Student information
MSc thesis topic: Can we detect small temporal differences in spring/fall phenology with high spatial and temporal resolution remote sensing data?
Changing climate means that also trees have to adapt to new conditions. To study which tree from which location will be best adapted to future climate provenance trials have been set up. A provenance trial means that we planted trees (beeches) from all over Europe in a randomized block experiment. Trees from all over Europe are planted, and regularly measured.
One of the observed differences between the different provenances is the moment they start to grow leaves in spring, and shed leaves in fall. In the experimental plot at the Oostereng (close to Wageningen), 33 different Beech provenances were planted 25 years, in subplots of 10x10m. The small size of the experiment, combined with the short time period in which differences between the provenances can be observed asks for high spatial and temporal resolution remote sensing data.
In the spring of 2024 a number of UAV flights (RGB and multispectral) were done, which we plan to continue in fall. Further, Planet high resolution satellite data are available at a 3m spatial resolution and fairly high temporal interval.
In this thesis you will investigate if those data are suitable to capture the differences in leaf development in spring and fall for the different provenances.
Objectives and Research questions
- Investigate the possibilities of the different remote sensing data sources to capture variation in spring and fall phenology on a subplot level for the Oostereng Beech provenance trial.
Requirements
- Affinity with forest ecology
- Followed the Advanced Earth Observation course, since drone data processing will be part of the methodology
Literature and information
Theme(s): Sensing & measuring, Integrated Land Monitoring