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Tag Archive 'SYSSIFOSS'

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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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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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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Airborne light detection and ranging (LiDAR) data provides reliable information on forest structure. Related forest inventory approaches recently evolved into operational tools. Today, further optimization of existing approaches is pursued to ensure high data quality of the inventory information and cost-efficiency over varied environmental and silvicultural conditions. Synthetic LiDAR data has been suggested as useful [...]

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