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Abstract

Precision agriculture is now a topic that attracts many researchers due to the important of food security. In this topic, using the Unmmaed Aerial Vehicle (UAV) for pesticides, monitoring and mapping are under consideration. In addition, the combination of UAV and multi-spectral camera for imaging has been extensively used for vegetation mapping in the farm. This paper aims to introduce a method for mapping fields by using the multispectral camera mount on an UAV. Ariel images have been captured by multi-spectral Sentera camera mounted on Phantom 4 Pro. Successive images, including the NDVI spectral images and NDRE spectral images with GPS information, are the output of the Sentera camera. A combination of the UAV imaging and image processing techniques were used to create the rice planting area mapping. Agisoft software was used to create the Ortho-mosaic images of NDVI spectral image and NDRE spectral image. After that, digital maps contain information about Normalised Difference Vegetation Index (NDVI) and Normalised Difference Red-Edge (NDRE) were created. An observation area was created from the map to evaluate crop health by using these indices. This area included both the middle-stage rice field and the dragon fruits farm with cannels. The crop health is validated again by using the RGB aerial image. By comparing the maps and actual survey, the health of the rice fields is able to evaluate and improve the rice cultivation management. It seems that the NDRE value was the best indicator in visualizing the health of the rice field while the NDVI was better for the dragon fruits field. Utilizing these maps, field visits by farmers can be minimized and farmers can concentrate on the diseased location and give appropriate treatment.



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Article Details

Issue: Vol 5 No 1 (2022)
Page No.: 1400-1406
Published: Apr 30, 2022
Section: Research article
DOI: https://doi.org/10.32508/stdjet.v5i1.941

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Creative Commons License

Copyright: The Authors. This is an open access article distributed under the terms of the Creative Commons Attribution License CC-BY 4.0., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 How to Cite
Bui, V. H., Ngo, Q. H., Nguyen, H. C., & Luu, T. H. (2022). Unmanned aerial vehicle imaging application for crop health in rice field. Science & Technology Development Journal - Engineering and Technology, 5(1), 1400-1406. https://doi.org/https://doi.org/10.32508/stdjet.v5i1.941

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