Johannes Schumacher

Research Scientist at NIBIO

Johannes Schumacher has a diverse work experience in the field of forestry and research. Johannes started their career as a Co-Founder of recycle, where they specialized in the construction of bamboo bicycle frames and bicycle building, repairing, and selling. Johannes then worked as a Freelancer at Albert-Ludwigs-Universität Freiburg im Breisgau. Later, they joined FVA Forstliche Versuchs- und Forschungsanstalt Baden-Württemberg for project work.

In 2012, Johannes became a Visiting PhD Student at Texas A&M University, where they learned and used software such as eCognition and object-based analysis. During their time at the University of Copenhagen, they worked as a Research Assistant, creating countrywide tree type and biomass maps based on aerial lidar data and CIR images.

Johannes continued their research career as a PhD Fellow at the University of Copenhagen, where they worked with airborne lidar, high-resolution image, and ground data to perform tasks such as image segmentation, object-based analyses, classification, mapping, and statistics.

Johannes Schumacher then worked as a Guest Researcher at Wageningen UR (University & Research Centre). Johannes also served as a Consultant at UNIQUE forestry and land use GmbH. Johannes was responsible for providing expert advice in the field of forestry and land use.

From 2016 to 2019, Johannes worked as a Researcher at Forstliche Versuchs- und Forschungsanstalt Baden-Württemberg (FVA), conducting research in the forestry sector. Currently, they hold the position of Research Scientist at NIBIO Norwegian Institute of Bioeconomy Research, focusing on bioeconomic research.

Johannes Schumacher completed their Master's Degree in Forest Management/Forest Resources Management at The University of Freiburg from 2003 to 2009. Following this, they pursued a Doctor of Philosophy (PhD) at Københavns Universitet - University of Copenhagen from 2010 to 2014. Johannes'sdoctoral research focused on forest resource assessment using remote sensing data.

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