Student information
MSc thesis topic: Assessing patterns of tropical forest disturbances [using the RADD alerts]
The RADD (RAdar for Detecting Deforestation) alerts offer insights into tropical forest disturbances. Leveraging data from Sentinel-1, a SAR satellite with 10m spatial detail, these alerts provide up-to-date information on tropical forest disturbances every 6 to 12 days across 50 countries since 2020/2021. The RADD alerts enable the exploration of spatial and temporal patterns in forest disturbances across the pan-tropical region.
The wealth of disturbance information that the RADD alerts provide has not been systematically characterized across the tropics before. Forest disturbance types exhibit a multitude of spatial and temporal characteristics. Human-induced disturbances, such as large-scale deforestation for agricultural purposes (e.g., plantations) or mining, alongside natural disturbances like fires, flooding, or windthrow events, showcase diverse patterns in space and time.
Accessing three years' worth of RADD forest disturbance alerts spanning the entire pan-tropical region allows us to characterize spatial and temporal pattens of disturbance events and potentially relate them to ancillary data, related for example to accessibility (road, settlements,…) or environmental factors (topography,…). Questions that will be tackled are: are disturbance patterns across the tropics distinctly different in terms of size, shape, and temporal evolution ? or how do these characteristics relate to management and conservation practices, economic characteristics, drivers and other relevant ancillary data?
Software: Google Earth Engine, R/python, ArcGIS/QGIS
Objectives and Research questions
- Analysing spatial and temporal patterns of disturbances in tropical forests
- Evaluating interrelations among disturbances and their impacts
- Characterize disturbances in relation to spatial ancillary data
Requirements
- Geo-scripting course
- Advanced Earth Observation
Literature and information
- https://radd-alert.wur.nl
- Reiche, J., Mullissa, A., Slagter, B., Gou, Y., Tsendbazar, N.-E., Odongo-Braun, C., Vollrath, A., Weisse, M.J., Stolle, F., Pickens, A., Donchyts, G., Clinton, N., Gorelick, N., Herold, M., 2021. Forest disturbance alerts for the Congo Basin using Sentinel-1. Environmental Research Letters 16, 024005. https://doi.org/10.1088/1748-9326/abd0a8
Expected reading list before starting the thesis research
- Bart Slagter, Johannes Reiche, Diego Marcos, Adugna Mullissa, Etse Lossou, Marielos Peña-Claros, Martin Herold, Monitoring direct drivers of small-scale tropical forest disturbance in near real-time with Sentinel-1 and -2 data, Remote Sensing of Environment, Volume 295, 2023.
- Sommerfeld, A., Senf, C., Buma, B. et al. Patterns and drivers of recent disturbances across the temperate forest biome. Nat Commun 9, 4355 (2018).
- Gou, Y., Balling, J., Sy, V. D., Herold, M., Keersmaecker, W. D., Slagter, B., Mullissa, A., Shang, X., & Reiche, J. (2022). Intra-annual relationship between precipitation and forest disturbance in the African rainforest. Environmental Research Letters, 17(4), 044044.
- https://earthobservatory.nasa.gov/images/145888/making-sense-of-amazon-deforestation-patterns
- Information on types of tropical forest disturbances.
Theme(s): Sensing & measuring; Integrated Land Monitoring