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Evaluation Of Current Policies on the use of Unmanned Aerial Vehicles in Indian Agriculture


Affiliations
1 Department of Soil and Crop Sciences, Texas A&M University, United States
2 Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Australia
3 Department of Agronomy, CCS Haryana Agricultural University, Hisar 125 004, Australia
 

Unmanned aerial vehicles (UAVs), commonly called ‘drones’, have enormous potential for technological advances in many sectors including agriculture. The recent revision in UAV policy by the Directorate General of Civil Aviation (DGCA), India, can impact the pace of research and development in machine vision capabilities in the country. Several other countries that have framed UAV policy previously, are continuously bringing changes to the existing framework to make it more user friendly. India can learn from those changes and bring out a comprehensive update to foster a broader application of these tools in agriculture. This policy review provides suggestions and solutions for increasing licensing centres, limiting UAV speed and weight for safer flights and including aerial pesticide applications in UAV permits to revolutionize the multibillion-dollar agriculture industry. This article has also examines the current UAV regulations in four other countries.

Keywords

DGCA, Drone Policy, Precision Agriculture, Remote Sensing, Unmanned Aerial Vehicles.
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  • Hunt Jr, E. R. and Daughtry, C. S., What good are unmanned aircraft systems for agricultural remote sensing and precision agriculture? Int. J. Remote Sens., 2018, 39, 5345–5376.

  • Zhang, C. and Kovacs, J. M., The application of small unmanned aerial systems for precision agriculture: a review. Precis. Agric., 2012, 13, 693–712.

  • Nebiker, S., Annen, A., Scherrer, M. and Oesch, D., A lightweight multispectral sensor for micro UAV – opportunities for very high resolution airborne remote sensing. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., 2008, 37, 1193–1199.

  • Gao, J. et al., Fusion of pixel and object-based features for weed mapping using unmanned aerial vehicle imagery. Int. J. Appl. Earth Obs. Geoinf., 2018, 67, 43–53.

  • Bai, G., Jenkins, S., Yuan, W., Graef, G. L. and Ge, Y., Fieldbased scoring of soybean iron deficiency chlorosis using RGB imaging and statistical learning. Front. Plant Sci., 2018, 9, 1002; doi:10.3389/fpls.2018.01002.

  • Hague, T., Marchant, J. A. and Tillett, N. D., Ground based sensing systems for autonomous agricultural vehicles. Comput. Electron. Agric., 2000, 25, 11–28.

  • BIS research, Global Unmanned Aerial Vehicles Market 2021, BIS Res., 2018; https://bisresearch.com/industry-report/global-unmanned-aerial-vehicles-market-2021.html (accessed on 18 September 2018).

  • ISRO, Agriculture and Soil. Indian Space Research Organisation, India, 2019; https://www.isro.gov.in/earth-observation/agriculture-and-soils (accessed on 6 March 2019).

  • Parihar, J. S. and Oza, M. P., FASAL: an integrated approach for crop assessment and production forecasting. Agriculture and Hydrology Applications of Remote Sensing. In Proceedings of SPIE, Goa, India, 2006, 6411, 641101–641113; doi:10.1117/ 12.713157.

  • MNCFC, Forecasting Agricultural output using Space, Agrometeorology and Land based observations. Mahalanobis National Crop Forecast Centre, India, 2019; http://www.ncfc.gov.in/about_fasal.html (accessed on 6 March 2019).

  • DGCA, Civil Aviation Requirements. Director General of Civil Aviation, India, Policy F. No. 05-13/2014-AED, 2018, vol. 4, pp. 1–24; http://www.dgca.nic.in (accessed on 10 September 2018).

  • Sundqvist, L., Cellular controlled drone experiment: evaluation of network requirements. M Sc thesis, Aalto University, Helsinki, Finland, 2015, pp. 1–61.

  • Chen, S., The regulation of the recreational use of ‘Drones’ for aerial photography and videography: comparing Singapore’s unmanned aircraft act with other legislation, Singapore Law Rev., 2015, 33, 55–92.

  • Siebert, S. and Teizer, J., Mobile 3D mapping for surveying earthwork projects using an unmanned aerial vehicle (UAV) system. Automat. Constr., 2014, 41, 1–14.

