2134/9011
Rene Wackrow
Rene
Wackrow
Jim H. Chandler
Jim H.
Chandler
Minimising systematic error surfaces in digital elevation models using oblique convergent imagery
Loughborough University
2011
Close range photogrammetry
Convergent image configuration
Digital camera
Digital elevation model
Spatial measurement
Built Environment and Design not elsewhere classified
2011-10-31 12:02:18
Journal contribution
https://repository.lboro.ac.uk/articles/journal_contribution/Minimising_systematic_error_surfaces_in_digital_elevation_models_using_oblique_convergent_imagery/9449990
There are increasing opportunities to use consumer-grade digital cameras, particularly
if accurate spatial data can be captured. Research recently conducted at
Loughborough University identified residual systematic error surfaces or domes discernible
in digital elevation models (DEMs). These systematic effects are often associated
with such cameras and are caused by slightly inaccurate estimated lens
distortion parameters. A methodology that minimises the systematic error surfaces
was therefore developed, using a mildly convergent image configuration in a vertical
perspective. This methodology was tested through simulation and a series of practical
tests. This paper investigates the potential of the convergent configuration to minimise
the error surfaces, even if the geometrically more complex oblique perspective is used.
Initially, simulated data was used to demonstrate that an oblique convergent image
configuration can minimise remaining systematic error surfaces using various imaging
angles. Additionally, practical tests using a laboratory testfield were conducted to
verify results of the simulation. The need to develop a system to measure the topographic
surface of a flooding river provided the opportunity to verify the findings of
the simulation and laboratory test using real data. Results of the simulation process,
the laboratory test and the practical test are reported in this paper and demonstrate
that an oblique convergent image configuration eradicates the systematic error surfaces
which result from inaccurate lens distortion parameters. This approach is significant
because by removing the need for an accurate lens model it effectively improves
the accuracies of digital surface representations derived using consumer-grade digital
cameras. Carefully selected image configurations could therefore provide new opportunities
for improving the quality of photogrammetrically acquired data.