Photogrammetry, Remote Sensing and Mapping
Mapping items test scale relationships, sensor geometry and the accuracy language used in mapping contracts. Expect photo scale, relief displacement, GSD, overlap, orthorectification, LiDAR and positional accuracy standards.
Core relationships
- Photo scale S = f ÷ H, with focal length f and flying height above the surface H expressed in the same units.
- Relief displacement d = r·h ÷ H, where r is the radial distance from the principal point; displacement is radial and grows toward the photo edge.
- Stereo compilation typically uses about 60% endlap and 25–30% sidelap.
- Ground sample distance = pixel size × H ÷ f.
- An orthophoto is a differentially rectified image with relief displacement removed. It is a map product, not a boundary survey, and carries no boundary opinion.
LiDAR and remote sensing
Point clouds carry intensity and return information; vertical accuracy is reported as RMSEz and verified against independent ground checkpoints. Classification of ground versus vegetation drives the bare-earth DEM. Multispectral imagery supports land-cover and wetland mapping; indices such as NDVI are band ratios, not boundary measurements.
Worked example
Aerial camera with f = 6.0 in (0.500 ft) flying 6,000 ft above ground. Scale = 0.500 ÷ 6,000 = 1:12,000. A 100-ft tree standing 3.0 in from the principal point displaces by d = 3.0 × 100 ÷ 6,000 = 0.05 in, which at 1:12,000 is about 50 ft on the ground. The same frame covers 9 in × 12,000 ÷ 12 = 9,000 ft of ground per side. This is why canopy edges cannot define a property line.
Traps
- Using flying height above sea level instead of above ground.
- Treating an orthophoto or LiDAR-derived line as a surveyed boundary.
- Quoting horizontal accuracy as a bare number without RMSE, confidence level and checkpoint count.
- Forgetting that relief displacement increases with radial distance, so tall features near the frame edge are worst.