Stephan Hoffmann
Forsker
Biografi
My educational background encompasses International Forestry, with a B.Sc. from HNE Eberswalde and a M.Sc. from the University of Freiburg. Afterwards, my professional journey commenced in the forestry industry of Ghana, where I developed a growing passion for forest operations. This experience paved the way for me to engage in diverse applied projects worldwide, collaborating with various institutions in a range of climate zones. This journey also fueled my ambition to pursue a Ph.D. in the field of forest operations.
Consequently, I've evolved into a versatile forest operations expert, with a particular focus on steep terrain harvesting, forest road management, and the practical application of forest science.
Sammendrag
Collection, processing and provision of comprehensive geometric information of forest roads is decisive for its technical classification to facilitate sustainable timber supply chains. An automized classification system based on the mobile proximal sensor platform RoadSens was developed, applied and validated through a case study approach in Eastern Norway. Six sample roads of various vegetation stages were surveyed through RoadSens and complemented through sampled total station measurements for validation purposes. The determined geometric parameters road slope, curvature and width were used for technical classification following the national forest road standard. Road width was identified as the main constraint in meeting the standard, resulting in a general downgrading of the sampled roads according to its technical class. The results showed a root mean square error (RMSE) ranging from ±0.53 to 1.50 m (12–33%) depending on the road and vegetation stage compared to the validation data. Despite these accuracy constraints, the application case study already indicates a general need for improvement of road data acquisition and updating of associated databases. The study underscores that, despite the challenges and limitations, there is a clear need for an automated sensing and classification system, which offers a cost-effective alternative to manual surveying and requires less specialized expertise.
Sammendrag
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Forfattere
Heikki Korpunen Yrjö Nuutinen Paula Jylhä Lars Eliasson Aksel Granhus Juha Laitila Stephan Hoffmann Timo MuhonenSammendrag
• Overall forest management objectives and stand properties set the requirements and possibilities for harvesting in continuous cover forestry (CCF). • Harvester and forwarder operators play a key role in successful CCF harvesting, as both productivity and quality of work are essential factors in harvesting operations. • Optimal stand conditions improve work productivity on selection harvesting sites; harvested stem volume correlates well with work productivity in cutting, and density of remaining trees does not significantly reduce work productivity in forwarding. • Carefully executed group cutting and shelterwood harvesting can reduce the number of damaged remaining trees, which is beneficial for future tree generations. • Research-based information is needed about work productivity in harvesting, damage caused by harvesting, and optimisation of strip road and forest road networks for CCF.
