Research
My doctoral project is a part of the project Framtidens skogsskötsel i södra Sverige (a.k.a. Future silviculture in southern Sweden, FRAS) and is called Efficient stand treatment. The premise for my project is to evaluate how/if silviculture can be improved by specifying the management within forest stands to sub-stands.
The topic interests me since it connects research areas ranging from ecophysiology and silviculture to forest remote sensing. The forest companies are currently in a digitalization process, in which forest remote sensing data, harvester data and other geographical data is implemented in the operational, tactical and strategical levels in decision-making. The rapid technological development opens up for new research questions dealing with how, and if, we can better reach the goals and objectives in forest management when high resolution data is available.
Publications
Article in journal (Refereed)
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Persson, M., Trubins, R., Eriksson, L.O., Bergh, J., Sonesson, J., et al. (2022). Precision thinning : a comparison of optimal stand-level and pixel-level thinning. Scandinavian Journal of Forest Research. 37 (2). 99-108.
Status: Published -
Persson, M., Lindberg, E., Reese, H. (2018). Tree Species Classification with Multi-Temporal Sentinel-2 Data. Remote Sensing. 10 (11).
Status: Published
Doctoral thesis, comprehensive summary (Other academic)
- Persson, M. (2022). Evaluating thinning practices and assessment methods for improved management in coniferous production forests in southern Sweden. Doctoral Thesis. Växjö, Linnaeus University Press. 59.