Photogrammetry and Remote Sensing
Questions test the chain from sensor geometry to a usable product: orientation, ground sample distance, elevation-model type and radiometric interpretation.
Geometry and orientation
- Interior orientation: focal length, principal point and lens distortion. Exterior orientation: three position and three attitude parameters per image.
- The collinearity condition states that the perspective centre, the image point and the ground point are collinear. Bundle adjustment solves all orientations simultaneously and can include self-calibration.
- Forward overlap is typically about 60% (minimum ~55%) and sidelap 20–30%, so each ground point appears on at least two images.
- GSD = (pixel size × flying height) / focal length, with all lengths in the same unit.
Products and sensors
A DSM includes vegetation and buildings; a DTM is bare earth; DEM is the generic term. Orthorectification removes tilt and relief displacement and needs a DEM. LiDAR gives direct range and multiple returns. SAR is side-looking and all-weather but suffers speckle and layover, so InSAR or radargrammetry supplies elevation.
Indices
NDVI = (NIR − Red) / (NIR + Red), ranging −1 to +1; healthy vegetation is usually above 0.3. NDWI uses green and NIR for water.
Worked example: a camera with 100 mm focal length and 5.2 µm pixels flies at 1200 m above ground. GSD = (5.2 × 10⁻⁶ × 1200) / 0.100 = 0.0624 m, about 6.2 cm. If the specification is 5 cm, solve for height: H = GSD × f / pixel = 0.05 × 0.1 / 5.2 × 10⁻⁶ ≈ 962 m above ground, or choose a longer lens.
Traps
- Mixing micrometres and millimetres in the GSD formula - the commonest arithmetic loss.
- Quoting DSM accuracy as if it were DTM accuracy; buildings inflate the error statistics.
- Assuming overlap alone guarantees matching over water, snow or uniform sand.