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Photogrammetry reconstructs precise 2D and 3D geometric data from overlapping photos. Photogrammetry software and algorithms determine camera positions and dense point clouds; these are then used to create orthophotos, models and plans as a reliable basis for planning, refurbishment and documentation.
Why is photogrammetry important?
- Comprehensive and cost-effective: Large areas, roofs and facades can be captured quickly, for example by drone survey, without scaffolding or operational downtime.
- Precise and traceable: With RTK/PPK, GCPs/check points and calibration, centimetre-level results can be achieved.
- Seamless workflows: Results can be used in CAD/BIM formats such as DWG, DXF and IFC, as well as in GIS and quantity or volume calculations.
- Visually rich: Colour orthophotos and textures make assessment, communication and documentatio
Use cases
- Roof and facade measurement, orthoprojections/unwrapped elevations
- Terrain surveys, cut/fill volumes, construction progress
- Existing-condition documentation, as-built comparison
- Heritage conservation, damage mapping, crack monitoring
Photogrammetry vs LiDAR
- Photogrammetry: Image-based, colour-rich and cost-effective; accuracy depends on texture, lighting, overlap and calibration.
- LiDAR: Direct distance measurement, robust in vegetation and low-texture areas, with highly precise point clouds.
Best practice: Combine both methods, for example colourised LiDAR point clouds with photogrammetric facade orthoprojections.
Common errors and misconceptions
- “More images automatically mean better results”: Without sufficient overlap, stable exposure and GCPs, gaps and distortions can occur.
- Rolling shutter/blur: Movement that is too fast or exposure times that are too long can cause artefacts; shutter settings and flight or movement speed must be coordinated.
- Poor georeferencing: Missing or inaccurate GCPs and unclear coordinate systems or units, such as UTM/ETRS89 or m/mm, make further use more difficult.
- Incorrect GSD: If the ground sampling distance is too coarse, important details are missed; if it is too fine, data volumes increase without added value. GSD should match the intended purpose.
- No QA documentation: Without check points and RMS values, results are difficult to verify.
FAQ
What accuracy is realistic?
With RTK/PPK, well-distributed GCPs and a suitable GSD, centimetre-level results can be achieved. Quality is documented using check points and RMS values.
When is photogrammetry better than LiDAR?
Photogrammetry is suitable for colour-accurate orthoprojections, large textured surfaces and cost-sensitive requirements. LiDAR is superior for low-texture areas and vegetation.
Which formats should I request?
GeoTIFF for orthophotos and orthoprojections, E57/LAS/LAZ for point clouds, DWG/DXF/PDF for 2D data and IFC for BIM. The coordinate system, units, tolerances and version should be documented for each format.