UAV Low-Altitude Remote Sensing for Precision Weed Management

Weed Technology

Volumn 32, Issue 1, 2018, Pages 2-6

  Huang, Yanbo ^a   Reddy, Krishna N ^a   Fletcher, Reginald S ^a   Pennington, Dean ^b  

^a AGRICULTURAL RESEARCH SERVICE   (United States)

^b Yazoo Mississippi Delta Joint Water Management District   (United States)

Author keywords

Glyphosate Resistant weeds; Low Altitude remote sensing; precision agriculture; unmanned aerial vehicle

Indexed keywords

AGRICULTURAL LAND; CHEMICAL CONTROL; GLYPHOSATE; PESTICIDE RESISTANCE; PRECISION AGRICULTURE; REMOTE SENSING; UNMANNED VEHICLE; WEED;

EID: 85042220917     PISSN: 0890037X     EISSN: None     Source Type: Journal    
DOI: 10.1017/wet.2017.89     Document Type: Conference Paper

References (36)

1. Barber T (2017) Damage Reports from Dicamba Pouring in Over the Last 2 Weeks. Fayetteville, AK: University of Arkansas. http://www.arkansas-crops. com/2017/06/12/reports-dicamba-pouring. Accessed September 6, 2017
2. Bongiovanni R, Lowenberg-Deboer J (2004) Precision agriculture and sustainability. Precis Agric 5:359-387
3. De Castro AI, Jurado-Expósito M, Penã-Barragán JM, López-Granados F (2012) Airborne multi-spectral imagery for mapping cruciferous weeds in cereal and legume crops. Precis Agric 13:302-321
4. [FAA] Federal Aviation Administration (2016) Summary of Small Unmanned Aircraft Rule (Part 107). FAA News. Washington DC: FAA. https://www. faa.gov/uas/media/Part-107-Summary.pdf. Accessed May 30, 2017.
5. Freeman PK, Freeland RS (2015) Agricultural UAVs in the U.S.: Potential, policy, and hype. Remote Sensing Applications: Society and Environment 2, 35-43
6. Green JM (2014) Current state of herbicides in herbicide-resistant crops. Pest Manag Sci 70:1351-1357
7. Harris T (2014) UAV Potential for Ranchers. http://farmprogress.com/blogsuav-potential-ranchers-8167. Accessed May 30, 2017
8. Heap I (2017) The International Survey of Herbicide Resistant Weeds. http://www.weedscience.org. Accessed May 30, 2017
9. Herwitz S, Johnson L, Dunagan S, Higgins R, Sullivan D, Zheng J, Lobitz BM, Leung JG, Gallmeyer BA, Aoyagi M, Slye RE, Brass JA (2004) Imaging from an unmanned aerial vehicle: Agricultural surveillance and decision support. Comput Electron Agric 44:49-61
10. Huang Y, Howard B, Pennington D, Reddy KN, Thomson SJ (2016) Assessing soybean injury from dicamba using RGB and CIR images acquired on small UAVs. Proceedings of the 13th International Conference on Precision Agriculture poster. St Louis, MO, July 31-August 4, 2016
11. Huang Y, Reddy KN (2015) Unmanned aerial vehicles: A unique platform for low-altitude remote sensing for crop management. Pages 185-192 in Rao AN, Yaduraju NT, eds. Weed Science for Sustainable Agriculture, Environment and Biodiversity: Proceedings of the Plenary and Lead Papers of the 25th Asian-Pacific Weed Science Society Conference. Madhya Pradesh, India: Indian Society of Weed Science
12. Huang Y, Reddy KN, Thomson SJ, Yao H (2015) Assessment of soybean injury from glyphosate using airborne multispectral remote sensing. Pest Manag Sci 71:545-552
13. Huang Y, Thomson SJ (2015) Remote sensing for cotton farming. Pages 1-26 in Fang DD and Percy RG eds. Cotton. 2nd edn, Agronomy Monograph 57. Madison, WI: American Society of Agronomy, Crop Science Society of America, and Soil Society of America
14. Huang Y, Thomson SJ, Hoffman WC, Lan Y, Fritz BK (2013) Development and prospect of unmanned aerial vehicles for agricultural production management. Int J Agric Biol Eng 6:1-10
15. Huang Y, Thomson SJ, Ortiz BV, Reddy KN, Ding W, Zablotowicz RM, Bright JR Jr (2010) Airborne remote sensing assessment of the damage to cotton caused by spray drift from aerially applied glyphosate through spray deposition measurements. Biosyst Eng 7:212-220
