RA
Rasmus Astrup
cs.CVstat.APForestsecologyClimate ChangeForestryTreesAdaptation, Physiologicalafforestationautomatic detection and classification
On Valency
published · living versionsW_xbcpb9k9·v1 · currentpublished
3Dtrees.earth: community research infrastructure for tree and forest analysis using close-range LiDAR data
with Janusch Vajna-Jehle, Kilian Gerberding, Daniel Lusk, Teja Kattenborn +273
1 version
Preprints & journals
34 papers in the corpus · 2014–2026Contemporary high resolution European forest structure assessed using tree-level National Forest Inventory data.42247354 · Nabuurs, Gert-Jan, Maximo, Yasmin I, Starcevic, Ajdin et al.2026 · 1 citationPloS one. 2026;21(6):e0346611
Factors influencing birch (Betula spp.) age distribution in Norway: Insights from tree ring data10.1101/2025.06.10.658859v1 · Vergarechea, M., Anton Fernandez, C., Jepsen, J. et al.2025 · 0 citationsbioRxiv
A high-resolution, country-wide scenario analysis of forest susceptibility to spruce bark beetle damage in Norway10.1101/2025.05.06.652523v1 · Cattaneo, N., Krokene, P., Astrup, R.2025 · 0 citationsbioRxiv
Pan-European forest maps produced with a combination of earth observation data and national forest inventory plots.40486231 · Miettinen, Jukka, Breidenbach, Johannes, Adame, Patricia et al.2026 · 9 citationsData in brief. 2025;60:111613
Improved forest management for increased carbon sequestration: An assessment of the most prominent approaches in Norway.39935061 · Sevillano, Ignacio, Antón-Fernández, Clara, Søgaard, Gunnhild et al.2025 · 12 citationsJournal of environmental management. 2025;375:124333
deadtrees.earth - An Open-Access and Interactive Database for Centimeter-Scale Aerial Imagery to Uncover Global Tree Mortality Dynamics10.1101/2024.10.18.619094v2 · Mosig, C., Vajna-Jehle, J., Mahecha, M. D. et al.2024 · 27 citationsbioRxiv
BranchPoseNet: Characterizing tree branching with a deep learning-based pose estimation approach2409.14755v1 · Stefano Puliti, Carolin Fischer, Rasmus Astrup2024 · 1 citationarXiv
Benchmarking tree species classification from proximally-sensed laser scanning data: introducing the FOR-species20K dataset2408.06507v1 · Stefano Puliti, Emily R. Lines, Jana Mullerov'a et al.2024 · 53 citationsarXiv
Access to exact National Forest Inventory plot locations must be carefully evaluated.38359875 · Schadauer, Klemens, Astrup, Rasmus, Breidenbach, Johannes et al.2024 · 11 citationsThe New phytologist. 2024;242(2):347-350
SegmentAnyTree: A sensor and platform agnostic deep learning model for tree segmentation using laser scanning data2401.15739v1 · Maciej Wielgosz, Stefano Puliti, Binbin Xiang et al.2024 · 126 citationsRemote Sensing of Environment, Volume 313, 2024, 114367, ISSN 0034-4257
Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning2312.15084v2 · Binbin Xiang, Maciej Wielgosz, Theodora Kontogianni et al.2023 · 149 citationsarXiv
Multi-Sensor Terrestrial SLAM for Real-Time, Large-Scale, and GNSS-Interrupted Forest Mapping2310.01064v1 · Weria Khaksar, Rasmus Astrup2023 · 1 citationarXiv
FOR-instance: a UAV laser scanning benchmark dataset for semantic and instance segmentation of individual trees2309.01279v1 · Stefano Puliti, Grant Pearse, Peter Surov'y et al.2023 · 31 citationsarXiv
Understanding Europe’s forest harvesting regimesx5910j · Susanne Suvanto, Adriane Esquivel Muelbert, Mart-Jan Schelhaas et al.2023 · 34 citationsEarthArXiv
Towards accurate instance segmentation in large-scale LiDAR point clouds2307.02877v1 · Binbin Xiang, Torben Peters, Theodora Kontogianni et al.2023 · 22 citationsarXiv
Point2Tree(P2T) -- framework for parameter tuning of semantic and instance segmentation used with mobile laser scanning data in coniferous forest2305.02651v1 · Maciej Wielgosz, Stefano Puliti, Phil Wilkes et al.2023 · 39 citationsarXiv
Assessing and mitigating systematic errors in forest attribute maps utilizing harvester and airborne laser scanning data2203.04679v2 · Janne Raty, Marius Hauglin, Rasmus Astrup et al.2022 · 8 citationsarXiv
