Tag: Lidar
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Major HELIOS++ Release: v2.0.0
We are happy to release a new major version of HELIOS++: https://github.com/3dgeo-heidelberg/helios/releases What’s new in this release? Installation The new way to install HELIOS++ is via the conda or mamba package managers. We recommend mamba or micromamba. After creating a dedicated Python environment for your HELIOS++ project and activating it, run: mamba install helios or…
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Kick-off: Extract4D Project
Last week, we, 3DGeo Heidelberg (Prof. Dr. Bernhard Höfle), had a kick-off meeting for our new joint research project Extract4D, led by Prof. Dr. Katharina Anders (TU Munich, Remote Sensing Applications). Here is a sneak peek at this exciting research project. Background The Earth’s surface is constantly being shaped by wind, water and gravity. Observing…
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Deep learning with simulated laser scanning data for 3D point cloud classification
Esmorís, A.M., Weiser, H., Winiwarter, L., Cabaleiro, J.C. & Höfle, B. (2024): Deep learning with simulated laser scanning data for 3D point cloud classification. ISPRS Journal of Photogrammetry and Remote Sensing. Vol. 215, pp. 192-213. DOI: 10.1016/j.isprsjprs.2024.06.018 3D point clouds acquired by laser scanning are invaluable for the analysis of geographic phenomena. To extract information…
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VirtuaLearn3D: New Preprint
We have published a preprint of our recent work in the VirtuaLearn3D project! Deep learning with simulated laser scanning data for 3D point cloud classification Esmorís, A.M., Weiser, H., Winiwarter, L., Cabaleiro, J.C. & Höfle, B. (2024) Laser scanning is an active remote sensing technique to acquire state-of-the-art spatial measurements in the form of 3D…
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New paper on the potential of simulated laser scanning and field data to train forest biomass models
In great collaboration with colleagues from Karlsruhe (DE), Vienna (AT), Brno (CZ), Leipzig (DE), Raszyn (PL), and Berlin (DE), we published a paper investigating approaches to improve LiDAR-based biomass models when only limited sample plots with field data are available. The main work was carried out by PhD student Jannika Schäfer (IFGG, Karlsruhe Institute of…
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🦇 Halloween release of HELIOS++, v1.3.0
We proudly present our Halloween release of HELIOS++, Version 1.3.0: https://github.com/3dgeo-heidelberg/helios/releases What’s new in this release? HELIOS++ now supports LiDAR simulation of dynamic scenes. We can now simulate laser scanning of scenes that change during the simulation. This is done by introducing rigid motions, which are defined with XML syntax in the scene XML file.…
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Impressions from Silvilaser 2023
Last week, our PhD student, Hannah Weiser, joined Silvilaser 2023 at University College London (UCL). The conference covers cutting-edge science and technology from the laser scanning and forest communities, which is a perfect match for Hannah’s PhD topic and 3DGeo research in general. The week started off with interesting workshops on Tuesday using some of…
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Final meeting of the E-TRAINEE project
Last week, the 3DGeo research group hosted the final meeting of the E-TRAINEE project, finally and for the first time in presence. For almost three years now, we have been developing a research-oriented open-source e-learning course – soon to be published! The course on “Time Series Analysis in Remote Sensing for Understanding Human-Environment Interactions” teaches…
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Introducing the VirtuaLearn3D Project
With VirtuaLearn3D (Virtual Laser Scanning for Machine Learning Algorithms in Geographic 3D Point Cloud Analysis), a new project of the 3DGeo group has started. The focus of this project is to enable powerful machine learning algorithms for geographic point cloud analysis by advancing the concept of virtual laser scanning to overcome the lack of training…
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Open Data: Multi-platform point clouds and orthophotos of the inland dune in Sandhausen
The commune Sandhausen (Baden-Württemberg) got its name from the inland dune, which is located in the area of the village. In 2021 and 2022, the 3DGeo group of Heidelberg University conducted UAV-based and ground-based surveys of three areas of the inland dune of Sandhausen to acquire 3D point clouds and orthophotos. The dataset is freely and…
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Data description paper: Individual tree point clouds and tree measurements from multi-platform laser scanning in German forests
New data description paper on our tree point cloud dataset was just published Today, our data description paper was published in the open access Journal Earth System Science Data: Weiser, H., Schäfer, J., Winiwarter, L., Krašovec, N., Fassnacht, F. E., and Höfle, B. (2022): Individual tree point clouds and tree measurements from multi-platform laser scanning…
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Nina Krašovec wins Nahtigal Award 2021
This week on 29 November, it was announced that our team member Nina Krašovec received Nahtigal Award from the Faculty of Arts of the University of Ljubljana (UL) for her master’s thesis “Detection of standing dead trees using leaf-on and leaf-off UAV-borne laser scanning point cloud data in mixed forests”. The research was conducted under…