Oscar Andersson

While forestry increasingly relies on digital data, important features and structures within forest landscapes remain difficult to detect, interpret, and represent in existing decision-support systems.

To address that, my research explore how data-driven methods such as remote sensing and artificial intelligence can be combined with ecological- and archeological understanding to improve the detection and interpretation of forest landscape information. 

As an industrial PhD student within the WIFORCE Research School, my research is conducted at the interface between academia and industry, with a strong emphasis on applied relevance. The long-term goal is to contribute to more reliable forest inventories, improved planning, and better-informed decisions in digitally supported forestry by bridging science with industrial need.

Awarded Arvid Lindman's reward fund for meritorious completion of his thesis.

I hold a Master’s degree in Forest Science from the Swedish University of Agricultural Sciences (SLU). My MSc thesis in Forest Ecology and Sustainable Management was supervised by Clydecia Spitzer and Michael Gundale and examined how warming alters root trait strategies and enhances overyielding in boreal tree seedling mixtures.

I am currently a first-year industrial PhD student within the WIFORCE Research School, affiliated with SLU and industry. My doctoral work builds on my background in forest ecology while shifting focus towards data-driven and soil science approaches for improving forest information and planning in a digital forestry context.

WIFORCE

Swedish University of Agricultural Sciences, Department of Forest Ecology & Management

Main supervisors PhD: Lars Östlund, William Lidberg

MSc Thesis supervisors: Clydecia Spitzer, Michael Gundale