Point clouds are usually associated with drones, LiDAR, and specialized equipment.
This lightning talk will explore how far you can go with something much easier to obtain: phone video.

I’ll show a workflow for turning consumer-grade imagery into point clouds and Cloud Optimized Point Clouds using open-source tools, then bringing the results into QGIS, GeoLibre, and web-based 3D visualization tools. I’ll also show some Gaussian splats as a more intuitive way to visualize the same captured scene.

We already have access to all kinds of aerial imagery, elevation data, LiDAR, and other geospatial data.

But those datasets don’t capture everything. There is still real value in boots-on-the-ground observation, even when those boots aren’t carrying survey-grade equipment.

A ranger, cyclist, or volunteer with a phone can capture details, context, and change that an aerial survey may miss.

The goal is to explore where “good enough” 3D capture can complement the authoritative data we already have, rather than trying to replace it.