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Unmanned Aircraft Vehicles

  • Joseph Awange
  • John Kiema
Chapter
Part of the Environmental Science and Engineering book series (ESE)

Abstract

In recent decades, Unmanned Aircraft Vehicles (UAVs) became a popular household name that caught attention over the world. With its continued development, its advantages are increasingly outstanding whether for military or civilian use. Compared to the manned aircrafts, UAVs are cheap, efficient, convenient, reduce casualty rates in the modern war and achieve complex goals when combined with other equipments (e.g., sensors, scanners) in the civil fields. Therefore, many countries, especially the developed countries, are already engaged in the research and development of UAVs. This chapter systematically introduces UAVs from the perspective of terminology and definitions, historical background, basics of unmanned aerial systems, GNSS in supporting UAVs, Environment applications of UAVs, and finally discusses its future challenges.

References

  1. 1.
    Veroustraete F (2015) The rise of the drones in agriculture. EC Agric 325–327. https://www.researchgate.net/publication/282093589
  2. 2.
    Villasenor J (2012) What is a drone, anyway? Sci Am. https://blogs.scientificamerican.com/guest-blog/what-is-a-drone-anyway/. Retrieved at 6 Jan 2017
  3. 3.
    Gertler J (2012) U.S. unmanned aerial systems. Congressional Research Service. https://fas.org/sgp/crs/natsec/R42136.pdf. Retrieved at 8 Jan 2017
  4. 4.
    The Development, Concepts and Doctrine Centre (DCDC) (2011) Joint Doctrine Note 2/11, The UK Approach To Unmanned Aircraft Systems. Ministry of Defence. https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/33711/20110505JDN_211_UAS_v2U.pdf. Retrieved at 8 Jan 2017
  5. 5.
    Wendel A (2014) 13 innovative ways earth scientists use drones. Earth Space Sci News 99(4):30–34Google Scholar
  6. 6.
    Clarke R (2016) Understanding the drone epidemic. Comput Law & Secur Rev 30(3):230–246.  https://doi.org/10.1016/j.clsr.2014.03.002CrossRefGoogle Scholar
  7. 7.
    Custers B (Ed) (2016) The future of drone use - opportunities and threats from ethical and legal perspecitives. Springer, Berlin.  https://doi.org/10.1007/978-94-6265-132-6_1
  8. 8.
    Dalamagkidis K (2015) Handbook of unmanned aerial vehicles (Chap. 4), aviation history and unmanned flight. Springer Netherlands, pp 57–81.  https://doi.org/10.1007/978-90-481-9707-1_93
  9. 9.
    Renard JB, Dulac F, Berthet G (2015) LOAC: a small aerosol optical counter/sizer for ground-based and balloon measurements of the size distribution and nature of atmospheric particles - Part 2: First results from balloon and unmanned aerial vehicle flights. Atmos Meas Tech Discuss 27:1261–1299.  https://doi.org/10.5194/amtd-8-1261-2015CrossRefGoogle Scholar
  10. 10.
    Fahlstrom PG, Gleason TJ (2012) Introduction to UAV system, 4th edn. Wiley, New YorkGoogle Scholar
  11. 11.
    De Havilland Aircrafts Museum (2017) De Havilland DH82B Queen Bee. http://www.dehavillandmuseum.co.uk/aircraft/de-havilland-dh82b-queen-bee/. Retrieved at 9 Jan 2017
  12. 12.
    National Museum of the US Air Force (2015) Radioplane/Northrop MQM-57 Falconer. http://www.nationalmuseum.af.mil/Visit/MuseumExhibits/FactSheets/Display/tabid/509/Article/195784/radioplanenorthrop-mqm-57-falconer.aspx. Retrieved at 9 Jan 2017
  13. 13.
    Zaloga SJ (2011) Unmanned aerial vehicles: robotic air warfare 1917–2007. Bloomsbury Publishing, LondonGoogle Scholar
  14. 14.
    Keane JF, Carr SS (2013) A brief history of early unmanned aircraft. Johns Hopkins APL Tech Dig 32(3):558–571. https://pdfs.semanticscholar.org/ed38/531575cf6fce272fd3d88ebe06f9775b021f.pdf
  15. 15.
