Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2023
Authors
Stefano Puliti Grant Pearse Peter Surovy Luke Wallace Markus Hollaus Maciej Wielgosz Rasmus AstrupAbstract
The FOR-instance dataset (available at this https URL) addresses the challenge of accurate individual tree segmentation from laser scanning data, crucial for understanding forest ecosystems and sustainable management. Despite the growing need for detailed tree data, automating segmentation and tracking scientific progress remains difficult. Existing methodologies often overfit small datasets and lack comparability, limiting their applicability. Amid the progress triggered by the emergence of deep learning methodologies, standardized benchmarking assumes paramount importance in these research domains. This data paper introduces a benchmarking dataset for dense airborne laser scanning data, aimed at advancing instance and semantic segmentation techniques and promoting progress in 3D forest scene segmentation. The FOR-instance dataset comprises five curated and ML-ready UAV-based laser scanning data collections from diverse global locations, representing various forest types. The laser scanning data were manually annotated into individual trees (instances) and different semantic classes (e.g. stem, woody branches, live branches, terrain, low vegetation). The dataset is divided into development and test subsets, enabling method advancement and evaluation, with specific guidelines for utilization. It supports instance and semantic segmentation, offering adaptability to deep learning frameworks and diverse segmentation strategies, while the inclusion of diameter at breast height data expands its utility to the measurement of a classic tree variable. In conclusion, the FOR-instance dataset contributes to filling a gap in the 3D forest research, enhancing the development and benchmarking of segmentation algorithms for dense airborne laser scanning data.
Authors
Danielle M. Duni Matthew M. McIntosh Shelemia Nyamuryekung'e Andres F. Cibils Michael C. Duniway Richard Estell Sheri Spiegal Alfredo L. Gonzalez Melakeneh G. Gedefaw Matthew Redd Robert Paulin Caitriana M. Steele Santiago A. Utsumi Andres PereaAbstract
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Authors
Johannes BreidenbachAbstract
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In the context of BioCities, the circular bioeconomy has transformative potential in rethinking urban areas, especially using urban, peri-urban, and rural forestry as a nature-based solution. These can be seen as an interconnected forest network providing essential and high-value services, such as health benefits and climate resilience, and sustainable products, principally through rural and peri-urban forests.
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Authors
Tomáš Peterka Petra Hájková Martin Jiroušek Dirk Hinterlang Milan Chytrý Liene Aunina Judit Deme Melinda Lyons Hallie Seiler Harald Zechmeister Iva Apostolova Carl Beierkuhnlein Melanie Bischof Claudia Biţă-Nicolae Lisa Brancaleoni Renata Ćušterevska Jürgen Dengler Yakiv Didukh Daniel Dítě Lyubov Felbaba-Klushyna Emmanuel Garbolino Renato Gerdol Svitlana Iemelianova Florian Jansen Riikka Juutinen Jasmina Kamberović Jutta Kapfer Barbora Klímová Ilona Knollová Tiina H.M. Kolari Predrag Lazarević Ringa Luostarinen Eva Mikulášková Đorđije Milanović Luca Miserere Jesper Erenskjold Moeslund José A. Molina Aaron Pérez-Haase Alessandro Petraglia Marta Puglisi Eszter Ruprecht Eva Šmerdová Daniel Spitale Marcello Tomaselli Kiril Vassilev Michal HájekAbstract
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