3D Geodata Academy

Vectorization of 3D Point Cloud for LiDAR City Models

Published on January 18, 2024 • 2 min read

Clustering • LiDAR • Point Cloud

3D Point Cloud Vectorization for LiDAR City Models

This hands-on approach is standalone and covers the process of LiDAR Vectorization. We then focus on City Model Automatic Generation (LoD 0) in 5 main phases. We are going to code a solution with Python that takes a point cloud (.laz), and returns instantiated vectorized houses with both their 2D footprint and 3D LoD 0 Mesh Model.

This hands-on approach is standalone and covers the process of LiDAR City Model Automatic Generation (LoD 0) in 5 main phases. We are going to code a solution with Python that takes a point cloud (.laz), and returns instantiated vectorized houses with both their 2D footprint and 3D LoD 0 Mesh Model.

Vectorization Materials and 3D Tutorial Resources

🍇3D Dataset + Code: Google Drive Folder
📘Hands-on Guide: In Editorial Phase

My 3D Recommendation 🍉

Turning raster and 3D unstructured datasets (i.e.) point clouds into vectors is often an integral cog of systems in production. I would recommend following up the 3D Python Crash Course if you want to kickstart your journey by creating solutions to identified challenges, using only your computer and Python: 3D Python Crash Course


If you want to get a tad more toward application-first or depth-first approaches, I curated on this website several learning tracks and courses to help you along your journey. Feel free to follow the ones that best suit your need, and do not hesitate to reach out directly to me if you have any questions or if I can give you some advice on your current challenges!

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