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Forests are messy, models are wrong. Numerical models are amazing. They are clean, logical, and reassuringly mathematical. But as George Box reminds us, “all Models are wrong, but some are useful”. This is especially true for dynamic, ecological systems such as forests. Forest development is difficult to predict. When… Read More

The first edition of the SmartForest conference took place at the forestry department of the Technical University of Munich in Freising. The event featured two days of knowledge exchange and deep discussions between attendees from the worlds of research and practice, focusing on the future of forests… Read More

The subject of our first LabelledGreenData4All stakeholder workshop on June 13th 2024 was “Machine Learning Models and data Annotation and their Data Requirements within the Environmental Sector”. A total of 26 participants representing a variety of organisations from a wide range of backgrounds, such as science, researching, and… Read More

Note: You can find the original German press release for this project here. At present, the availability of high-quality annotated environmental data, usable to train Machine Learning (ML) algorithms is very limited. Within the project “LabelledGreenData4All”, the need as well as the potential of these high-quality data sets… Read More