Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
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
Agisoft (2017) Dense cloud classification and DTM generation with Agisoft photoscan professional. Available via http://www.agisoft.com/index.php?id=35. Last accessed 8 May 2017
Amon P, Riegl U et al (2015) UAV-based laser scanning to meet special challenges in lidar surveying, Geomatics Indaba Proceedings 2015. Stream 2:138–147
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
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
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
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
Enyedi A, Kozma Bognár V, Berke J (2016) Távérzékelési célú képalkotó algoritmusok összehasonlítása tartalom és szerkezet alapján. Remote Sens 6(6):464–475
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
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
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
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-B1:369–374
Guenther GC (2011) Airborne lidar bathymetry. In: Maune D (ed) Digital elevation model technologies and applications: the DEM users manual. Maryland, Asprs Publications, p. 253–320
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
Jancsó T (2010) Data acquisition and integration 5., Photogrammetry. Available via http://www.tankonyvtar.hu/hu/tartalom/tamop425/0027_DAI5/ch01.html. Accessed 8 May 2017
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
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-B1:405–410
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-B8:99–103
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
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
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
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
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 105–118
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
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
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/C22:149–154
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
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-B7:499–504
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
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-B4:349–352
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
Zhou G, Yang J et al (2012) Advances of flash LiDAR development onboard UAV. Int Arch Photogramm Remote Sens Spat Inf Sci XXXIX-B3:193–198
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this chapter
Cite this chapter
Szabó, G., Bertalan, L., Barkóczi, N., Kovács, Z., Burai, P., Lénárt, C. (2018). Zooming on Aerial Survey. In: Casagrande, G., Sik, A., Szabó, G. (eds) Small Flying Drones. Springer, Cham. https://doi.org/10.1007/978-3-319-66577-1_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-66577-1_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-66576-4
Online ISBN: 978-3-319-66577-1
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)