The 3DGeo Research Group will present some of their latest research at EGU General Assembly 2022.
We are looking forward to meet you at the following talks:
Virtual Laser Scanning using HELIOS++ - Applications in Machine Learning and Forestry: The presentation provides an introduction to VLS, possible use cases, pitfalls and best practices for successful application of [...]
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Posted in 3D, Lidar Group, Publications, Research on Aug 23rd, 2021
In the SYSSIFOSS project, we are investigating how we can take advantage of virtual laser scanning (VLS), the simulation of laser scanning in a computer environment, in forestry applications. These applications include survey planning and optimization, sensitivity analyses, and algorithm development. For example, VLS may be used to investigate the influence of different sensor and [...]
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Posted in 3D, Lidar Group, Publications, Research on Jul 29th, 2021
Our forest laser scanning dataset collected in the frame of the SYSSIFOSS project is now openly available through the PANGAEA Data Publisher:
Weiser, H., Schäfer, J., Winiwarter, L., et al. (2021): Terrestrial, UAV-borne and airborne laser scanning point clouds of central European forest plots, Germany, with extracted individual trees and manual forest inventory measurements. PANGAEA, https://doi.org/10.1594/PANGAEA.933426
Until [...]
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Posted in 3D, Events, Lidar Group, Research on Apr 23rd, 2021
From 19 to 30 April 2021, European researchers from the Earth, planetary and space sciences are gathering in the virtual European Geosciences Union (EGU) assembly.
On Monday, 26 April, two SYSSIFOSS presentations will be opening the block “Point clouds for forestry applications” in session BG11 - Remote sensing for forest applications.
Dr. Fabian E. Fassnacht (KIT) will [...]
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Posted in 3D, Digital Earth, Lidar Group on Sep 11th, 2020
Do you want to find out about the potential of simulating LiDAR data over synthetic forest stands and the steps to get there? Get to know the SYSSIFOSS research project in the video below!
Link to video
In SYSSIFOSS we are using 3D LiDAR forest data to create a database of diverse model trees (different species [...]
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Members of the 3DGeo research group were recently taking advantage of the good weather to acquire some more data within the DFG-funded project SYSSIFOSS. We packed the drone and the RIEGL miniVUX-1UAV laser scanner, and drove to the forest near Bretten where 8 of our plots are located. In four days and 16 flights we [...]
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On Tuesday, 25.02.2020, the 3DGeo group and the SYSSIFOSS project partner from KIT organised a collaborative data processing event. 24 participants spent 6 hours (10:00-16:00) extracting individual trees from airborne LiDAR forest point clouds.
In the SYSSIFOSS project, the segmented 3D tree models are required to simulate 3D forest stands when combined [...]
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Posted in 3D, Lidar Group, Publications, Research on Jan 13th, 2020
In close collaboration with the 3DGeo Research Group, Moritz Bruggisser of the Department of Geodesy and Geoinformation (RG Photogrammetry) presented his current research progress on the impact of acquisition patterns on the robustness and accuracy of tree models derived from UAV LiDAR for forest dynamic studies.
His work fits well into the scope of the SYSSIFOSS [...]
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On November 12-13, Jannika Schäfer from KIT presented the SYSSIFOSS project at the 2nd symposium on satellite-based earth obersvation (2. Symposium zur angewandten Satellitenerdbeoachtung) in Cologne.
SYSSIFOSS is a joint project between the Institute of Geography and Geoecology (IFGG) of the Karlsruhe Institute of Technology (KIT) and the 3DGeo Research Group of Heidelberg University.
In this project [...]
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Posted in 3D, Digital Earth, Lidar Group, Research on May 27th, 2019
On May 1st, the SYSSIFOSS project has started and first test scans have already been conducted in the forest. Experciences from these initial testings serve as a basis for many field campaigns this summer which aim at the acquisition of high-density point clouds of 140 single trees with a RIEGL VZ-400 terrestrial laser scanner. Moreover, [...]
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