    Kenzo N (2007) Prospect and recent research & development for civil use autonomous unmanned aircraft as UAV and MAV. J Syst Des Dyn 1(2):120–128.  https://doi.org/10.1299/jsdd.1.120CrossRefGoogle Scholar
  16. 16.
    Gupta SG, Ghonge MM, Jawandhiya PM (2013) Review of unmanned aircraft system (UAS). Int J Adv Res Comput Eng & Technol 2(4):1646–1658. https://www.researchgate.net/profile/Mangesh_Ghonge/publication/249998592_Review_of_Unmanned_Aircraft_System_UAS/links/02e7e51e8ef1668ce8000000.pdf
  17. 17.
    UAV Insider (2013) Rotary wing vs fixed wing UAVs. http://www.uavinsider.com/rotary-wing-vs-fixed-wing-uavs/. Retrieved at 11 Jan 2017
  18. 18.
    QuestUAV (2015) Fixed wing versus rotary wing for UAV mapping applications. http://www.questuav.com/news/fixed-wing-versus-rotary-wing-for-uav-mapping-applications. Retrieved at 11 Jan 2017
  19. 19.
    Chapman A (2016) Types of drones: multi-rotor vs fixed-wing vs single rotor vs hybrid VTOL. DRONE, 3. http://www.auav.com.au/articles/drone-types/. Retrieved at 12 Jan 2017
  20. 20.
    Adams SM, Friedland CJ (2011) A survey of unmanned aerial vehicle (UAV) usage for imagery collection in disaster research and management. Available at https://www.researchgate.net/publication/266465037
  21. 21.
    Doncieux S, Mouret JB, Muratet L, Meyer JA (2004) The ROBUR project: towards an autonomous flapping-wing animat. Proc J MicroDrones. https://pdfs.semanticscholar.org/e993/f2787820f2684ca2a14271e065d817e329a7.pdf. Retrieved at 13 January 2017
  22. 22.
    Michelson RC, Reece S (1998) Update on flapping wing micro air vehicle research-ongoing work to develop a flapping wing, crawling entomopter. In: 13th Bristol international RPV/UAV systems conference proceedings, vol 30. http://edge.rit.edu/content/P06007/public/websites/senior%20design/MAVSD/shane/References/Bristol_MAV_ornithopter_Paper.pdf. Retrieved at 13 Jan 2017
  23. 23.
    Watts AC, Ambrosia VG, Hinkley EA (2012) Unmanned aircraft systems in remote sensing and scientific research: classification and considerations of use. Remote Sens 4:1671–1692.  https://doi.org/10.3390/rs4061671CrossRefGoogle Scholar
  24. 24.
    Winnefeld JA, Kendall F (2011) U.S. unmanned systems integrated roadmap FY2011-2036. Department of Defence, United States of American. http://www.acq.osd.mil/sts/docs/Unmanned%20Systems%20Integrated%20Roadmap%20FY2011-2036.pdf. Retrieved at 13 Jan 2017
  25. 25.
    Liping O (2009) Brief introduction of UAVs. Bull Adv Technol Res 3(5):31–34. http://www.siat.cas.cn/xscbw/xsqk/200912/W020091208627529515062.pdf
  26. 26.
    Çuhadar İ, Dursun M (2016) Unmanned air vehicle systems data links. J Autom Control Eng 4(3):189–193.  https://doi.org/10.18178/joace.4.3.189-193CrossRefGoogle Scholar
  27. 27.
    Wolfgang WR (1999) UAV data-links: tasks, types, technologies and examples. Development and Operation of UAVs for Military and Civil Applications. http://oai.dtic.mil/oai/oai?verb=getRecord&metadataPrefix=html&identifier=ADP010757. Retrieved at 15 Jan 2017
  28. 28.
    Austin R (2011) Unmanned aircraft systems: UAVS design, development and deployment. Wiley, New York, p 54Google Scholar
  29. 29.
    Xu Y, Ou J, He H, Zhang X, Mills J (2016) Mosaicking of unmanned aerial vehicle imagery in the absence of camera poses. Remote Sens 8:204.  https://doi.org/10.3390/rs8030204CrossRefGoogle Scholar
  30. 30.
