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Project properties |
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| Title | Integrate satellite-based forest disturbance products with multi-element analysis and for improved timber tracing |
| Group | Forest Ecology and Forest Management Group |
| Project type | thesis |
| Credits | 36 |
| Supervisor(s) | prof.dr. PA (Pieter) Zuidema
dr. J. Reiche (GRS) |
| Examiner(s) | dr. JP (Peter) van der Sleen |
| Contact info | Pieter.Zuidema@wur.nl |
| Begin date | 2024/05/01 |
| End date | |
| Description | 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% (Boeschoten et al 2023). 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 References: • https://radd-alert.wur.nl • Reiche, J. et al. 2021. https://doi.org/10.1088/1748-9326/abd0a8 • Boeschoten et al 2022. https://www.sciencedirect.com/science/article/pii/S0048969722049762?via%3Dihub • Boeschoten et al 2023. https://iopscience.iop.org/article/10.1088/1748-9326/acc81b • Link to project site: www.timtrace.nl Keywords to search by: Topic(s): Forest management Region(s): Africa Climate(s): Tropical zone |
| Used skills | Proficiency in using R |
| Requirements | Standard for MSc thesis:
- WEC-31806 Ecological Methods I, or a comparable alternative course; - One FEM course (at least), depending on the topic of the thesis: FEM-30306 Forest Ecology and Forest Management, FEM-30806 Resource Dynamics Sustainable Utilization, FEM-32306 Agroforestry, or Models for Ecological Systems FEM-31806 If different: Recommended courses: • Geo-scripting course • Advanced Earth Observation Standard for BSc thesis minimal 120 credits |