Thesis subject
MSc thesis topic: Isolating and estimating volume of agroforestry systems in the Flevopolder
Point clouds of forests acquired with Terrestrial Laser Scanning (TLS) contain a wealth of information on tree structural properties. However, segmenting individual trees from the point clouds is time intense especially with complex structure of the hedges
Within the XX group, it is interested to know the volume of hedges surrounding arable land, for that, we have an experimental field in XXX. In this area there are hedges planted since 2021/2022.
The hedges are composed from four different species (poplar, willow, alder and elm) and planted in a repeated pattern: poplar, elm, elm, willow, alder, alder.
There are a total of six of these hedges, each planted within 50/100m between each of them. In between, there is arable field.
Hedges are 2.50x1x6m (lxwxh).
Relevance to research/projects at GRS or other groups
- Review literature on state-of-the-art tree segmentation algorithms
- One/two days LiDAR fieldwork scanning the hedge in the flevopolder during off-leaf season (october)
- Co-registration (pre-processing) of TLS scan projects to form whole plot point clouds
- Application of (different) segmentation algorithm(s) to estimate volume of different trees
- Evaluation of volume estimation results based on reference measurements
Requirements
- Scripting skills (e.g. R, Python, MatLab) are a preference
- Basic knowledge of Cloudcompare software
- Completion GRS-32306 Advanced Earth Observation
Literature and information
Expected reading list before starting the thesis research
- Raumonen, P., Casella, E., Calders, K., Murphy, S., Åkerblom, M., Kaasalainen, M., … Kaasalainen, M. (2015). MASSIVE-SCALE TREE MODELLING FROM TLS DATA. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, II-3/W4(March), 189–196. doi:10.5194/isprsannals-II-3-W4-189-2015
Theme(s): Modelling & visualisation