    Tiwari A, Dixit A (2015) Unmanned aerial vehicle and geospatial technology pushing the limits of development. Am J Eng Res (AJER), 4(1):16–21. http://www.ajer.org/papers/v4(01)/C0401016021.pdf
  31. 31.
    Stehr NJ (2015) Drones: the newest technology for precision agriculture. Nat Sci Educ 44:89–91.  https://doi.org/10.4195/nse2015.04.0772CrossRefGoogle Scholar
  32. 32.
    Malveaux C, Hall S, Price RR (2014) Using drones in agriculture: unmanned aerial systems for agricultural remote sensing applications. In: 2014 ASABE and CSBE/SCGAB annual international meeting sponsored by ASABE. https://elibrary.asabe.org/abstract.asp?aid=44960&t=2&redir=&redirType=. Retrieved at 25 Jan 2017
  33. 33.
    Leila HE, Alfonso TR, Austin J, Mac M (2015) Assessment of surface soil moisture using high-resolution multi-spectral imagery and artificial neural networks. Remote Sens 7:2627–2646.  https://doi.org/10.3390/rs70302627CrossRefGoogle Scholar
  34. 34.
    Sebastian O, Irene M, Klaus DP, Johannes BR (2012) Unmanned aerial vehicle (UAV) for monitoring soil erosion in Morocco. Remote Sens 4(11):3390–3416.  https://doi.org/10.3390/rs4113390CrossRefGoogle Scholar
  35. 35.
    Turner N, Houghton B, Taddeucci J, von der Lieth J, Kueppers U, Gaudin D, Ricci T, Kim K, Scalato P (2017) Drone peers into open volcanic vents. Earth Space Sci News 98.  https://doi.org/10.1029/2017EO082751
  36. 36.
    McFarlane DA, Lundberg J, van Rentergem G, Ramírez CJ (2017) An autonomous boat to investigate acidic crater lakes. Earth Space Sci News 98.  https://doi.org/10.1029/2017EO073409
  37. 37.
    Sholarin EA, Awange JL (2015) Environmental project management, principles, methodology, and processes. Springer International Publishing, BaselGoogle Scholar
  38. 38.
    Witman S (2017) Detecting gas leaks with autonomous underwater vehicles. Earth Space Sci News 98.  https://doi.org/10.1029/2017EO080597
  39. 39.
    Showstack R (2014) Robot explores under-ice habitats in the Arctic. Earth Space Sci News 95.  https://doi.org/10.1029/2014EO021181
  40. 40.
    Niethammer U, Rothmund S, Schwaderer U, Zeman J, Joswig W (2014) Open source image-processing tools for low-cost UAV-based landslide investigations. Int Arch Photogramm, Remote Sens Spat Inf Sci 38(1):161–166Google Scholar
  41. 41.
    Kwok R, Untersteiner N (2011) The thinning of Arctic sea ice. Phys Today 64(4):3641CrossRefGoogle Scholar
  42. 42.
    Romanovsky VE, Burgess M, Smith M, Yoshikawa K, Brown J (2002) Permafrost temperature records: indicators of climate change. Eos Trans AGU 83(50):589594CrossRefGoogle Scholar
  43. 43.
    de Boer G, Ivey MD, Schmid B, McFarlane S, Petty R (2016) Unmanned platforms monitor the Arctic atmosphere. Earth Space Sci News 97.  https://doi.org/10.1029/2016EO046441
  44. 44.
    Barlow J, Gilham J, Cofrã II (2017) Kinematic analysis of sea cliff stability using UAV photogrammetry. Int J Remote Sens 38(8–10):2464–2479.  https://doi.org/10.1080/01431161.2016.1275061CrossRefGoogle Scholar
  45. 45.
    Kornei K (2017) New technique reveals iceberg calving process. Earth Space Sci News 98.  https://doi.org/10.1029/2017EO072825
  46. 46.
    Jaime P, Michael KM, Brian MN, Serge AW, Lian PK (2014) Small drones for community-based forest monitoring: an assessment of their feasibility and potential in tropical areas. Forests 5(6):1481–1507.  https://doi.org/10.3390/f5061481CrossRefGoogle Scholar
  47. 47.
