Korean Journal of Soil Science and Fertilizer (한국토양비료학회지)

Korean Society of Soil Science and Fertilizer (한국토양비료학회)
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A Comparative Study of Image Classification Method to Classify Onion and Garlic Using Unmanned Aerial Vehicle (UAV) Imagery

  • Lee, Kyung-Do (Department of Agricultural Environment, National Institute of Agricultural Sciences, RDA) ;
  • Lee, Ye-Eun (Department of Agricultural Environment, National Institute of Agricultural Sciences, RDA) ;
  • Park, Chan-Won (Department of Agricultural Environment, National Institute of Agricultural Sciences, RDA) ;
  • Na, Sang-Il (Department of Agricultural Environment, National Institute of Agricultural Sciences, RDA)
  • Received : 2016.10.24
  • Accepted : 2016.11.15
  • Published : 2016.12.31
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Abstract

Recently, usage of UAV (Unmanned Aerial Vehicle) has increased in agricultural part. This study was conducted to classify onion and garlic using supervised classification of a fixed-wing UAV (Model : Ebee) images for evaluation of possibility about estimation of onion and garlic cultivation area using UAV images. Aerial images were obtained 11~12 times from study sites in Changryeng-gun and Hapcheon-gun during farming season from 2015 to 2016. The result for accuracy in onion and garlic image classification by R-G-B and R-G-NIR images showed highest Kappa coefficients for the maximum likelihood method. The result for accuracy in onion and garlic classification showed high Kappa coefficients of 0.75~0.97 from DOY 105 to DOY 141, implying that UAV images could be used to estimate onion and garlic cultivation area.

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References

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