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Mitigating systematic error in topographic models derived from UAV and ground-based image networks

James, MR; Robson, S; (2014) Mitigating systematic error in topographic models derived from UAV and ground-based image networks. Earth Surface Processes and Landforms , 39 (10) 1413 - 1420. 10.1002/esp.3609. Green open access

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Abstract

High resolution digital elevation models (DEMs) are increasingly produced from photographs acquired with consumer cameras, both from the ground and from unmanned aerial vehicles (UAVs). However, although such DEMs may achieve centimetric detail, they can also display systematic broad-scale error that restricts their wider use. Such errors which, in typical UAV data are expressed as a vertical 'doming' of the surface, result from a combination of near-parallel imaging directions and inaccurate correction of radial lens distortion. Using simulations of multi-image networks with near-parallel viewing directions, we show that enabling camera self-calibration as part of the bundle adjustment process inherently leads to erroneous radial distortion estimates and associated DEM error. This effect is relevant whether a traditional photogrammetric or newer structure-from-motion (SfM) approach is used, but errors are expected to be more pronounced in SfM-based DEMs, for which use of control and check point measurements are typically more limited. Systematic DEM error can be significantly reduced by the additional capture and inclusion of oblique images in the image network; we provide practical flight plan solutions for fixed wing or rotor-based UAVs that, in the absence of control points, can reduce DEM error by up to two orders of magnitude. The magnitude of doming error shows a linear relationship with radial distortion and we show how characterization of this relationship allows an improved distortion estimate and, hence, existing datasets to be optimally reprocessed. Although focussed on UAV surveying, our results are also relevant to ground-based image capture. © 2014 John Wiley & Sons, Ltd.

Type: Article
Title: Mitigating systematic error in topographic models derived from UAV and ground-based image networks
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/esp.3609
Publisher version: http://dx.doi.org/10.1002/esp.3609
Additional information: © 2014 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1443475
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