한국토양비료학회지 (Korean Journal of Soil Science and Fertilizer)

  • 제49권5호
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  • Pages.420-428
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  • 2016
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  • 0367-6315(pISSN)
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  • 2288-2162(eISSN)
한국토양비료학회 (Korean Society of Soil Science and Fertilizer)
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Estimation of Highland Kimchi Cabbage Growth using UAV NDVI and Agro-meteorological Factors

  • Na, Sang-Il (Climate Change and Agro-Ecology Division, National Institute of Agricultural Sciences, RDA) ;
  • Hong, Suk-Young (Soil and Fertilizer Management Division, National Institute of Agricultural Sciences, RDA) ;
  • Park, Chan-Won (Climate Change and Agro-Ecology Division, National Institute of Agricultural Sciences, RDA) ;
  • Kim, Ki-Deog (Highland Agriculture Research Center, National Institute of Crop Science, RDA) ;
  • Lee, Kyung-Do (Climate Change and Agro-Ecology Division, National Institute of Agricultural Sciences, RDA)
  • 투고 : 2016.06.16
  • 심사 : 2016.09.06
  • 발행 : 2016.10.31
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초록

For more than 50 years, satellite images have been used to monitor crop growth. Currently, unmanned aerial vehicle (UAV) imagery is being assessed for analyzing within field spatial variability for agricultural precision management, because UAV imagery may be acquired quickly during critical periods of rapid crop growth. This study refers to the derivation of growth estimating equation for highland Kimchi cabbage using UAV derived normalized difference vegetation index (NDVI) and agro-meteorological factors. Anbandeok area in Gangneung, Gangwon-do, Korea is one of main districts producing highland Kimchi cabbage. UAV imagery was taken in the Anbandeok ten times from early June to early September. Meanwhile, three plant growth parameters, plant height (P.H.), leaf length (L.L.) and outer leaf number (L.N.), were measured for about 40 plants (ten plants per plot) for each ground survey. Six agro-meteorological factors include average temperature; maximum temperature; minimum temperature; accumulated temperature; rainfall and irradiation during growth period. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, $NDVI_{UAV}$ and rainfall in the model explain 93% of the P.H. and L.L. with a root mean square error (RMSE) of 2.22, 1.90 cm. And $NDVI_{UAV}$ and accumulated temperature in the model explain 86% of the L.N. with a RMSE of 4.29. These lead to the result that the characteristics of variations in highland Kimchi cabbage growth according to $NDVI_{UAV}$ and other agro-meteorological factors were well reflected in the model.

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참고문헌

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피인용 문헌

  1. A Comparative Study of Image Classification Method to Classify Onion and Garlic Using Unmanned Aerial Vehicle (UAV) Imagery vol.49, pp.6, 2016, https://doi.org/10.7745/KJSSF.2016.49.6.743
  2. Application of Highland Kimchi Cabbage Status Map for Growth Monitoring based on Unmanned Aerial Vehicle vol.49, pp.5, 2016, https://doi.org/10.7745/KJSSF.2016.49.5.469
  3. Mapping the Spatial Distribution of IRG Growth Based on UAV vol.49, pp.5, 2016, https://doi.org/10.7745/KJSSF.2016.49.5.495
  4. Study on Reflectance and NDVI of Aerial Images using a Fixed-Wing UAV "Ebee" vol.49, pp.6, 2016, https://doi.org/10.7745/KJSSF.2016.49.6.731