Preliminary thesis title: Estimation of forest plants densities thanks to presence/absence data
The aim of this doctoral project is to develop new methods and tools to estimate (non-tree) plant densities in forests, thanks to modelling with spatial point processes, generalized linear models and presence/absence data. Presence/absence sampling is indeed easier to perform and less prone to error than traditional data collecting methods such as vegetation cover assessment through ocular inspection. Different approaches will be studied, namely a model-based approach, a hybrid inference approach, cluster processes for plants that grow in clusters, and finally coupling between national inventory data and citizen science data (e.g. Artdatabanken). The data used will primarily come from national inventories that are part of SLU; the Swedish NFI and the NILS, but also from remote sensing