Study on Fire Blight Forecasting Using fixed-Wing Drone

Hyun-Jung  Kim1   Tae-Hwan  Kang2,*   

1Department of Biosystems Engineering, Chungbuk National University, Cheongju, Republic of Korea
2Major in Bio-Industry Mechanical Engineering, Kongju National University, Yesan, Republic of Korea

Abstract

The fire-blight due to its extremely strong infectivity, once the infection is confirmed in the orchard, all of the tress located within 100 m must be destroyed and then the orchard is prohibited to cultivate the Rosaceae trees for 5 years. In South Korea, since fire-blight was confirmed for the first time in Ansung area in 2015, the infection is still being detected every year. Traditional methods to observe fire-blight requires a lot of costs and time, and also the pathogen can be transmitted by the inspectors from the infected orchard to the normal one. Thus, it is necessary to develop a remote, unmanned monitoring system for fire-blight to prevent the communication of fire-blight. Using a multi-spectral camera with 4 spectral bands (red, green, blue, red-edge, and NIR) attached on a fixed-wing drone (senseFly-eBee SQ). As a result, it is judged as impossible to detect the pear tree from the outbreak of fire blight in the growth index NDVI, reflected light NIR, and Red-edge areas because of the low spatial resolution (6 cm/pixel) and early fire blight, which spread throughout the pear trees that was photographed when some of the previous leaves showed signs of disease. In the future that low-altitude and close-up shots with high spatial resolution will be necessary for highly reliable judgements of fire blight in the future.

Figures & Tables

Fig. 1. Fixed-wing drones and sensors for data video acquisition.