Recent Publications

  1. Networking the forest infrastructure towards near real-time monitoring – A white paper
    Roman Zweifel et al.
    Science of the Total Environment, 872 162167 (2023).
  2. Reconstructing radial stem size changes of trees with machine learning
    Mirko Luković, Roman Zweifel, Guillaume Thiry, Ce Zhang and Mark Schubert
    Journal of the Royal Society Interface, 19, 20220349 (2022).
  3. Semi-supervised learning for quality control of high-value wood products
    M. Schubert, Walter Sonderegger, Mirko Luković and Oliver Kläusler
    Wood Science and Technology, DOI (2022).
  4. Sustainable-Macromolecule-Assisted Preparation of Cross-linked, Ultralight, Flexible Graphene Aerogel Sensors toward Low-Frequency Strain/Pressure to High-Frequency Vibration Sensing
    Zhihui Zeng, Na Wu, Weidong Yang, Hao Xu, Yaozhong Liao, Chenwei Li, Mirko Luković, Yunfei Yang, Shanyu Zhao, Zhongqing Su and Xuehong Lu
    Small, 18, 2202047 (2022).
  5. Nanocellulose Assisted Preparation of Ambient Dried, Large-Scale and Mechanically Robust Carbon Nanotube Foams for Electromagnetic Interference Shielding
    Zhihui Zeng, Changxian Wang, Tingting Wu, Daxin Han, Mirko Luković, Fei Pan, Gilberto Siqueira and Gustav Nyström
    Journal of Materials Chemistry A, 8, 17969 (2020).
  6. Geometry-induced nonequilibrium phase transition in sandpiles
    M. N. Najafi, J. Cheraghalizadeh, M. Luković and H. J. Herrmann
    Physical Review E 101, 032116 [arxiv] (2020).
  7. Prediction of mechanical properties of wood fiber insulation boards as a function of machine and process parameters by random forest
    M. Schubert, M. Luković and H. Christen
    Wood Science and Technology 54, 703 (2020).
  8. Hierarchical Porous Wood Cellulose Scaffold with Atomically Dispersed Pt Catalysts for Low-Temperature Ethylene Decomposition
    H. Guo, P. Warnicke, M. Griffa, U. Müller, Z. Chen, R. Schaeublin, Z. Zhang and M. Luković
    ACS Nano 13 (12) 14337 (2019).
  9. Bioinspired Struvite Mineralization for Fire-Resistant Wood
    H. Guo, M. Luković, M. Mendoza, C.M. Schlepütz, M. Griffa, B. Xu, S. Gaan, H. J. Herrmann and I. Burgert
    ACS Applied Materials & Interfaces 11 5427 (2019).

Projekte

Development of an AI-based software module for automated cleaning and gap-filling of TreeNet data.

FORWARDS aims to develop, test, and implement a European Observatory that will supply timely and detailed information on European forests' vulnerability to climate change impacts, and provide knowledge to guide climate smart forestry

TreeNet ist ein internationales Beobachtungs- und Forschungsnetzwerk, in dem Punktdendrometer automatisch die täglichen Stammradiusschwankungen von Bäumen erfassen. Der kontinuierliche Fluss von Daten liefert Echtzeitinformationen über die Wasserverhältnisse im Baum und das radial Stammwachstum

deepT investigates times series of stem radius changes with deep neural network (DNN) algorithms in order to recognize tree species, growth patterns and tree water deficit-induced stem shrinkage characteristics.

Nowcast and predict forest condition from TreeNet data with the help of machine learning.

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