Zooming on Aerial Survey

  • Gergely Szabó
  • László Bertalan
  • Norbert Barkóczi
  • Zoltán Kovács
  • Péter Burai
  • Csaba Lénárt


The aim of this chapter is to provide a general overview about the main components of a developed UAS mapping system, the survey, and processing procedure. At first (4.1), a brief introduction is given about basic operational elements and accessories of UAS. Then, recent camera/sensor technologies allowing various survey solutions are going to be discussed. Once these hardware components are presented, the detailed workflow of a basic UAV-based mapping procedure is described (4.2). A further discussion focuses not only on the analytical or planning phases but also on providing useful information on the operational and processing parts as well (4.3). Then, there comes image acquisition and project planning (4.4). The photogrammetry-based image processing requires detailed expertise and attention; Sect. 4.5 maybe helpful to avoid potential mistakes. The last section (4.6) summarizes some aspects of the use of LiDAR technologies in UAV-based surveys.


  1. d’Oleire-Oltmanns S, Marzolff I et al (2012) Unmanned aerial vehicle (UAV) for monitoring soil erosion in Morocco. Remote Sens 4(11):3390–3416. doi: 10.3390/rs4113390 CrossRefGoogle Scholar
  2. Agisoft (2017) Dense cloud classification and DTM generation with Agisoft photoscan professional. Available via Last accessed 8 May 2017
  3. Amon P, Riegl U et al (2015) UAV-based laser scanning to meet special challenges in lidar surveying, Geomatics Indaba Proceedings 2015. Stream 2:138–147Google Scholar
  4. Andersen MS, Gergely Á et al (2017) Processing and performance of topobathymetric lidar data for geomorphometric and morphological classification in a high-energy tidal environment. Hydrol Earth Syst Sci 21:43–63. doi: 10.5194/hess-21-43-2017 CrossRefGoogle Scholar
  5. Candiago S, Remondino F et al (2015) Evaluating multispectral images and vegetation indices for precision farming applications from UAV images. Remote Sens 7(4):4026–4047. doi: 10.3390/rs70404026 CrossRefGoogle Scholar
  6. Carrio A, Pestana J et al (2015) UBRISTES: UAV-based building rehabilitation with visible and thermal infrared remote sensing. In: Reis L, Moreira A, Lima P, Montano L, Muñoz-Martinez V (eds) Robot 2015: second Iberian robotics conference, Advances in Intelligent Systems and Computing, vol 417. Springer, Cham. doi: 10.1007/978-3-319-27146-0_19 Google Scholar
  7. Colomina I, Molina P (2014) Unmanned aerial systems for photogrammetry and remote sensing: a review. ISPRS J Photogramm Remote Sens 92:79–97. doi: 10.1016/j.isprsjprs.2014.02.013 CrossRefGoogle Scholar
  8. Enyedi A, Kozma Bognár V, Berke J (2016) Távérzékelési célú képalkotó algoritmusok összehasonlítása tartalom és szerkezet alapján. Remote Sens 6(6):464–475Google Scholar
  9. Essen H, Johannes W et al (2012) High resolution W-band UAV SAR. Paper presented at the 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 22–27 July 2012. doi:  10.1109/IGARSS.2012.6352480
  10. Fonstad MA, Dietrich JT et al (2013) Topographic structure from motion: a new development in photogrammetric measurement. Earth Surf Process Landf 38(4):421–430. doi: 10.1002/esp.3366 CrossRefGoogle Scholar
  11. Georgopoulos A, Oikonomou C et al (2016) Evaluating unmanned aerial platforms for cultural heritage large scale mapping. Int Arch Photogramm Remote Sens Spat Inf Sci XLI-B5:355–362. doi: 10.5194/isprsarchives-XLI-B5-355-2016 CrossRefGoogle Scholar
  12. Grenzdörffer G, Niemeyer F, Schmidt F (2012) Development of four vision camera system for a micro-UAV. Int Arch Photogramm Remote Sens Spat Inf Sci XXXIX-B1:369–374CrossRefGoogle Scholar
  13. Guenther GC (2011) Airborne lidar bathymetry. In: Maune D (ed) Digital elevation model technologies and applications: the DEM users manual. Maryland, Asprs Publications, p. 253–320Google Scholar
  14. Höfle B, Rutzinger M (2011) Topographic airborne LiDAR in geomorphology: a technological perspective. Z Geomorphol 55(2):1–29. doi: 10.1127/0372-8854/2011/0055S2-0043 CrossRefGoogle Scholar
  15. Jancsó T (2010) Data acquisition and integration 5., Photogrammetry. Available via Accessed 8 May 2017
