The 3DGeo Research Group at Heidelberg University (Germany) investigates and develops computational methods for the geographic analysis of 3D/4D point clouds and designs participatory STEM education concepts.
Here, we host and maintain our open-source software, public documentations and e-learning material.
| Software | Description |
|---|---|
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Python library / command line tool for high-fidelity LiDAR Simulation (Virtual Laser Scanning) |
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Python library for change analysis in multitemporal and 4D point clouds |
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Python library for voxel-based point cloud operations |
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Python library for the storage and sharing of single tree-based point clouds (incl. REST API and web frontend), see our web frontend instance https://pytreedb.geog.uni-heidelberg.de/ |
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4DGeo Dashboard for visualizing the results of change analysis in environmental point clouds, see our web instance https://3dgeo-heidelberg.github.io/4DGeo/ |
| Project | Description | Source code |
|---|---|---|
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Documentation of 3DGeo outcomes in the project AIMon5.0, incl. example notebooks | 3dgeo-heidelberg/aimon |
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Showcase of the concept of virtual laser scanning of dynamic scenes (VLS-4D), incl. example notebooks | 3dgeo-heidelberg/vls-4d |
| Course | Description | Source code |
|---|---|---|
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Open e-learning course on time series analysis in remote sensing for understanding human-environment interactions | 3dgeo-heidelberg/etrainee |