MSc thesis topic: Tropical forests disturbances and regrowth monitoring using remote sensing time series data
Tropical forests are hotspots of global biodiversity and store a large amount of carbon thus play an essential role in mitigating climate change (Griffiths et al., 2018). Forest disturbances and regrowth have been considered as essential ecological process that is not well understood or quantified (Zhao et al., 2018). On one hand, disturbances events (caused by harvest, fire, insect, wind) emit carbon in the atmosphere.
On the other hand, vegetation regrowth after disturbances absorbs carbon. Thus, the process of disturbance and regrowth introduces considerable uncertainties in quantifying forest carbon budget at a regional or global scale. To address these uncertainties, spatiotemporally characterizing disturbances and regrowth in tropical forests are of great importance for better understanding the extent and status of the tropical forests thus assist in developing strategies for sustainable management of forests resources and adaption for climate change.
- To identify the location and time of the forest disturbance and regrowth
- To assess the accuracy of detected forests disturbances and regrowth
- Griffiths, P., Jakimow, B., & Hostert, P. (2018). Reconstructing long term annual deforestation dynamics in Pará and Mato Grosso using the Landsat archive. Remote Sensing of Environment, 216(October 2017), 497–513.
- Zhao, F., Huang, C., Goward, S. N., Schleeweis, K., Rishmawi, K., Lindsey, M. A., … Michaelis, A. (2018). Development of Landsat-based annual US forest disturbance history maps (1986–2010) in support of the North American Carbon Program (NACP). Remote Sensing of Environment, 209(February), 312–326.
- Geo-scripting course
- Advanced programming skills (e.g. R, Python, GEE) or strong motivation to learn it.
Theme(s): Modelling & visualisation; Integrated Land Monitoring