Detection of Forest Clear-Cuts with Shuttle Radar Topography Mission (SRTM) and Tandem-X InSAR Data. - Svein Solberg; Rasmus Astrup; Dan Johan Weydahl (Remote. Sens., 2013)

Temporal Stability of X-Band Single-Pass InSAR Heights in a Spruce Forest: Effects of Acquisition Properties and Season. - Svein Solberg; Dan Johan Weydahl; Rasmus Astrup (IEEE Trans. Geosci. Remote. Sens., 2015)

Creating a Regional MODIS Satellite-Driven Net Primary Production Dataset for European Forests. - Mathias Neumann; Adam Moreno; Christopher Thurnher; Volker Mues; Sanna Härkönen; Matteo Mura; Olivier Bouriaud; Mait Lang; Giuseppe Cardellini; Alain Thivolle-Cazat; Karol Bronisz; Ján Merganic; et al. (Remote. Sens., 2016)

Mapping forests using an unmanned ground vehicle with 3D LiDAR and graph-SLAM. - Marek Pierzchala; Philippe Giguère; Rasmus Astrup (Comput. Electron. Agric., 2018)

An inverse shortest path approach to find forwarder productivity functions. - Nils Egil Søvde; Rasmus Astrup; Bruce Talbot (Comput. Electron. Agric., 2019)

Combining MODIS and National Land Resource Products to Model Land Cover-Dependent Surface Albedo for Norway. - Ryan M. Bright; Rasmus Astrup (Remote. Sens., 2019)

Assessing Harvested Sites in a Forested Boreal Mountain Catchment through Global Forest Watch. - Fernando Rossi; Johannes Breidenbach; Stefano Puliti; Rasmus Astrup; Bruce Talbot (Remote. Sens., 2019)

Detection and Classification of Root and Butt-Rot (RBR) in Stumps of Norway Spruce Using RGB Images and Machine Learning. - Ahmad Ostovar; Bruce Talbot; Stefano Puliti; Rasmus Astrup; Ola Ringdahl (Sensors, 2019)

Estimation of Forest Growing Stock Volume with UAV Laser Scanning Data: Can It Be Done without Field Data? - Stefano Puliti; Johannes Breidenbach; Rasmus Astrup (Remote. Sens., 2020)

A New Drone Laser Scanning Benchmark Dataset for Characterization of Single-Tree and Forest Biophysical Properties. - Stefano Puliti; Grant D. Pearse; Michael S. Watt; Edward T. A. Mitchard; Iain McNicol; Magnus Bremer; Martin Rutzinger; Peter Surový; Luke Wallace; Markus Hollaus; Rasmus Astrup (IGARSS, 2021)

Prediction of butt rot volume in Norway spruce forest stands using harvester, remotely sensed and environmental data. - Janne Räty; Johannes Breidenbach; Marius Hauglin; Rasmus Astrup (Int. J. Appl. Earth Obs. Geoinformation, 2021)

Spatio-temporal prediction of soil moisture and soil strength by depth-to-water maps. - Marian Schönauer; Kari Väätäinen; Robert Prinz; Harri Lindeman; Dariusz Pszenny; Martin Jansen; Joachim Maack; Bruce Talbot; Rasmus Astrup; Dirk Jaeger (Int. J. Appl. Earth Obs. Geoinformation, 2021)

Automatic detection of snow breakage at single tree level using YOLOv5 applied to UAV imagery. - Stefano Puliti; Rasmus Astrup (Int. J. Appl. Earth Obs. Geoinformation, 2022)

Spatio-temporal prediction of soil moisture using soil maps, topographic indices and SMAP retrievals. - Marian Schönauer; Robert Prinz; Kari Väätäinen; Rasmus Astrup; Dariusz Pszenny; Harri Lindeman; Dirk Jaeger (Int. J. Appl. Earth Obs. Geoinformation, 2022)

UAV-Based Hyperspectral Imagery for Detection of Root, Butt, and Stem Rot in Norway Spruce. - Benjamin Allen; Michele Dalponte; Hans Ole Ørka; Erik Næsset; Stefano Puliti; Rasmus Astrup; Terje Gobakken (Remote. Sens., 2022)

SiTree: A framework to implement single-tree simulators. - Clara Antón-Fernández; Rasmus Astrup (SoftwareX, 2022)

Climate targets in European timber-producing countries conflict with goals on forest ecosystem services and biodiversity. - Clemens Blattert; Mikko Mönkkönen; Daniel Burgas; Fulvio Di Fulvio; Astor Toraño Caicoya; Marta Vergarechea; Julian Klein 003; Markus Hartikainen; Clara Antón-Fernández; Rasmus Astrup; Michael Emmerich 001; Nicklas Forsell; et al. (Zenodo, 2022)

