// the find
mikeroyal/Photogrammetry-Guide
Photogrammetry Guide. Photogrammetry is widely used for Aerial surveying, Agriculture, Architecture, 3D Games, Robotics, Archaeology, Construction, Emergency management, and Medical.
A curated-links guide (not a library) covering the photogrammetry ecosystem: tools, algorithms, drone hardware, GIS software, LiDAR, NeRF, and game engine integration. It's a reading list for someone starting out in photogrammetry who needs a map of the landscape.
The topic coverage is genuinely broad and organized — SfM, point clouds, LiDAR SLAM, ground segmentation, and NeRF are all here with direct GitHub/paper links rather than vague descriptions. The algorithm sections (ICP, NDT, KISS-ICP, Patchwork++) cite actual papers with code, so they're actionable. It covers the full stack from hardware (drone types, camera recommendations) to processing software to deep learning approaches, which saves real research time. The LiDAR section in particular is dense with real citations.
The repo itself contains almost no code — three files, one of which is a near-empty Python stub ('Getting Started with Photogrammetry.py'). It's a markdown document dressed up as a GitHub repo. Many links are to commercial or external software (ENVI, ERDAS, Leica Cyclone) with no commentary on cost, which is useless without context. It hasn't been updated since the maintenance badge says 2024 and newer techniques like 3D Gaussian Splatting are tacked on at the end without the depth given to older topics. The writing quality is uneven — drone buying sections read like a 2019 blog post while the algorithm sections are solid.