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Scientific paper - Original scientific paper
THE EVALUATION OF THE RGB AND MULTISPECTRAL CAMERA ON THE UNMANNED AERIAL VEHICLE (UAV) FOR THE MACHINE LEARNING CLASSIFICATION OF MAIZE
Poljoprivreda, 28 (2022), 2; 74-80. https://doi.org/10.18047/poljo.28.2.10
Jurišić, Mladen; Radočaj, Dorijan; Plaščak, Ivan; Galić Subašić, Daria; Petrović, Davor

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Jurišić, M., Radočaj, D., Plaščak, I., Galić Subašić, D. & Petrović, D. (2022). THE EVALUATION OF THE RGB AND MULTISPECTRAL CAMERA ON THE UNMANNED AERIAL VEHICLE (UAV) FOR THE MACHINE LEARNING CLASSIFICATION OF MAIZE. Poljoprivreda, 28. (2), 74-80. doi: 10.18047/poljo.28.2.10

Jurišić, Mladen, et al. "THE EVALUATION OF THE RGB AND MULTISPECTRAL CAMERA ON THE UNMANNED AERIAL VEHICLE (UAV) FOR THE MACHINE LEARNING CLASSIFICATION OF MAIZE." Poljoprivreda, vol. 28, no. 2, 2022, pp. 74-80. https://doi.org/10.18047/poljo.28.2.10

Jurišić, Mladen, Dorijan Radočaj, Ivan Plaščak, Daria Galić Subašić and Davor Petrović. "THE EVALUATION OF THE RGB AND MULTISPECTRAL CAMERA ON THE UNMANNED AERIAL VEHICLE (UAV) FOR THE MACHINE LEARNING CLASSIFICATION OF MAIZE." Poljoprivreda 28, no. 2 (2022): 74-80. https://doi.org/10.18047/poljo.28.2.10

Jurišić, M., et al. (2022) 'THE EVALUATION OF THE RGB AND MULTISPECTRAL CAMERA ON THE UNMANNED AERIAL VEHICLE (UAV) FOR THE MACHINE LEARNING CLASSIFICATION OF MAIZE', Poljoprivreda, 28(2), pp. 74-80. doi: 10.18047/poljo.28.2.10

Jurišić M, Radočaj D, Plaščak I, Galić Subašić D, Petrović D. THE EVALUATION OF THE RGB AND MULTISPECTRAL CAMERA ON THE UNMANNED AERIAL VEHICLE (UAV) FOR THE MACHINE LEARNING CLASSIFICATION OF MAIZE. Poljoprivreda [Internet]. 2022 December 20 [cited 2024 July 12];28(2):74-80. doi: 10.18047/poljo.28.2.10

M. Jurišić, D. Radočaj, I. Plaščak, D. Galić Subašić and D. Petrović, "THE EVALUATION OF THE RGB AND MULTISPECTRAL CAMERA ON THE UNMANNED AERIAL VEHICLE (UAV) FOR THE MACHINE LEARNING CLASSIFICATION OF MAIZE", Poljoprivreda, vol. 28, no. 2, pp. 74-80, December 2022. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:151:739593. [Accessed: 12 July 2024]

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Metadata
Title (english)THE EVALUATION OF THE RGB AND MULTISPECTRAL CAMERA ON THE UNMANNED AERIAL VEHICLE (UAV) FOR THE MACHINE LEARNING CLASSIFICATION OF MAIZE
AuthorMladen Jurišić
AuthorDorijan Radočaj
AuthorIvan Plaščak
AuthorDaria Galić Subašić
AuthorDavor Petrović
Author's institutionJosip Juraj Strossmayer University of Osijek
Faculty of Agrobiotechnical Sciences Osijek
(Department of Agricultural Engineering and Renewable Energy Resources)
Scientific / art field,
discipline and subdiscipline		BIOTECHNICAL SCIENCES
Agronomy
Agricultural Engineering and Technology
Abstract (english)
This study investigated a crop and soil classification applying the Random Forest machine learning algorithm based on the red-green-blue (RGB) and multispectral sensor imaging deploying an unmanned aerial vehicle (UAV). The study area covered two 10 x 10 m subsets of a maize-sown agricultural parcel near Koška. The highest overall accuracy was obtained in the combination of the red edge (RE), near-infrared (NIR), and normalized difference vegetation index (NDVI) in both subsets, with a 99.8% and 91.8% overall accuracy, respectively. The conducted analysis proved that the RGB camera obtained sufficient accuracy and was an acceptable solution to the soil and vegetation classification. Additionally, a multispectral camera and spectral analysis allowed for a more detailed analysis, primarily of the spectrally similar areas. Thus, this procedure represents a basis for both the crop density calculation and weed detection while deploying an unmanned aerial vehicle. To ensure crop classification effectiveness in practical application, it is necessary to further integrate the weed classes in the current vegetation class and separate them into crop and weed classes.
Keywords (english)
Languageenglish
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review - domestic
Publication versionPublished version
Journal titlePoljoprivreda
Numberingvol. 28, no. 2, pp. 74-80
p-ISSN1330-7142
e-ISSN1848-8080
DOIhttps://doi.org/10.18047/poljo.28.2.10
URN:NBNurn:nbn:hr:151:739593
Publication2022-12-20
Document URLhttps://hrcak.srce.hr/289119
Type of resourceText
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2024-05-08 11:00:48