What is photogrammetry in surveying?

Photogrammetry reconstructs 3D geometry and scaled maps from overlapping photographs using Structure from Motion (SfM) and dense matching. It produces point clouds, meshes, textured models, and orthophotos when ground or aerial images have sufficient overlap and control.

When is photogrammetry better than LiDAR?

Photogrammetry is often more cost-effective for open terrain, delivers natural color texture in the model, and works well for orthophotos. LiDAR is stronger under vegetation, in poor lighting, and when you need ground returns without visible texture.

How accurate is drone photogrammetry?

With GCPs or RTK/PPK geotagging, horizontal accuracy often reaches roughly 1–3× the GSD; vertical is typically looser. Always tie to independent check points and follow project specifications.

Photogrammetry for Surveying — SfM, Orthos & Accuracy

How the pipeline works

Capture: Aerial or terrestrial images with high sidelap and overlap. SfM: Tie points link images and solve camera poses. Dense matching: Builds a point cloud or depth maps. Products: DSM/DTM, orthomosaic, mesh, contours—depending on software and classification.

Control and accuracy

GCPs (ground control points) or PPK/RTK image geotags anchor the model to real coordinates. Use independent check points to verify RMSE. Accuracy depends on flying height (GSD), lens quality, calibration, wind, and vegetation—not just pixel count.

Photogrammetry vs LiDAR (quick)

Topic	Photogrammetry	LiDAR
Canopy	Weak under dense trees	Strong with multi-return
Lighting	Needs decent light & texture	Active illumination
Color / texture	Built-in	Often needs separate imagery
Typical budget	Often lower entry	Higher sensor cost

FAQ

Do I need GCPs if I use RTK on the drone?: RTK/PPK reduces the need for many GCPs but check points still validate the solution—especially for vertical.
Can I mix photogrammetry and LiDAR?: Yes—colorize LiDAR with imagery, or fuse clouds in software when deliverables require both geometry and texture.