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Evaluating spatial resolution for quality assurance of UAV images

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Abstract

With advantages of operational convenience, quick process and economic feasibility, the availability of UAV Photogrammetry is increasing significantly in many different fields of acquiring geospatial information recently. In particular, it is being applied even to a cadastral surveying, including production of orthophotos and large scale topographic maps that require highly precise positional information. However, a quality verification process of UAV images should be preceded, because they are quite inhomogeneous by acquiring under strong variable conditions such as a rapid change of flying heights and exposure stations. In this paper, as part of a quality assurance plan for UAV images to ensure high quality products by UAV-Photogrammetry, a simple analysis method for the spatial resolution of UAV images was presented. To do this, portable resolution test charts in a pattern of Siemens star and Tri-bar were installed in a test area before imaging, and then visual resolution and GSD (Ground Sample Distance) appeared on the photographed images were measured. UAV images were taken with both payloads of fixed and rotary wing. The flight heights were 130 m and 260 m for fixed wing, and just 130 m for rotary wing. The results showed that a GSD of UAV image from fixed wing installed with a camera (Canon IXUS 127 HS) is 4.08 cm at the flying height of 130 m, 7.94 cm at 260 m, and a GSD of UAV image from rotary wing installed with a camera (Sony NEX-5N) is 4.10 cm at the flying height of 130 m. These values are almost consistent with theoretical resolution. The method proposed in this study is considered as a very useful for the applying of spatial resolution analysis of UAV images.

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Authors and Affiliations

  1. Department of Civil Engineering, Dong-A University, Busan, South Korea

    Jaeone Lee & Sangmin Sung

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  1. Jaeone Lee
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  2. Sangmin Sung
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Correspondence to Sangmin Sung.

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Lee, J., Sung, S. Evaluating spatial resolution for quality assurance of UAV images. Spat. Inf. Res. 24, 141–154 (2016). https://doi.org/10.1007/s41324-016-0015-0

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  • DOI: https://doi.org/10.1007/s41324-016-0015-0

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