Student information

MSc thesis topic: Model-based accuracy assessment of mapped global forest biomass (changes)

Knowledge about global forest biomass is very important within the context of climatic change processes, mitigating actions and (financial) compensation for those actions. Currently, there are several global and regional forest biomass products available and new products are being produced. The accuracy of existing products varies and the accuracy of new products needs to be assessed. Unfortunately, plot data that can be used for accuracy assessments are unevenly spread over the globe. Furthermore the plot data themselves are not error free. To deal with these issues, a geostatistical validation protocol has been developed within the CCI Biomass project

The aim of this thesis research is to test and elaborate the validation protocol on a region of choice. A second possibility is to assess uncertainty propagation in the assessment of biomass trends.

Objectives (choose from)

  • Model uncertainty in forest biomass plot data
  • Assess and model systematic deviations in mapped biomass
  • Model uncertainty in mapped biomass, accounting for uncertainty in plot data •Assess uncertainty in mapped biomass trends
  • Assess whether and how biomass maps can be used to reduce forest inventory efforts
  • To be discussed ...

Literature

  • Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., . . . Townshend, J. R. G. (2013). High-Resolution Global Maps of 21st-Century Forest Cover Change. Science, 342(6160), 850-853. doi:10.1126/science.1244693
  • McRoberts, R. E. (2014). Post-classification approaches to estimating change in forest area using remotely sensed auxiliary data. Remote Sensing of Environment, 151, 149-156. doi:10.1016/j.rse.2013.03.036
  • Olofsson, P., Foody, G. M., Herold, M., Stehman, S. V., Woodcock, C. E., & Wulder, M. A. (2014). Good practices for estimating area and assessing accuracy of land change. Remote Sensing of Environment, 148, 42-57. doi:10.1016/j.rse.2014.02.015
  • Réjou-Méchain, M., Tanguy, A., Piponiot, C., Chave, J., & Hérault, B. (2017). biomass: an r package for estimating above-ground biomass and its uncertainty in tropical forests. Methods in Ecology and Evolution, 8(9), 1163-1167. doi:doi:10.1111/2041-210X.12753
  • Rozendaal, D. M. A., Santoro, M., Schepaschenko, D., Avitabile, V., & Herold, M. (2017). DUE GlobBiomass D17 Validation Report.

Requirements

  • Strong analytical skills (including statistical analysis)
  • Scripting skills

Theme(s): Modelling & visualisation, Integrated Land Monitoring