MultiOptForest Optimization Notebook (V1.0). - Clemens Blattert; Mikko Mönkkönen; Daniel Burgas; Fulvio Di Fulvio; Astor Toraño Caicoya; Marta Vergarechea; Julian Klein 003; Markus Hartikainen; Clara Antón-Fernández; Rasmus Astrup; Michael Emmerich 001; Nicklas Forsell; et al. (Zenodo, 2022)

Climate targets in European timber-producing countries conflict with goals on forest ecosystem services and biodiversity. - Clemens Blattert; Mikko Mönkkönen; Daniel Burgas; Fulvio Di Fulvio; Astor Toraño Caicoya; Marta Vergarechea; Julian Klein 003; Markus Hartikainen; Clara Antón-Fernández; Rasmus Astrup; Michael Emmerich 001; Nicklas Forsell; et al. (Zenodo, 2022)

Climate targets in European timber-producing countries conflict with goals on forest ecosystem services and biodiversity. - Clemens Blattert; Mikko Mönkkönen; Daniel Burgas; Fulvio Di Fulvio; Astor Toraño Caicoya; Marta Vergarechea; Julian Klein 003; Markus Hartikainen; Clara Antón-Fernández; Rasmus Astrup; Michael Emmerich 001; Nicklas Forsell; et al. (Zenodo, 2022)

Towards accurate instance segmentation in large-scale LiDAR point clouds. - Binbin Xiang; Torben Peters; Theodora Kontogianni; Frawa Vetterli; Stefano Puliti; Rasmus Astrup; Konrad Schindler (CoRR, 2023)

FOR-instance: a UAV laser scanning benchmark dataset for semantic and instance segmentation of individual trees. - Stefano Puliti; Grant D. Pearse; Peter Surový; Luke Wallace; Markus Hollaus; Maciej Wielgosz; Rasmus Astrup (CoRR, 2023)

Multi-Sensor Terrestrial SLAM for Real-Time, Large-Scale, and GNSS-Interrupted Forest Mapping. - Weria Khaksar; Rasmus Astrup (CoRR, 2023)

Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning. - Binbin Xiang; Maciej Wielgosz; Theodora Kontogianni; Torben Peters; Stefano Puliti; Rasmus Astrup; Konrad Schindler (CoRR, 2023)

Point2Tree(P2T) - Framework for Parameter Tuning of Semantic and Instance Segmentation Used with Mobile Laser Scanning Data in Coniferous Forest. - Maciej Wielgosz; Stefano Puliti; Phil Wilkes; Rasmus Astrup (Remote. Sens., 2023)

SegmentAnyTree: A sensor and platform agnostic deep learning model for tree segmentation using laser scanning data. - Maciej Wielgosz; Stefano Puliti; Binbin Xiang; Konrad Schindler; Rasmus Astrup (CoRR, 2024)

Benchmarking tree species classification from proximally-sensed laser scanning data: introducing the FOR-species20K dataset. - Stefano Puliti; Emily R. Lines; Jana Müllerová; Julian Frey; Zoe Schindler; Adrian Straker; Matt Allen 001; Lukas Winiwarter; Nataliia Rehush; Hristina Hristova; Brent Murray; Kim Calders; et al. (CoRR, 2024)

BranchPoseNet: Characterizing tree branching with a deep learning-based pose estimation approach. - Stefano Puliti; Carolin Fischer; Rasmus Astrup (CoRR, 2024)

PixSim: Enhancing high-resolution large-scale forest simulations. - Nicolas Cattaneo; Rasmus Astrup; Clara Antón-Fernández (Softw. Impacts, 2024)

RoadSens: An integrated near-field sensor solution for 3D forest road monitoring. - Mostafa Hoseini; Helle Ross Gobakken; Stephan Hoffmann; Csongor Horvath; Johannes Rahlf; Jan Bjerketvedt; Stefano Puliti; Rasmus Astrup (Comput. Electron. Agric., 2025)

Multispectral airborne laser scanning for tree species classification: a benchmark of machine learning and deep learning algorithms. - Josef Taher; Eric Hyyppä; Matti Hyyppä; Klaara Salolahti; Xiaowei Yu; Leena Matikainen; Antero Kukko; Matti Lehtomäki; Harri Kaartinen; Sopitta Thurachen; Paula Litkey; Ville Luoma; et al. (CoRR, 2025)

ForestFormer3D: A Unified Framework for End-to-End Segmentation of Forest LiDAR 3D Point Clouds. - Binbin Xiang; Maciej Wielgosz; Stefano Puliti; Kamil Král; Martin Krucek; Azim Missarov; Rasmus Astrup (CoRR, 2025)