Thesis subject

MSc Thesis topic: Spatially-explicit drivers of forest recovery in the Brazilian amazon in the last 3 decades

Understanding the dynamics of forest cover, which steeply decreased between 1985 and 2018 throughout Brazil, is essential for estimating the global carbon balance and quantifying the provision of ecosystem services. A 30-m spatial resolution dataset of the annual increment, extent, and age of secondary forests for Brazil over the 1986–2018 period was developed (Junior at el, 2020). For this dataset, land-use and land-cover maps from MapBiomas Project (Collection 4.1) were used as input data for the algorithm, implemented in the Google Earth Engine platform. This dataset provides critical spatially explicit information for supporting carbon emissions reduction, biodiversity, and restoration policies, enabling environmental science applications, territorial planning, and subsidizing environmental law enforcement.

The above mentioned unique dataset on the age of secondary forests provides an opportunity to assess the drivers behind the recovery of secondary forests. Open-source regional and global data representing anthropogenic and environmental drivers (e.g. climate, distance to roads, etc) can be used to investigate this in a spatially and temporally detailed way.


  • Assess spatially-explicit human and environmental drivers of forest recovery in the Brazilian Amazon


  • Junior, C.H.S., Heinrich, V.H., Freire, A.T., Broggio, I.S., Rosan, T.M., Doblas, J., Anderson, L.O., Rousseau, G.X., Shimabukuro, Y.E., Silva, C.A. and House, J.I., 2020. Benchmark maps of 33 years of secondary forest age for Brazil. Scientific data, 7(1), pp.1-9.
  • Suarez, D.R., Rozendaal, D.M., De Sy, V., Gibbs, D.A., Harris, N.L., Sexton, J.O., Feng, M., Channan, S., Zahabu, E., Pekkarinen, A. and Martius, C., 2021. Variation in aboveground biomass in forests and woodlands in Tanzania along gradients in environmental conditions and human use. Environmental Research Letters, 16(4), p.044014.


  • Willingness to work in R is appreciated but not mandatory

Theme(s): Integrated Land Monitoring