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Introduction

  • Ram AvtarEmail author
  • Teiji Watanabe
Chapter

Abstract

This chapter gives an introduction to the brief history, development, and state-of-the-art technology used in unmanned aerial vehicles (UAVs) with their application in the fields of agriculture and environment. The chapter also outlines the structure of book consisting of several chapters, each of which is authored by researchers working in their respective fields throughout their research career. The contributing authors are an amalgam of academicians, researchers, industry professionals, and users of such technology. The research areas considered in the case studies of this book cover diverse land from different countries and regions. This chapter summarizes the structure and approach toward the use of UAVs in an attempt to tackle the various challenges and issues faced in the use of UAVs.

Keywords

UAV Remote sensing Precision agriculture Drone Multi-sensor 3D model 

References

  1. Chiba T, Urayama T, Mochizuki T, Miura S, Naruke S (2019) Making a 3D model of a crater using UAV. For the future 2019 Asia air survey, pp 92–93Google Scholar
  2. Fahlstrom P, Gleason T (2012) Introduction to UAV systems. Wiley, HobokenGoogle Scholar
  3. Javernick L, Brasington J, Caruso B (2014) Modeling the topography of shallow braided rivers using structure-from-motion photogrammetry. Geomorphology 213:166–182CrossRefGoogle Scholar
  4. RSPO (2013) RSPO principles and criteria for sustainable palm oil production. https://rspo.org/key-documents/certification/rspo-principles-and-criteria
  5. Tokekar P et al (2016) Sensor planning for a symbiotic UAV and UGV system for precision agriculture. IEEE Trans Robot 32(6):1498–1511CrossRefGoogle Scholar
  6. Toro FG, Tsourdos A (2018) UAV-based remote sensing colume-2, special issue. MDPI sensors, ISSN:1424-8220Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Faculty of Environmental Earth ScienceHokkaido UniversitySapporoJapan

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