Thomas Nord-Larsen

Thomas Nord-Larsen

Senior Researcher

ORCID: 0000-0002-5341-6435

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  1. Published

    Danish National Forest Accounting Plan 2021-2030

    Johannsen, VK, Nord-Larsen, Thomas, Bentsen, Niclas Scott & Vesterdal, Lars, 2019, Institut for Geovidenskab og Naturforvaltning, Københavns Universitet. 79 p. (IGN Rapport).

    Research output: Book/Report › Report › Commissioned

  2. Published

    Danish National Forest Accounting Plan 2021-2030 - resubmission 2019

    Johannsen, VK, Nord-Larsen, Thomas, Bentsen, Niclas Scott & Vesterdal, Lars, 2019, 1 ed. Frederiksberg: Institut for Geovidenskab og Naturforvaltning, Københavns Universitet. 112 p. (IGN Rapport).

    Research output: Book/Report › Report › Commissioned

  3. Published

    Danish National Forest Inventory: Design and calculations

    Nord-Larsen, Thomas & Johannsen, VK, 2016, Department of Geosciences and Natural Resource Management, University of Copenhagen. 33 p. (IGN Report).

    Research output: Book/Report › Report › Research

  4. Published

    Debat: Som ren betonby når København aldrig byens klimamål

    Beck, S. A., Klaumann, J. R., Larsen, F., Thybring, Emil Engelund, Bentsen, Niclas Scott, Nord-Larsen, Thomas, Madsen, P., Johannsen, VK, Marsh, R., Koch, M., Søndergaard, J. & Vestergaard-Jensen, A., 4 Jan 2019, In: Altinget.dk. 1 p.

    Research output: Contribution to journal › Contribution to newspaper - Comment/debate › Communication

  5. Published

    Deciduous trees as lichen phorophytes: biodiversity and colonization patterns under common garden conditions

    Larsen, H. M. E., Hansen, Eric Steen, Nord-Larsen, Thomas & Rasmussen, Hanne Nina, 2020, In: Lichenologist. 52, 3, p. 221-232 11 p.

    Research output: Contribution to journal › Journal article › Research › peer-review

  6. Published

    Deep learning based 3D point cloud regression for estimating forest biomass

    Oehmcke, Stefan, Li, Lei, Caballer Revenga, Jaime, Nord-Larsen, Thomas, Trepekli, Aikaterini, Gieseke, F. & Igel, Christian, 1 Nov 2022, 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2022. Renz, M., Sarwat, M., Nascimento, M. A., Shekhar, S. & Xie, X. (eds.). Association for Computing Machinery, Inc., p. 1-4 38

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  7. Published

    Deep learning enables image-based tree counting, crown segmentation and height prediction at national scale

    Li, Sizhuo, Brandt, Martin Stefan, Fensholt, Rasmus, Kariryaa, Ankit, Igel, Christian, Gieseke, Fabian Cristian, Nord-Larsen, Thomas, Oehmcke, Stefan, Carlsen, Ask Holm, Junttila, S., Tong, Xiaoye, d’Aspremont, A. & Ciais, P., 2023, In: PNAS Nexus. 2, 4, 16 p., pgad076.

    Research output: Contribution to journal › Journal article › Research › peer-review

  8. Published

    Deep point cloud regression for above-ground forest biomass estimation from airborne LiDAR

    Oehmcke, Stefan, Li, Lei, Trepekli, Aikaterini, Caballer Revenga, Jaime, Nord-Larsen, Thomas, Gieseke, Fabian Cristian & Igel, Christian, 2024, In: Remote Sensing of Environment. 302, 21 p., 113968.

    Research output: Contribution to journal › Journal article › Research › peer-review

  9. Published

    Denmark

    Nord-Larsen, Thomas & Johannsen, VK, 2016, National Forest Inventories: Assessment of Wood Availability and Use. Vidal, C., A. Alberdi, I., Hernández Mateo, L. & J. Redmond, J. (eds.). 1 ed. Springer, p. 327-345 19 p.

    Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

  10. Published

    Denmark

    Bastrup-Birk, Annemarie, Nord-Larsen, Thomas, Johannsen, VK, Buttenschøn, Rita M. & Vesterdal, Lars, 2010, National forest inventories: pathways for common reporting. Tomppo, E., Gschwantner, T., Lawrence, M. & McRoberts, R. E. (eds.). Springer Science+Business Media, p. 157-169 13 p.

    Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

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