16. Hung C, Xu Z, Sukkarieh S (2014) Feature learning based approach for weed classification using high resolution aerial images from a digital camera mounted on a UAV. Remote Sens 6:12037-12054
17. Jha P, Norsworthy JK (2009) Soybean canopy and tillage effects on emergence of Palmer amaranth (Amaranthus palmeri) from a natural seed bank. Weed Sci 57:644-651
18. Lee MA, Huang Y, Nandula VK, Reddy KN (2014) Differentiating glyphosateresistant and glyphosate-sensitive Italian ryegrass using hyperspectral imagery. Page 91080B in Kim MS, Chao K, eds. SPIE Proceedings 9108: Sensing for Agriculture and Food Quality and Safety VI. Bellingham, WA: SPIE.
19. Mesas-Carrascosa FJ, Torres-Sánchez JT, Clavero-Rumbao I, Garciá-Ferrer A, Penã JM, Borra-Serrano I, López-Grandos F (2015) Assessing optimal flight parameters for generating accurate multispectral orthomosaicks by UAV to support site-specific crop management. Remote Sens 7:12793-12814
20. National Research Council (1997) Precision Agriculture in the 21st Century. Washington, DC: National Academies Press. 149 p
21. Penã JM, Torres-Sánchez J, de Castro AI, Kelly M, López-Granados F (2013) Weed mapping in early-season maize fields using object-based analysis of unmanned aerial vehicle (UAV) images. PLoS ONE 8:e77151
22. Penã JM, Torres-Sanchez J, Serrano-Perez A, de Castro AI, Lopez-Granados F (2015) Quantifying efficacy and limits of unmanned aerial vehicle (UAV) technology for weed seedling detection as affected by sensor resolution. Sensors 15:5609-5626
23. Pinter PJ, Hatfield JL, Schepers JS, Barnes EM, Moran MS (2003) Remote sensing for crop management. Photogramm Eng Remote Sens 69:647-664
24. Rasmussen J, Nielsen J, Garcia-Ruiz F, Christensen S, Streibig JC (2013) Potential uses of small unmanned aircraft systems (UAS) in weed research. Weed Res 53:242-248
25. Reddy K, Huang Y, Lee MA, Nandula VK, Fletcher RS, Thomson SJ, Zhao F (2014) Glyphosate-resistant and glyphosate-susceptible Palmer amaranth (Amaranthus palmeri S. Wats.): Hyperspectral reflectance properties of plants and potential for classification. Pest Manag Sci 70:1910-1917
26. Reddy KN, Jha P (2016) Herbicide-resistant weeds: Management strategies and upcoming technologies. Indian J Weed Sci 48:108-111
27. Rouse JW, Haas RH, Schell JA, Deering DW (1973). Monitoring vegetation systems in the great plain with ERTS. Pages 309-317 in Proceedings of the 3rd ERTS Symposium. NASA SP-351. Vol. 1. Washington, DC: NASA
28. Ruzgiene B, Aksa-Mitauskas C (2013) The use of UAV systems for mapping of built up area. ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 1:349-353
29. Shaw DR (2005) Remote sensing and site-specific weed management. Front Ecol Environ 3:526-532
30. Steckel L (2017) No One Reason for "Frustrating" Dicamba Issue. Knoxville, TN: University of Tennessee. http://www.cottongrower.com/opinion/noone-reason-for-frustrating-dicamba-issue. Accessed September 6, 2017
31. Steckel LE (2007) The dioecious Amaranthus spp.: Here to stay. Weed Technol 21:567-570
32. Torres-Sánchez J, López-Granados F, De Castro AI, Penã-Barragán JM (2013) Configuration and specifications of an unmanned aerial vehicle (UAV) for early site specific weed management. PLoS ONE 8:e58210
33. Ward M, Webster TM, Steckel LE (2013) Palmer amaranth (Amaranthus palmeri): A review. Weed Technol 27:12-27
34. Warren G, Metternicht G (2005) Agricultural applications of high-resolution digital multispectral imagery: Evaluating within-field spatial variability of canola (Brassica napus) in Western Australia. Photogramm Eng Remote Sens 71:595-602
35. Yano IH, Alves JR, Santiago WE, Mederos BJT (2016) Identification of weeds in sugarcane fields through images taken by UAV and random forest classifier. IFAC-PapersOnLine 49:415-420
36. Yao H, Huang Y (2013) Remote sensing applications to precision farming. Pages 333-352 in Wang G, Weng Q, eds. Remote Sensing of Natural Resources. Boca Raton, FL: CRC