  16. Kalisperakis I, Stentoumis C et al (2015) Leaf area index estimation in vineyards from UAV hyperspectral data, 2D image mosaics and 3D canopy surface models. Int Arch Photogramme Remote Sens Spat Inf Sci XL-1/W4:299–303. doi: 10.5194/isprsarchives-XL-1-W4-299-2015 CrossRefGoogle Scholar
  17. Kohoutek T, Eisenbeiss H (2012) Processing of UAV based range imaging data to generate detailed elevation models of complex natural structures. Int Arch Photogramm Remote Sen Spat Inf Sci XXXIX-B1:405–410CrossRefGoogle Scholar
  18. Levin E, Zarnowski A, McCarty JL, Bialas J, Banaszek A, Banaszek S (2016) Feasibility study of inexpensive thermal sensors and small UAS deployment for living human detection in rescue missions application scenarios. Int Arch Photogramm Remote Sens Spat Inf Sci XLI-B8:99–103CrossRefGoogle Scholar
  19. Mandlburger G, Pfennigbauer M et al (2015) Complementing airborne laser bathymetry with UAV-based lidar for capturing alluvial landscapes. Proc. SPIE 9637. Remote Sens Agric Ecosyst Hydrol XVII:96370A. doi: 10.1117/12.2194779 Google Scholar
  20. Miřijovský J, Langhammer J (2015) Multitemporal monitoring of the Morphodynamics of a mid-mountain stream using UAS photogrammetry. Remote Sens 7(7):8586–8609. doi: 10.3390/rs70708586 CrossRefGoogle Scholar
  21. Nebiker S, Lack N et al (2016) Light-weight multispectral UAV sensors and their capabilities for predicting grain yield and detecting plant diseases. Int Arch Photogramm Remote Sens Spat Inf Sci XLI-B1:963–970. doi: 10.5194/isprsarchives-XLI-B1-963-2016 CrossRefGoogle Scholar
  22. Nex F, Remondino F (2014) UAV for 3D mapping applications: a review. Appl Geomatics 6(1):1–15. doi: 10.1007/s12518-013-0120-x CrossRefGoogle Scholar
  23. Pfeifer N, Mandlburger G et al (2015) Lidar: exploiting the versatility of a measurement principle in photogrammetry. In: 55th photogrammetric week 2015. Stuttgart, Germany, p 105–118Google Scholar
  24. Remy M, de Macedo K, Moreira J (2012) The first UAV-based P- and X-band interferometric SAR system. Paper presented at the 2012 IEEE international geoscience and remote sensing symposium (IGARSS), 22–27 July 2012. doi: 10.1109/IGARSS.2012.6352478
  25. Rosen PA, Hensley S et al (2007) UAVSAR: new NASA airborne SAR system for research. IEEE Aerosp Electron Syst Mag 22(11):21–28. doi: 10.1109/MAES.2007.4408523 CrossRefGoogle Scholar
  26. Scholtz A, Kaschwich C et al (2011) Development of a new multi-purpose UAS for scientific application. Int Arch Photogramm Remote Sens Spat Inf Sci XXXVIII-1/C22:149–154CrossRefGoogle Scholar
  27. Szabó S, Enyedi P et al (2015) Automated registration of potential locations for solar energy production with light detection and ranging (LiDAR) and small format photogrammetry. J Clean Prod 112(5):3820–3829. doi: 10.1016/j.jclepro.2015.07.117 Google Scholar
  28. Wallace L, Lucieer A et al (2012) Assessing the feasibility of UAV-based LiDAR for high resolution forest change detection. Int Arch Photogramm Remote Sens Spat Inf Sci XXXIX-B7:499–504CrossRefGoogle Scholar
  29. Xie F, Lin Z et al (2012) Study on construction of 3D building based on UAV images. Int Arch Photogramm Remote Sens Spat Inf Sci XXXIX-B1:469–473. doi: 10.5194/isprsarchives-XXXIX-B1-469-2012 CrossRefGoogle Scholar
  30. Yun M, Kimb J et al (2012) Application possibility of smartphone as payload for photogrammetric UAV system. Int Arch Photogramm Remote Sens Spat Inf Sci XXXIX-B4:349–352CrossRefGoogle Scholar
  31. Zhang W, Qi J et al (2016) An easy-to-use airborne LiDAR data filtering method based on cloth simulation. Remote Sens 8(6):501. doi: 10.3390/rs8060501 CrossRefGoogle Scholar
  32. Zhou G, Yang J et al (2012) Advances of flash LiDAR development onboard UAV. Int Arch Photogramm Remote Sens Spat Inf Sci XXXIX-B3:193–198CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Gergely Szabó
    • 1
  • László Bertalan
    • 1
  • Norbert Barkóczi
    • 1
  • Zoltán Kovács
    • 1
  • Péter Burai
    • 1
  • Csaba Lénárt
    • 1
  1. 1.Department of Physical Geography and GISUniversity of DebrecenDebrecenHungary

Personalised recommendations