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2019 Vol.61, Issue 4
Estimation of Rice Grain Yield Distribution Using UAV Imagery

무인비행체 영상을 활용한 벼 수량 분포 추정

KyungDo Leea
,
HoYong Anb
,
ChanWon Parkc
,
KyuHo Sod
,
SangIl Nae†
,
SuYong Jangf
이 경도a
,
안 호용b
,
박 찬원c
,
소 규호d
,
나 상일e†
,
장 수용f
aResearcher, National Institute of Agricultural Science, Rural Development Administration
bResearcher, National Institute of Agricultural Science, Rural Development Administration
cResearcher, National Institute of Agricultural Science, Rural Development Administration
dResearcher, National Institute of Agricultural Science, Rural Development Administration
eResearcher, National Institute of Agricultural Science, Rural Development Administration
fCEO, Hanmaeum Farming Cooperation
a농촌진흥청 국립농업과학원 연구원
b농촌진흥청 국립농업과학원 연구원
c농촌진흥청 국립농업과학원 연구원
d농촌진흥청 국립농업과학원 연구원
e농촌진흥청 국립농업과학원 연구원
f한마음농업협력 대표이사
† Corresponding author Tel.: +82-63-238-2513 Fax.: +82-63-238-3823 E-mail: sangil917@korea.kr
2019. pp. 1-10
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Abstract

Unmanned aerial vehicle(UAV) can acquire images with lower cost than conventional manned aircraft and commercial satellites. It has the advantage of acquiring high-resolution aerial images covering in the field area more than 50 ha. The purposes of this study is to develop the rice grain yield distribution using UAV. In order to develop a technology for estimating the rice yield using UAV images, time series UAV aerial images were taken at the paddy fields and the data were compared with the rice yield of the harvesting area for two rice varieties(Singdongjin, Dongjinchal). Correlations between the vegetation indices and rice yield were ranged from 0.8 to 0.95 in booting period. Accordingly, rice yield was estimated using UAV-derived vegetation indices(R2=0.70 in Sindongjin, R2=0.92 in Donjinchal). It means that the rice yield estimation using UAV imagery can provide less cost and higher accuracy than other methods using combine with yield monitoring system and satellite imagery. In the future, it will be necessary to study a variety of information convergence and integration systems such as image, weather, and soil for efficient use of these information, along with research on preparing management practice work standards such as pest control and nutrient use based on UAV image information.

Keywords
UAV
rice
yield
vegetation index
remote sensing
References

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Information
  • Publisher :The Korean Society of Agricultural Engineers
  • Publisher(Ko) :한국농공학회
  • Journal Title :Journal of Korean Society of Agricultural Engineers
  • Journal Title(Ko) :한국농공학회논문집
  • Volume : 61
  • No :4
  • Pages :1-10
  • Received Date : 2019-04-30
  • Revised Date : 2019-05-14
  • Accepted Date : 2019-05-20
  • DOI :https://doi.org/10.5389/KSAE.2019.61.4.001
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