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Utilization of Weather, Satellite and Drone Data to Detect Rice Blast Disease and Track its Propagation

벼 도열병 발생 탐지 및 확산 모니터링을 위한 기상자료, 위성영상, 드론영상의 공동 활용

  • Jae-Hyun Ryu (National Institute of Agricultural Sciences, Rural Development Administration) ;
  • Hoyong Ahn (National Institute of Agricultural Sciences, Rural Development Administration) ;
  • Kyung-Do Lee (National Institute of Agricultural Sciences, Rural Development Administration)
  • 류재현 (농촌진흥청 국립농업과학원 기후변화평가과) ;
  • 안호용 (농촌진흥청 국립농업과학원 기후변화평가과) ;
  • 이경도 (농촌진흥청 국립농업과학원 기후변화평가과)
  • Received : 2023.11.06
  • Accepted : 2023.12.06
  • Published : 2023.12.30

Abstract

The representative crop in the Republic of Korea, rice, is cultivated over extensive areas every year, which resulting in reduced resistance to pests and diseases. One of the major rice diseases, rice blast disease, can lead to a significant decrease in yields when it occurs on a large scale, necessitating early detection and effective control of rice blast disease. Drone-based crop monitoring techniques are valuable for detecting abnormal growth, but frequent image capture for potential rice blast disease occurrences can consume significant labor and resources. The purpose of this study is to early detect rice blast disease using remote sensing data, such as drone and satellite images, along with weather data. Satellite images was helpful in identifying rice cultivation fields. Effective detection of paddy fields was achieved by utilizing vegetation and water indices. Subsequently, air temperature, relative humidity, and number of rainy days were used to calculate the risk of rice blast disease occurrence. An increase in the risk of disease occurrence implies a higher likelihood of disease development, and drone measurements perform at this time. Spectral reflectance changes in the red and near-infrared wavelength regions were observed at the locations where rice blast disease occurred. Clusters with low vegetation index values were observed at locations where rice blast disease occurred, and the time series data for drone images allowed for tracking the spread of the disease from these points. Finally, drone images captured before harvesting was used to generate spatial information on the incidence of rice blast disease in each field.

우리나라 대표적인 식량 작물인 벼는 넓은 면적에서 장기간 재배되어 병해충에 대한 저항성이 낮아지고 있다. 대표적인 벼 질병 중 하나인 도열병이 대규모로 발생하면 수확량이 감소하여 조기에 병을 발견하고 방제를 하여야 한다. 하지만 농지 중심에서 도열병이 발생 하면 육안으로 병을 발견하기 어렵다. 드론을 이용한 작물 모니터링 기법은 생육 이상을 탐지하는데 유용하나 언제 발생할지 모르는 도열병 발생을 위해 빈번하게 촬영을 하는 것은 많은 인력과 비용이 소모된다. 본 연구의 목적은 드론, 위성과 같은 원격탐사 자료와 기상자료를 공동 활용하여 벼 도열병을 조기에 탐지하는 것이다. 위성영상은 벼 재배 필지를 추출하는데 유용하였다. 식생지수와 수분지수의 특성을 이용하여 관개가 된 논을 효과적으로 탐지하였다. 이후 기온, 상대습도, 강우일수 자료를 활용하여 벼 도열병 발생위험도를 계산하였다. 도열병 발생위험도가 증가하면 병이 발생할 가능성이 높아진다는 것을 의미하며, 해당 시점에 드론 관측을 수행하였다. 병이 발생한 지점, 병이 발생한 지점과 일반 벼가 혼재되어 있는 지점, 일반 벼 지점에서 분광반사도의 변화를 살펴보았으며, 갈색 병반을 가지는 도열병 특성상 적색과 근적외선 파장대에서 분광반사도의 변화가 급격한 것을 확인하였다. 도열병이 발생한 지점에서는 주변 지점에 비해 식생지수 값이 낮은 군집이 나타났으며, 시계열 드론 영상을 통해 해당 지점으로부터 벼 도열병 확산을 추적하였다. 최종적으로 수확 전 드론 영상을 활용하여 필지별 도열병 발생률에 대한 공간정보를 생산하였다.

Keywords

Acknowledgement

본 논문은 성과물은 농촌진흥청 연구사업(과제번호: RS-2022-RD010059)의 지원에 의해 이루어졌으며, 지원에 감사드립니다.

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