  • Shakhatreh, H. et al., Unmanned aerial vehicles: a survey on civil applications and key research challenges. arXiv Preprint, 2018, arXiv:1805.00881.

  • Kaler, A. S., Ray, J. D., Schapaugh, W. T., Asebedo, A. R., King, C. A., Gbur, E. E. and Purcell, L. C., Association mapping identifies loci for canopy temperature under drought in diverse soybean genotypes. Euphytica, 2018, 214, 135.

  • Watts, A. C., Ambrosia, V. G. and Hinkley, E. A., Unmanned aircraft systems in remote sensing and scientific research: classification and considerations of use. Remote Sens., 2012, 4, 1671–1692.

  • CAAS, Regulations on unmanned aircraft operations. Civil Aviation Authority of Singapore, 2018; https://www.caas.gov.sg/ (accessed on 18 September 2018).

  • CASA, Flying drones/automated aircraft in Australia. Civil Aviation Safety Authority, Australia, 2018; https://www.casa.gov.au (accessed on 10 September 2018).

  • FAA, Unmanned Aircraft Systems, Federal Aviation Administration, USA, 2018; https://www.faa.gov/uas/ (accessed on 10 September 2018).

  • Hardin, P. J. and Hardin, T. J., Small-scale remotely piloted vehicles in environmental research. Geogr. Compass., 2010, 4, 1297–1311.

  • CAAC, Unmanned Aerial Vehicle Regulations. Civil Aviation Administration of China, 2018; http://www.caac.gov.cn/en/ (accessed on 10 September 2018).

  • Anonymous, Commercial Drone Industry trends. Drone Deploy, 2017; https://blog.dronedeploy.com/commercial-drone-industry-trends-aae2010ff349 (accessed on 27 September 2018).

  • Israelsen, J., Beall, M., Bareiss, D., Stuart, D., Keeney, E. and van den Berg, J., Automatic collision avoidance for manually teleoperated unmanned aerial vehicles. In Proceedings of Robotics and Automation (ICRA), IEEE International Conference, Hong Kong, China, 2014, IEEE 6638–6643.

  • DJI, 5-Direction of Obstacle Detection, Dà-Jiāng Innovations (DJI), 2018; https://www.dji.com/phantom-4-pro (accessed on 25 September 2018).

  • Raczynski, R. J., Accuracy analysis of products obtained from UAV-borne photogrammetry influenced by various flight parameters, Master’s thesis, Norwegian University of Science and Technology, Trondheim, 2017; https://brage.bibsys.no/xmlui/handle/11250/2452453.


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  • Evaluation Of Current Policies on the use of Unmanned Aerial Vehicles in Indian Agriculture

Abstract Views: 421  |  PDF Views: 132

Authors

Vijay Singh
Department of Soil and Crop Sciences, Texas A&M University, United States
Muthukumar Bagavathiannan
Department of Soil and Crop Sciences, Texas A&M University, United States
Bhagirath Singh Chauhan
Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Australia
Samar Singh
Department of Agronomy, CCS Haryana Agricultural University, Hisar 125 004, Australia

Abstract


Unmanned aerial vehicles (UAVs), commonly called ‘drones’, have enormous potential for technological advances in many sectors including agriculture. The recent revision in UAV policy by the Directorate General of Civil Aviation (DGCA), India, can impact the pace of research and development in machine vision capabilities in the country. Several other countries that have framed UAV policy previously, are continuously bringing changes to the existing framework to make it more user friendly. India can learn from those changes and bring out a comprehensive update to foster a broader application of these tools in agriculture. This policy review provides suggestions and solutions for increasing licensing centres, limiting UAV speed and weight for safer flights and including aerial pesticide applications in UAV permits to revolutionize the multibillion-dollar agriculture industry. This article has also examines the current UAV regulations in four other countries.

Keywords


DGCA, Drone Policy, Precision Agriculture, Remote Sensing, Unmanned Aerial Vehicles.

References





DOI: https://doi.org/10.18520/cs%2Fv117%2Fi1%2F25-29