Paper
6 September 2017 Commercial vs professional UAVs for mapping
Konstantinos G. Nikolakopoulos, Ioannis Koukouvelas
Author Affiliations +
Proceedings Volume 10444, Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017); 1044409 (2017) https://doi.org/10.1117/12.2279409
Event: Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017), 2017, Paphos, Cyprus
Abstract
The continuous advancements in the technology behind Unmanned Aerial Vehicles (UAVs), in accordance with the consecutive decrease to their cost and the availability of photogrammetric software, make the use of UAVs an excellent tool for large scale mapping. In addition with the use of UAVs, the problems of increased costs, time consumption and the possible terrain accessibility problems, are significantly reduced. However, despite the growing number of UAV applications there has been a little quantitative assessment of UAV performance and of the quality of the derived products (orthophotos and Digital Surface Models). Here, we present results from field experiments designed to evaluate the accuracy of photogrammetrically-derived digital surface models (DSM) developed from imagery acquired with onboard digital cameras. We also show the comparison of the high resolution vs moderate resolution imagery for largescale geomorphic mapping. The acquired data analyzed in this study comes from a small commercial and a professional UAV. The test area was mapped using the same photogrammetric grid by the two UAVs. 3D models, DSMs and orthophotos were created using special software. Those products were compared to in situ survey measurements and the results are presented in this paper.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Konstantinos G. Nikolakopoulos and Ioannis Koukouvelas "Commercial vs professional UAVs for mapping", Proc. SPIE 10444, Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017), 1044409 (6 September 2017); https://doi.org/10.1117/12.2279409
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Unmanned aerial vehicles

Orthophoto maps

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