Student information
MSc thesis topic: Integrate satellite-based forest disturbance products with multi-element analysis and for improved timber tracing
Illegal timber trade is a huge environmental problem, and is often associated with organized crime and deforestation. Legislation to fight illegal timber trade exist, but their enforcement required independent ways to verify timber origin. A method to do so is multi-element analyses, in which a chemical fingerprint of wood is obtained based on measuring concentrations of 40-60 elements in wood (Boeschoten et al 2022). Applying this to 22 sites in Central Africa, this method has proven to be able to trace back the origin of timber to regional clusters with accuracy of >85%. Yet, for forensic applications, this accuracy need to be improved.
Forest disturbance alert products such as the RADD (RAdar for Detecting Deforestation) alerts offer spatial and temporally detailed information on where and when forest logging takes place. Leveraging data from Sentinel-1, a SAR satellite with 10m spatial detail, the RADD alerts provide up-to-date information on tropical forest disturbances every 6 to 12 days across 50 countries since 2020/2021.
This thesis will combine results from multi-element analysis with spatially and temporally detailed forest disturbance information from the RADD alert (and other remote sensing products) to enhance the ability to assign the origin of timber. Spatial modeling will be employed to integrate the various data sources across the Congo Basin. Results will be compared against a benchmark scenario that uses only multi-element analysis.
Software: [Google Earth Engine], R/python, ArcGIS/QGIS
Objectives and Research questions
- Integrate forest disturbance alert products with multi-element analysis (results) using spatial modelling
- Asses the accuracy gain against results using only multi-element analysis.
Requirements
- Geo-scripting course
- Advanced Earth Observation
Literature and information
- https://radd-alert.wur.nl
- Reiche, J. et al. 2021. Forest disturbance alerts for the Congo Basin using Sentinel-1, Environ. Res. Lett., 16, 024005. https://doi.org/10.1088/1748-9326/abd0a8
- Boeschoten et al 2022. Clay and soil organic matter drive wood multi-elemental composition of a tropical tree species: Implications for timber tracing, Science of The Total Environment, Volume 849, 157877, https://www.sciencedirect.com/science/article/pii/S0048969722049762?via%3Dihub
- Boeschoten et al 2023. A new method for the timber tracing toolbox: applying multi-element analysis to determine wood origin, Environ. Res. Lett., 18, 054001. https://iopscience.iop.org/article/10.1088/1748-9326/acc81b
- Link to project site: www.timtrace.nl
Theme(s): Modelling & visualisation; Integrated Land Monitoring