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Nicolas Cattaneo

Research Scientist

NIBIO Publications
NIBIO Projects

Division of Forest and Forest Resources

Forest Operations and Digitalization

(+47) 412 20 885
nicolas.cattaneo@nibio.no

Place
Ås H8

Visiting address
Høgskoleveien 8, 1433 Ås

My NIBIO publications

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Academic article – A high-resolution, country-wide scenario analysis of forest susceptibility to spruce bark beetle damage in Norway

Nicolas Cattaneo, Paal Krokene, Rasmus Astrup

BioRxiv, 2025

Cattaneo, N., Krokene, P. & Astrup, R. 2025. A high-resolution, country-wide scenario analysis of forest susceptibility to spruce bark beetle damage in Norway (Academic article). Available at: https://doi.org/10.1101/2025.05.06.652523.
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Authors

Nicolas Cattaneo Paal Krokene Rasmus Astrup

Abstract

No abstract has been registered

Academic article – The potential impacts of climate and forest changes on streamflow for micro-, meso- and macro-scale catchments in Norway

Shaochun Huang, Stephanie Eisner, Wai Kwok Wong, ...

Journal of Hydrology Regional Studies, 2025

Huang, S., Eisner, S., Wong, W.K. & Cattaneo, N. 2025. The potential impacts of climate and forest changes on streamflow for micro-, meso- and macro-scale catchments in Norway (Academic article). Available at: https://doi.org/10.1016/j.ejrh.2024.102147.
To document

Authors

Shaochun Huang Stephanie Eisner Wai Kwok Wong Nicolas Cattaneo

Abstract

No abstract has been registered

Academic article – Estimating wood quality attributes from dense airborne LiDAR point clouds

Nicolas Cattaneo, Stefano Puliti, Carolin Fischer, ...

Forest Ecosystems, 2024

Cattaneo, N., Puliti, S., Fischer, C. & Astrup, R. 2024. Estimating wood quality attributes from dense airborne LiDAR point clouds (Academic article). Available at: https://hdl.handle.net/11250/3187114.
To document

Authors

Nicolas Cattaneo Stefano Puliti Carolin Fischer Rasmus Astrup

Abstract

No abstract has been registered

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NIBIO Projects

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Forest illustration

Division of Forest and Forest Resources

A Decision Support System for emerging forest management alternatives


This project aims to develop advanced tree growth models using LiDAR-derived, high-density point cloud data to improve the simulation of forest dynamics under close-to-nature silvicultural practices. By modeling tree-level growth in structurally complex and heterogeneous stands, these models will support more accurate, spatially explicit forest simulations and inform sustainable and diversified forest management decisions.

Active Updated: 09.05.2025
End: jan 2027
Start: jan 2025
3D_gjengivelse av skog_Foto Stefano Puliti NIBIO

Division of Forest and Forest Resources

SFI SmartForest: Bringing Industry 4.0 to the Norwegian forest sector


SmartForest will position the Norwegian forest sector at the forefront of digitalization resulting in large efficiency gains in the forest sector, increased production, reduced environmental impacts, and significant climate benefits. SmartForest will result in a series of innovations and be the catalyst for an internationally competitive forest-tech sector in Norway. The fundamental components for achieving this are in place; a unified and committed forest sector, a leading R&D environment, and a series of progressive data and technology companies. 

Active Updated: 29.07.2025
End: sep 2028
Start: oct 2020
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