Universitätssiegel
logo
Secretary
Bettina Knorr
knorr@uni-heidelberg.de
Phone: +49 (0) 6221 54-5560
Fax: +49 (0) 6221 54-4529
 
Postal Address
Heidelberg University
Prof. Bernhard Höfle
Institute of Geography
Im Neuenheimer Feld 368
69120 Heidelberg
Germany
 

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)
20.07.2024 08:09
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 […]

17.01.2024 14:45
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 […]

06.12.2023 11:46
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 […]

25.11.2023 18:57
DFG Software Grant

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 […]

31.10.2023 15:30
🦇 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. […]

15.09.2023 14:28
Kick-off: AImon5.0 – Real-time monitoring of gravitational mass movements for critical infrastructure risk management with AI-assisted 3D metrology

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), […]

11.09.2023 11:38
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 […]

19.06.2023 11:58
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 […]

20.04.2023 14:40
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 […]

06.04.2023 09:46
CharAct4D – Unravelling Landscape Dynamics via Automatic Characterization of Surface Activity using Geographic 4D Monitoring

With her new project CharAct4D Dr. Katharina Anders has become part of the Eliteprogramme for Postdocs of the Baden-Württemberg Stiftung, which supports early career researchers to qualify for a professorship -check the related press release by Heidelberg University. Many congratulations, Katharina! Katharina’s research interests in the 3DGeo research group are method development for 3D/4D change analysis […]

Archive of News

https://giscienceblog.uni-heidelberg.de/category/research/lidar-group/

Seitenbearbeiter: Webmaster-Team
Letzte Änderung: 31.01.2024
zum Seitenanfang/up