    Lisa C, Betschart S (2015) Christ the Redeemer Reconstructed in 3D. GIM Int Mag. https://www.gim-international.com/content/article/christ-the-redeemer-reconstructed-in-3d
  48. 48.
    Nex F, Remondino F (2014) UAV for 3D mapping applications: a review. Appl Geomat 6(1):1–15CrossRefGoogle Scholar
  49. 49.
    Moranduzzo T, Melgani F, Bazi Y, Alajlan N (2015) A fast object detector based on high-order gradients and Gaussian process regression for UAV images. Int J Remote Sens 36(10):2713–2733Google Scholar
  50. 50.
    Jung S, Ariyur KB (2017) Robustness for Scalable Autonomous UAV Operations. Int J Aeronaut Space Sci 18(4):767–779.  https://doi.org/10.5139/IJASS.2017.18.4.767CrossRefGoogle Scholar
  51. 51.
    Marçal ARS, Borges JS, Gomes JA, Pinto Da Costa JF (2005) Land cover update by supervised classification of segmented ASTER images. Int J Remote Sens 26(7):1347–1362. http://www.fc.up.pt/pessoas/andre.marcal/papers/IJRS_26_1347.pdf
  52. 52.
    Movia A, Beinat A, Crosilla F (2015) Comparison of unsupervised vegetation classification methods from VHR images after shadows removal by innovative algorithms. Int Arch Photogramm, Remote Sens Spat Inf Sci 40(7):1269–1276.  https://doi.org/10.5194/isprsarchives-XL-7-W3-1269-2015CrossRefGoogle Scholar
  53. 53.
    DeMario A, Lopez Pete, Plewka E, Wix R, Xia H, Zamora E, Gessler Dan, Yalin AP (2017) Water plume temperature measurements by an unmanned aerial system (UAS). Sensors 17:306.  https://doi.org/10.3390/s17020306CrossRefGoogle Scholar
  54. 54.
    Feng Q, Liu J, Gong J (2015) Urban flood mapping based on unmanned aerial vehicle remote sensing and random forest classifier—a case of Yuyao, China. Water 7:1437–1455.  https://doi.org/10.3390/w7041437CrossRefGoogle Scholar
  55. 55.
    Zhang W, Wu J (2014) To explore the UAV application in disaster prevention and reduction. Mech Mater 590:609–612.  https://doi.org/10.4028/www.scientific.net/AMM.590.609CrossRefGoogle Scholar
  56. 56.
    Yuan C, Zhang Y, Liu Z (2015) A survey on technologies for automatic forest fire monitoring, detection, and fighting using unmanned aerial vehicles and remote sensing techniques. Can J For Res 45(7):783–792.  https://doi.org/10.1139/cjfr-2014-0347CrossRefGoogle Scholar
  57. 57.
    Ferretti A, Moniti-Guarnieri A, Prati C, Rocca F (2007) InSAR principles: guidelines for SAR interferometry processing and interpretation. ESA Publications, AucklandGoogle Scholar
  58. 58.
    Fortuna J, Ferreira F, Gomes R, Ferreira S, Sousa J (2013) Using low cost open source UAVs for marine wild life monitoring - Field report. IFAC Proc Vol 46(30):291–295.  https://doi.org/10.3182/20131120-3-FR-4045.00055CrossRefGoogle Scholar
  59. 59.
    Rudol P, Doherty P (2008, March) Human body detection and geolocalization for UAV search and rescue missions using color and thermal imagery. In: Aerospace conference, 2008 IEEE, pp 1–8. https://www.ida.liu.se/divisions/aiics/publications/AEROCONF-2008-Human-Body-Detection.pdf
  60. 60.
    Cartier KMS (2017) Airborne laser spectroscopy system can map atmospheric gases. Earth Space Sci News 98.  https://doi.org/10.1029/2017EO078723
  61. 61.
    Clarke R, Moses LB (2014) The regulation of civilian drones impacts on public safety. Co Law & Secur Rev 30:263–285.  https://doi.org/10.1016/j.clsr.2014.03.007CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Spatial SciencesCurtin UniversityPerthAustralia
  2. 2.Department of Geospatial and Space TechnologyUniversity of Nairobi NairobiKenya

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