing & measuring