Climate change mitigation potential of biochar from forestry residues under boreal condition.34673068 · Hagenbo, Andreas, Antón-Fernández, Clara, Bright, Ryan M et al.2021 · 30 citationsThe Science of the total environment. 2022;807(Pt 3):151044
Prediction of butt rot volume in Norway spruce forest stands using harvester, remotely sensed and environmental data2107.04316v1 · Janne Raty, Johannes Breidenbach, Marius Hauglin et al.2021 · 11 citationsInternational Journal of Applied Earth Observation and Geoinformation, 2021
Improving living biomass C-stock loss estimates by combining optical satellite, airborne laser scanning, and NFI data2012.07921v2 · Johannes Breidenbach, Janis Ivanovs, Annika Kangas et al.2020 · 15 citationsarXiv
Timber Volume Estimation Based on Airborne Laser Scanning -- Comparing the Use of National Forest Inventory and Forest Management Inventory Data2011.02051v3 · Johannes Rahlf, Marius Hauglin, Rasmus Astrup et al.2020 · 25 citationsarXiv
Prediction and model-assisted estimation of diameter distributions using Norwegian national forest inventory and airborne laser scanning data2010.07107v2 · Janne Raty, Rasmus Astrup, Johannes Breidenbach2020 · 9 citationsarXiv
Evaluating the terrestrial carbon dioxide removal potential of improved forest management and accelerated forest conversion in Norway.32559355 · Bright, Ryan M, Allen, Micky, Antón-Fernández, Clara et al.2021 · 17 citationsGlobal change biology. 2020;26(9):5087-5105
Mapping forest age using National Forest Inventory, airborne laser scanning, and Sentinel-2 data2004.13427v1 · Johannes Schumacher, Marius Hauglin, Rasmus Astrup et al.2020 · 57 citationsarXiv
National mapping and estimation of forest area by dominant tree species using Sentinel-2 data2004.07503v1 · Johannes Breidenbach, Lars T. Waser, Misganu Debella-Gilo et al.2020 · 81 citationsarXiv
A century of National Forest Inventory in Norway - informing past, present, and future decisions.32834905 · Breidenbach, Johannes, Granhus, Aksel, Hylen, Gro et al.2023 · 121 citationsForest ecosystems. 2020;7(1):46
Detection and classification of Root and Butt-Rot (RBR) in Stumps of Norway Spruce Using RGB Images and Machine Learning.30939827 · Ostovar, Ahmad, Talbot, Bruce, Puliti, Stefano et al.2019 · 17 citationsSensors (Basel, Switzerland). 2019;19(7)
Cooling aerosols and changes in albedo counteract warming from CO2 and black carbon from forest bioenergy in Norway.29459753 · Arvesen, Anders, Cherubini, Francesco, Del Alamo Serrano, Gonzalo et al.2024 · 22 citationsScientific reports. 2018;8(1):3299
Carbon-equivalent metrics for albedo changes in land management contexts: relevance of the time dimension.27755703 · Bright, Ryan M, Bogren, Wiley, Bernier, Pierre et al.2017 · 51 citationsEcological applications : a publication of the Ecological Society of America. 2016;26(6):1868-1880
Modeling Soil Carbon Dynamics in Northern Forests: Effects of Spatial and Temporal Aggregation of Climatic Input Data.26901763 · Dalsgaard, Lise, Astrup, Rasmus, Antón-Fernández, Clara et al.2016 · 12 citationsPloS one. 2016;11(2):e0149902
The crushing weight of urban waste.26912849 · Yang, Hong, Huang, Xianjin, Thompson, Julian R et al.2016 · 40 citationsScience (New York, N.Y.). 2016;351(6274):674
Empirical coverage of model-based variance estimators for remote sensing assisted estimation of stand-level timber volume.28148972 · Breidenbach, Johannes, McRoberts, Ronald E, Astrup, Rasmus2020 · 74 citationsRemote sensing of environment. 2016;173:274-281
Sapling leaf trait responses to light, tree height and soil nutrients for three conifer species of contrasting shade tolerance.25422385 · Lilles, Erica B, Astrup, Rasmus, Lefrançois, Marie-Lou et al.2015 · 16 citationsTree physiology. 2014;34(12):1334-47
Climate change implications of shifting forest management strategy in a boreal forest ecosystem of Norway.24277242 · Bright, Ryan M, Antón-Fernández, Clara, Astrup, Rasmus et al.2014 · 66 citationsGlobal change biology. 2014;20(2):607-21
Career total: 225 works. 34 are in this corpus.
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