3D Geospatial Data Processing Group
3D Geospatial Data Processing (3DGeo) Research Group
We investigate and develop computational methods for the geographic analysis of 3D/4D point clouds. Our datasets are acquired by cutting-edge Earth observation technology (e.g. laser scanning/LiDAR, photogrammetry/SfM and SAR). We aim at increasing the understanding of geographic phenomena by observing and analyzing them in full 3D, in near real-time with high spatial and temporal resolution. Our methods can be applied to study physical processes (e.g. geomorphology), anthropogenic landscapes (e.g. emission reduction) and inherent human-environmental interactions (e.g. natural hazards, forestry and agriculture). Our research sites are spread all over the world: we perform in-situ 3D measurements, code in the lab and simulate Earth observation with our own open source software for virtual laser scanning.
Here, you can find our research projects, publications, videos, and open source code & data.
We love both programming and field work!
Latest News (RSS Feed)
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 […]
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 […]
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 […]
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 […]
Successful proposal: Fostering a community-driven and sustainable HELIOS++ scientific software The 3DGeo Group and the Scientific Software Center (SSC) of Heidelberg University have been successful with their proposal in the DFG call “Research Software – Quality assured and re-usable”, together with two other project proposals at Heidelberg University (see press release). The main objective of […]
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. […]
In September 2023, our new research project AImon5.0 has been kicked-off. In this project the open-source frameworks HELIOS++ and py4dgeo of the 3DGeo research group will be combined to enhance current approaches for operational risk monitoring. AImon5.0 is an interdisciplinary collaboration project of the 3DGeo research group with DMT GmbH & Co. KG (project leader), […]
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 […]
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 […]
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 […]
Archive of News
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