TUM Innovation Network - Earth Care

The goal of this project is to improve our projections on tree-species compositions of European forests under anticipated climate change. 

For this, tree-species parameterizations in the process-based ecosystem model LPJ-GUESS need to be validated against the observed drought-response of those species for well-known extreme events, e.g. the 2018 drought (Buras et al., 2020), since these events render a major constraint for plant metabolism. Here, precise ground-truthing data at large scale is needed to classify satellite-based drought-response as obtained by the European Forest Condition Monitor (Buras et al., 2021). Eventually, LPJ-GUESS simulations for various climate-change scenarios will be undertaken. 

To achieve these goals, the Ph.D. candidate will 
1) develop high-resolution (10 m pixel-size) AI-trained tree-species maps for key European tree species on the basis of Sentinel 2 images and forest inventory data (Welle et al., 2022),
 2) quantify species-specific responses to extreme droughts, 
3) parameterize hydraulic traits of key European tree species in LPJ-GUESS and validate those against remote-sensing based forest-drought response, and finally 4) simulate forest productivity and tree-species distributions for various climate change scenarios. 

Tasks 1) and 3) will be conducted in close collaboration with the group of Prof. Xiaoxiang Zhu and Prof. Yuanyuan Wang (both at TUM).