Minimising systematic error surfaces in digital elevation models using oblique convergent imagery

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

The accuracy of a river bed moulding/casting system and the effectiveness of a low-cost digital camera for recording river bed fabric

Digital photogrammetry has been used to develop and test an artificial river bed moulding and casting system, which allows the pebbles within a coarse grain river bed to be recreated for hydraulic research in a laboratory flow channel or flume. Imagery of both the original streambed and the cast facsimile was acquired using a non-metric Kodak DCS460 digital camera and digital elevation models and orthophotographs were derived and compared to assess the accuracy of the moulding and casting system. These comparative tests proved to be critical in modifying and developing the system. Additional imagery was obtained in the field using a non-metric Olympus C3030 “compact” digital camera to assess whether far cheaper camera technology could deliver data appropriate for such comparative examinations. Internal calibration parameter sets and data that were generated were compared with data obtained by the non-metric Kodak DCS460. These tests demonstrate that digital sensors built around highquality 35 mm professional camera bodies and lenses are required for comparative examinations and for similar system development

Metric capabilities of low-cost digital cameras for close range surface measurement

This paper examines the potential of low cost digital cameras for close-range surface measurement using feature based image matching methods. This is achieved through extracting digital elevation models (DEMs) and comparing accuracies between three low-cost consumer grade digital cameras (Sony DSC-P10, Olympus C3030, Nikon Coolpix 3100) and the proven Kodak DCS460. Surprisingly, the tests revealed that the highest accuracies were achieved using the Sony DSC-P10, not the Kodak DCS460, whilst the other two cameras certainly proved suitable for most close-range surface measurement tasks. Lens modelling was found to provide a limiting constraint on final accuracies, with very small systematic error surfaces caused by residual imperfections in lens modelling. The IMAGINE OrthoBASE Pro software and an independent self-calibrating bundle adjustment were used to process these data. These tests identified an inaccuracy in the self-calibrating capability of IMAGINE OrthoBASE Pro version 8.6 and Leica Geosystems LPS 8.7, which will be rectified in subsequent software releases. The study has demonstrated that cheaper consumer grade digital cameras have potential for routine surface measurement provided lens modelling is considered. The lead author is maintaining a web based repository for camera calibration data, which may assist other users