Korean Journal of Remote Sensing (대한원격탐사학회지)

Korean Society of Remote Sensing (대한원격탐사학회)
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A Study on Estimating Rice Yield in DPRK Using MODIS NDVI and Rainfall Data

MODIS NDVI와 강수량 자료를 이용한 북한의 벼 수량 추정 연구

  • Hong, Suk Young (Climate Change and Agroecology Division, Department of Agricultural Environment, National Institute of Agricultural Science(NAS), Rural Development Administration(RDA)) ;
  • Na, Sang-Il (Climate Change and Agroecology Division, Department of Agricultural Environment, National Institute of Agricultural Science(NAS), Rural Development Administration(RDA)) ;
  • Lee, Kyung-Do (Climate Change and Agroecology Division, Department of Agricultural Environment, National Institute of Agricultural Science(NAS), Rural Development Administration(RDA)) ;
  • Kim, Yong-Seok (Climate Change and Agroecology Division, Department of Agricultural Environment, National Institute of Agricultural Science(NAS), Rural Development Administration(RDA)) ;
  • Baek, Shin-Chul (Climate Change and Agroecology Division, Department of Agricultural Environment, National Institute of Agricultural Science(NAS), Rural Development Administration(RDA))
  • 홍석영 (농촌진흥청 국립농업과학원 농업환경부 기후변화생태과) ;
  • 나상일 (농촌진흥청 국립농업과학원 농업환경부 기후변화생태과) ;
  • 이경도 (농촌진흥청 국립농업과학원 농업환경부 기후변화생태과) ;
  • 김용석 (농촌진흥청 국립농업과학원 농업환경부 기후변화생태과) ;
  • 백신철 (농촌진흥청 국립농업과학원 농업환경부 기후변화생태과)
  • Received : 2015.10.05
  • Accepted : 2015.10.13
  • Published : 2015.10.31
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Abstract

Lack of agricultural information for food supply and demand in Democratic People's republic Korea(DPRK) make people sometimes confused for right and timely decision for policy support. We carried out a study to estimate paddy rice yield in DPRK using MODIS NDVI reflecting rice growth and climate data. Mean of MODIS $NDVI_{max}$ in paddy rice over the country acquired and processed from 2002 to 2014 and accumulated rainfall collected from 27 weather stations in September from 2002 to 2014 were used to estimated paddy rice yield in DPRK. Coefficient of determination of the multiple regression model was 0.44 and Root Mean Square Error(RMSE) was 0.27 ton/ha. Two-way analysis of variance resulted in 3.0983 of F ratio and 0.1008 of p value. Estimated milled rice yield showed the lowest value as 2.71 ton/ha in 2007, which was consistent with RDA rice yield statistics and the highest value as 3.54 ton/ha in 2006, which was not consistent with the statistics. Scatter plot of estimated rice yield and the rice yield statistics implied that estimated rice yield was higher when the rice yield statistics was less than 3.3 ton/ha and lower when the rice yield statistics was greater than 3.3 ton/ha. Limitation of rice yield model was due to lower quality of climate and statistics data, possible cloud contamination of time-series NDVI data, and crop mask for rice paddy, and coarse spatial resolution of MODIS satellite data. Selection of representative areas for paddy rice consisting of homogeneous pixels and utilization of satellite-based weather information can improve the input parameters for rice yield model in DPRK in the future.

식량수급을 이해하기 위한 농업 현황 정보가 부족한 북한을 대상으로 위성영상과 기후자료를 이용하여 객관적이고 재현 가능한 벼 수량을 추정하는 방법을 개발하는 것을 본 연구의 목적으로 하였다. 2002년부터 2014년까지의 MODIS 위성 식생지수 평균 NDVI 최대값과 27개 관측지점의 9월 강수량 자료를 이용하여 북한의 벼 수량 값을 추정하였다. 모형의 결정계수는 0.44, RMSE는 0.27 ton/ha로 다소 크게 나타났고, 분산분석결과 F비가 3.0983, 유의확률이 0.1008을 보였다. 벼논 지역의 MODIS 평균 NDVI 최대값과 등숙기의 기후자료를 이용하여 추정한 북한의 벼 수량은 2007년이 2.71 ton/ha로 가장 낮게, 2006년이 3.54 ton/ha로 가장 높게 나타났다. 통계 값과 추정 값의 산점도를 통하여 비교한 결과 벼 수량이 약 3.3 ton/ha 보다 적을 때는 모형의 추정 값이 높고 그 이상일 때는 통계 값이 더 높게 나타나는 경향이었다. 모형의 종속변수와 독립변수로 사용되는 위성영상의 품질, 단일 시기의 벼논 마스크 영상, 기상 관측지점의 수와 자료의 품질, 통계 값의 품질 등으로 벼 수량에 대한 추정 성능의 한계가 있지만 객관적 자료를 사용하여 재현 가능한 방법을 제시하였다는 의미를 가진다. 모형 구동을 위해 사용되는 자료의 품질을 높여 나가야 하는 과제를 안고 있다.

Keywords

References

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