Mapping, Photogrammetry, and Remote Sensing
What this domain tests
Mapping, Photogrammetry, and Remote Sensing tests how imagery and elevation data become maps, and how to judge their positional accuracy.
Aerial photogrammetry
- Photo scale = f / H, where f is focal length and H is flying height above ground or datum, in the same units.
- Relief displacement d = r × h / H, where r is radial distance from the principal point and h is object height. Displacement is radial from the principal point.
- Stereo overlap (usually 60% forward, 20–30% sidelap) creates parallax; parallax is converted to elevation.
- Orthophotos remove relief displacement and tilt using a DEM; they are not free of positional error.
LiDAR and remote sensing
- LiDAR delivers a point cloud; classify ground returns, then build a DEM, DSM, or TIN.
- GSD (ground sample distance) is the ground spacing of pixels; smaller GSD is finer resolution but not automatically more accurate.
- ASPRS/NSSDA accuracy is stated as RMSE at 95% confidence; check horizontal and vertical classes separately.
Worked example
A camera with a 6-in (0.5-ft) focal length flies at 6,000 ft above ground. Scale = 0.5 / 6,000 = 1:12,000. A 100-ft tall tower 3,000 ft (radial) from the principal point appears displaced by d = 3,000 × 100 / 6,000 = 50 ft outward on the photo. That is why planimetric maps are compiled from orthophotos and why tall features are checked in the field.
Traps
Using flying height above sea level when the scale call is above ground; forgetting to convert focal length to feet; using a single RMSE to describe both horizontal and vertical accuracy; and assuming a dense point cloud is a bare-earth DEM.