Korean Journal of Remote Sensing (대한원격탐사학회지)

Korean Society of Remote Sensing (대한원격탐사학회)
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Development of Garlic & Onion Yield Prediction Model on Major Cultivation Regions Considering MODIS NDVI and Meteorological Elements

MODIS NDVI와 기상요인을 고려한 마늘·양파 주산단지 단수예측 모형 개발

  • Na, Sang-il (National Institute of Agricultural Sciences, Rural Development Administration) ;
  • Park, Chan-won (National Institute of Agricultural Sciences, Rural Development Administration) ;
  • So, Kyu-ho (National Institute of Agricultural Sciences, Rural Development Administration) ;
  • Park, Jae-moon (National Institute of Agricultural Sciences, Rural Development Administration) ;
  • Lee, Kyung-do (National Institute of Agricultural Sciences, Rural Development Administration)
  • 나상일 (농촌진흥청 국립농업과학원) ;
  • 박찬원 (농촌진흥청 국립농업과학원) ;
  • 소규호 (농촌진흥청 국립농업과학원) ;
  • 박재문 (농촌진흥청 국립농업과학원) ;
  • 이경도 (농촌진흥청 국립농업과학원)
  • Received : 2017.06.30
  • Accepted : 2017.10.17
  • Published : 2017.10.30
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Abstract

Garlic and onion are grown in major cultivation regions that depend on the crop condition and the meteorology of the production area. Therefore, when yields are to be predicted, it is reasonable to use a statistical model in which both the crop and the meteorological elements are considered. In this paper, using a multiple linear regression model, we predicted garlic and onion yields in major cultivation regions. We used the MODIS NDVI that reflects the crop conditions, and six meteorological elements for 7 major cultivation regions from 2006 to 2015. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, the MODIS NDVI in February was chosen the significant independent variable of the garlic and onion yield prediction model. In the case of meteorological elements, the garlic yield prediction model were the mean temperature (March), the rainfall (November, March), the relative humidity (April), and the duration time of sunshine (April, May). Also, the rainfall (November), the duration time of sunshine (January), the relative humidity (April), and the minimum temperature (June) were chosen among the variables as the significant meteorological elements of the onion yield prediction model. MODIS NDVI and meteorological elements in the model explain 84.4%, 75.9% of the garlic and onion with a root mean square error (RMSE) of 42.57 kg/10a, 340.29 kg/10a. These lead to the result that the characteristics of variations in garlic and onion growth according to MODIS NDVI and other meteorological elements were well reflected in the model.

마늘과 양파 재배는 작물의 생육 조건과 주산지 기상에 영향을 받는다. 따라서 단수를 예측할 때에는 주산지의 작황과 기상을 고려할 필요가 있다. 본 연구에서는 2006년에서 2015년까지의 작물의 생육 조건을 반영한 MODIS NDVI와 7개 주산지의 기상요인을 다중 회귀 모형에 적용하여 주산지별 마늘 및 양파의 단수예측 모형을 개발하였다. 다중 회귀 모형에서 독립변수 채택은 단계적 선택방법을 이용하였다. 그 결과, 마늘과 양파 단수예측 모형은 2월의 MODIS NDVI가 중요한 독립변수로 채택되었다. 기상요인은 마늘의 경우, 평균온도(3월), 강우량(11월, 3월), 상대습도(4월), 최저온도(6월)가 채택되었으며, 양파는 강우량(11월), 일조시간(1월), 상대습도(4월), 최저온도(6월)가 독립변수로 채택되었다. MODIS NDVI와 기상요인을 이용한 단수예측 모형은 주산지별 마늘, 양파 평균 단수의 84.4%, 75.9% 설명력을 나타내었으며, RMSE는 각각 42.57 kg/10a, 340.29 kg/10a로 나타났다. 따라서 본 모형은 MODIS NDVI와 기상요인에 따른 마늘과 양파의 단수 변화특성을 잘 반영하고 있는 것으로 판단된다.

Keywords

References

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