UKy-Campus-LIDAR
Overview
Extract UE 4.24.3 UKy Campus LiDAR point cloud + DTM terrain tiles + aerial imagery into open formats and view them in an interactive Three.js web viewer — no Unreal Engine required at runtime. The twin now extends past campus to the full Lexington / Lextran service area: authoritative LFUCG building footprints and street centerlines, KyFromAbove/KYAPED-derived elevations, active LFUCG traffic-signal locations, attributed OpenStreetMap crossing evidence, and the live Lextran bus feed. Large city layers stay packed into one buffer / draw call per layer, with adaptive quality controls protecting the viewer's 30 fps interaction target.
Google Photorealistic 3D Tiles streamed into the Three.js twin — the whole city in real, textured 3D (campus, downtown skyline, the Lextran service area). This optional layer stays off until enabled with a valid provider key; its cache is transient.
From the project’s README on GitHub.
At a glance
| Repository | Kentucky-Open-Science/UKy-Campus-LIDAR |
|---|---|
| Research area | Robotics, drones & sensing |
| Primary language | JavaScript |
| Languages | JavaScript 68.8%, Python 29.6%, CSS 0.9%, HTML 0.8% |
| License | None specified |
| Stars / forks | 0 / 0 |
| Open issues and pull requests | 0 |
| Created | 2026-06-12 |
| Last push | 2026-07-18 |
| Default branch | main |
| Topics | lidar |
What the README covers
- Gallery
- Quick start
- What's in here
- Re-extracting from source
- Filling in Lexington — KyFromAbove LiDAR
- Authoritative public-data rebuild
- Exact service bbox
- Source precedence and modeled fields
- Reproduce the current layers
- Export the complete static map to USD
- Licensing and redistribution
- Photorealistic basemap — Google 3D Tiles (opt-in)
- Viewer controls
- Generated artifacts and exact counts
- Digital twin — controllable signals + autonomous agents
- Radio survey and LoRaWAN placement
- Live traffic cameras
- Camera-detected cars (Phase 1 — geometry + spawn)
- Multiplayer twin server — shared world over an API
- Runtime traffic and scenario API
- First-person cameras + vision navigation (YOLO)
- Gym environment (campus_gym)
- Language-conditioned navigation + evaluation (the agentic layer)
- NPC traffic + signals, scenarios, vectorization, training
Top contributors
- @armstrongsam25 (97 commits)
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Get the code
git clone https://github.com/Kentucky-Open-Science/UKy-Campus-LIDAR.git