Journal
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Volume 52, Issue 5, Pages 2738-2745Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2013.2265295
Keywords
Remote sensing; unmanned aerial vehicles (UAVs)
Categories
Funding
- Winifred Violet Scott Trust
- Australian Antarctic Division
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Micro-unmanned aerial vehicles often collect a large amount of images when mapping an area at an ultrahigh resolution. A direct georeferencing technique potentially eliminates the need for ground control points. In this paper, we developed a camera-global positioning system (GPS) module to allow the synchronization of camera exposure with the airframe's position as recorded by a GPS with 10-20-cm accuracy. Lever arm corrections were applied to the camera positions to account for the positional difference between the GPS antenna and the camera center. Image selection algorithms were implemented to eliminate blurry images and images with excessive overlap. This study compared three different software methods (Photoscan, Pix4D web service, and an in-house Bundler method). We evaluated each based on processing time, ease of use, and the spatial accuracy of the final mosaic produced. Photoscan showed the best performance as it was the fastest and the easiest to use and had the best spatial accuracy (average error of 0.11 m with a standard deviation of 0.02 m). This accuracy is limited by the accuracy of the differential GPS unit (10-20 cm) used to record camera position. Pix4D achieved a mean spatial error of 0.24 m with a standard deviation of 0.03 m, while the Bundler method had the worst mean spatial accuracy of 0.76 m with a standard deviation of 0.15 m. The lower performance of the Bundler method was due to its poor performance in estimating camera focal length, which, in turn, introduced large errors in the Z-axis for the translation equations.
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