Refine your search
Collections
Co-Authors
Journals
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Chauhan, Bhagirath Singh
- Issues and Strategies for Rice Residue Management to Unravel Winter Smog in North India
Abstract Views :271 |
PDF Views:80
Authors
Affiliations
1 ICAR, Agricultural Technology Application Research Institute, Ludhiana 141 004, IN
2 Punjab Agricultural University, Ludhiana 141 004, IN
3 The Centre for Crop Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Gatton, Queensland 4343, AU
1 ICAR, Agricultural Technology Application Research Institute, Ludhiana 141 004, IN
2 Punjab Agricultural University, Ludhiana 141 004, IN
3 The Centre for Crop Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Gatton, Queensland 4343, AU
Source
Current Science, Vol 114, No 12 (2018), Pagination: 2419-2419Abstract
Rice is the most popular kharif food crop grown in North India. In Punjab, 75–80% of area under rice is machine-harvested and based on harvest index, 18–20 million tonnes of rice straw production is estimated. Approximately 95% of paddy straw and 25% of wheat straw are burnt every year in Punjab, making the state the major culprit for greenhouse gas emissions. The emissions from wheat crop residues in Punjab are relatively low compared to those from paddy fields. Residue burning in agricultural fields of North India is a major source of smoke, smog and particulate pollution.Full Text
References
- Gupta, P. K. et al., Curr. Sci., 2004, 87(12), 1713–1717.
- Evaluation Of Current Policies on the use of Unmanned Aerial Vehicles in Indian Agriculture
Abstract Views :261 |
PDF Views:78
Authors
Affiliations
1 Department of Soil and Crop Sciences, Texas A&M University, US
2 Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, AU
3 Department of Agronomy, CCS Haryana Agricultural University, Hisar 125 004, AU
1 Department of Soil and Crop Sciences, Texas A&M University, US
2 Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, AU
3 Department of Agronomy, CCS Haryana Agricultural University, Hisar 125 004, AU
Source
Current Science, Vol 117, No 1 (2019), Pagination: 25-29Abstract
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.Full Text
References
- 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.