Peach flower monitoring using aerial multispectral imaging

Journal of Imaging

Volumn 3, Issue 1, 2017, Pages

  Horton, Ryan ^a   Cano, Esteban ^a   Bulanon, Duke ^a   Fallahi, Esmaeil ^b  

^a NORTHWEST NAZARENE UNIVERSITY   (United States)

^b UNIVERSITY OF IDAHO   (United States)

Author keywords

Blossoms; Digital image processing; Machine vision; Peaches; Unmanned aerial system

Indexed keywords

ANTENNAS; COMPUTER VISION; CROPS; CULTIVATION; FORESTRY; FRUITS; IMAGE ENHANCEMENT; IMAGE SEGMENTATION; INFRARED DEVICES; TREES (MATHEMATICS);

BLOSSOM; CROP PRODUCTION; FRUIT TREES; GROWING SEASON; IMAGE PROCESSING ALGORITHM; MACHINE-VISION; MONITORING AND ASSESSMENT; MULTISPECTRAL IMAGING; PEACH; UNMANNED AERIAL SYSTEMS;

ORCHARDS;

EID: 85034746913     PISSN: None     EISSN: 2313433X     Source Type: Journal    
DOI: 10.3390/jimaging3010002     Document Type: Article

References (16)

1. USDA-National Agriculture Statistics Service. State Agriculture Overview (Idaho). Available online: https://www.nass.usda.gov/Quick-Stats/Ag-Overview/stateOverview.php?state=IDAHO (accessed on 30 April 2016).
2. Downey, D.R.; Ehsani, K.; Giles, S.; Haneklaus, D.; Karimi, K.; Panten, F.; Pierce, E.; Schnug, D.C.; Slaughter, S.; Upadhyaya, D. Advanced Engineering Systems for Specialty Crops: A Review of Precision Agriculture for Water, Chemical, and Nutrient Application, and Yield Monitoring. Landbauforsch. - VTI Agric. For. Res. 2010, 340, 1-88.
3. Lee, W.S.; Alchanatis, V.; Yang, C.; Hirafuji, M.; Moshou, D.; Li, C. Sensing technologies for precision specialty crop production. Comput. Electron. Agric. 2010, 74, 2-33. [CrossRef]
4. Pajares, G. Overview and current status of remote sensing applications based on Unmanned Aerial Vehicles (UAVs). Photogramm. Eng. Remote Sens. 2015, 81, 281-329. [CrossRef]
5. Johnson, A.K.L.; Kinsey-Henderson, A.E. Satellite-based remote sensing for monitoring Baath land use in sugar industry. Proc. Aust. Soc. Sugar Cane Technol. 1997, 19, 237-245.
6. Li, Z.; Liu, Y.; Walker, R.; Hayward, R.; Zhang, J. Towards automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved Hough transform. Mach. Vis. Appl. 2010, 21, 677-686. [CrossRef]
7. Coifman, B.; McCord, M.; Mishalani, R.G.; Iswalt, M.; Ji, Y. Roadway traffic monitoring from an unmanned aerial vehicle. IEEE Proc. Intell. Trans. Syst. 2006, 153, 11-20. [CrossRef]
8. Ro, K.; Oh, J.S.; Dong, L. Lessons learned: Application of small UAV for urban highway traffic monitoring. In Proceedings of the 45th AIAA Aerospace Sciences Meeting and Exhibit, Reno, NV, USA, 8-11 January 2007; pp. 2007-2596.
9. Boon, W.A.; Greenfield, R.; Tesfamichael, S.Wetland Assessment Using Unmanned Aerial Vehicle (UAV) Photgrammetry. In Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXIII ISPRS Congress, Prague, Czech Republic, 12-19 July 2016.
10. Bulanon, D.M.; Horton, M.; Salvador, P.; Fallahi, E. Apple Orchard Monitoring Using Aerial Multispectral Imaging; ASABE Paper No. 1913165; American Society of Agricultural and Biological Engineers (ASABE): St. Joseph, MI, USA, 2014.
11. Bulanon, D.M.; Lonai, J.; Skovgard, H.; Fallahi, E. Evaluation of different irrigation methods for an apple orchard using an aerial imaging system. ISPRS Int. J. Geo-Inf. 2016, 5, 79. [CrossRef]
12. Fujii, J.A.; Kennedy, R.A. Seasonal changes in the photosynthetic rate in apple trees - A comparison between fruiting and nonfruiting trees. Plant Pysiol. 1985, 78, 519-524. [CrossRef]
13. Aggelopoulou, K.D.; Wulfsohn, D.; Fountas, S.; Gemtos, T.A.; Nanos, G.D.; Blackmore, S. Spatial variation in yield and quality in a small apple orchard. Precis. Agric. 2010, 11, 538-556. [CrossRef]
14. Da-Jiang Innovations (DJI). Available online: http://www.dji.com/products/phantom (accessed on 30 December 2016).
15. DroneDeploy. Available online: https://www.dronedeploy.com/ (accessed on 30 December 2016).
16. Gonzalez, R.C.; Woods, R.E. Digital Image Processing, 3rd ed.; Pearson: New York, NY, USA, 2007.