ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-5, 17-24, 2014
© Author(s) 2014. This work is distributed
under the Creative Commons Attribution 3.0 License.
28 May 2014
Assessing UAV platform types and optical sensor specifications
B. Altena and T. Goedemé Faculty of Industrial engineering, KU Leuven Jan de Nayerlaan 5, Sint-Katelijne-Waver, Belgium
Keywords: UAV photogrammetry, platform comparison, optical quality Abstract. Photogrammetric acquisition with unmanned aerial vehicles (UAV) has grown extensively over the last couple of years. Such mobile platforms and their processing software have matured, resulting in a market which offers off-the-shelf mapping solutions to surveying companies and geospatial enterprises. Different approaches in platform type and optical instruments exist, though its resulting products have similar specifications. To demonstrate differences in acquisitioning practice, a case study over an open mine was flown with two different off-the-shelf UAVs (a fixed-wing and a multi-rotor). The resulting imagery is analyzed to clarify the differences in collection quality. We look at image settings, and stress the fact of photographic experience if manual setting are applied. For mapping production it might be safest to set the camera on automatic. Furthermore, we try to estimate if blur is present due to image motion. A subtle trend seems to be present, for the fast flying platform though its extent is of similar order to the slow moving one. It shows both systems operate at their limits. Finally, the lens distortion is assessed with special attention to chromatic aberration. Here we see that through calibration such aberrations could be present, however detecting this phenomena directly on imagery is not straightforward. For such effects a normal lens is sufficient, though a better lens and collimator does give significant improvement.
Conference paper (PDF, 4014 KB)

Citation: Altena, B. and Goedemé, T.: Assessing UAV platform types and optical sensor specifications, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-5, 17-24, doi:10.5194/isprsannals-II-5-17-2014, 2014.

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