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- W1999900919 startingPage "5417" @default.
- W1999900919 abstract "본 논문은 MODIS 위성 영상을 이용하여 논벼 생산량을 추정하는 모형의 적합도 개선 및 추정모형내 적절한 설명변수를 탐색하고자 수행되었다. 또한 이 연구는 한국에서 논벼 생산량 조사를 위해 위성 영상을 사용하는 방안을 검토하기 위해 수행되었다. 미국, 호주, 일본 등 많은 선진국들은 재배면적 및 생산량 조사와 같은 농업통계를 산출하기 위해 위성 영상을 이용하고 있다. 그러나 위성 영상을 이용한 작물 생산량 조사의 정확성은 아직 충분치 않은 수준이다. 본 연구는 위성 영상을 이용한 논벼 생산량 조사의 정확도를 증대시키기 위한 몇 가지 방법을 검토하고 있다. 많은 작물 중 논벼를 연구대상으로 선정한 이유는 논벼가 다른 작물 보다 재배면적과 작황의 영상 분석이 용이하였기 때문이고, 다양한 위성 영상 중 MODIS 영상을 이용한 것은 한국 논벼 생산량 조사 연구를 위해 보다 적절한 영상을 다수 포함하고 있었기 때문이다. 이 연구에서 등온선에 의해 구분된 논벼로부터 도출된 NDVI지수, 논벼 등숙기의 일조시간, 강우량, 온도 등 기상변수를 이용하여 단수함수가 추정되었다. 단수함수 추정결과, 모형의 적합도(R-squared)는 0.768-0.891를 보였다. 이 연구는 연평균 등온선에 의해 구분된 NDVI지수와 (등숙기) 기상변수가 단수함수 추정에 매우 유용하게 이용될 수 있음을 보이고 있다. This research was performed in order to improve the goodness of fit of paddy rice production forecasting using MODIS images and to find out appropriate explanatory variables in the forecasting model. The aim of this paper is to review the use of satellite images for the survey of paddy rice production in Korea. Many developed countries, including the United States, Australia, and Japan, have been using satellite images to produce agricultural statistics such as crop production, cultivated acreage, etc. The survey accuracy of crop production by using satellite images, however, is not satisfied in practical use. In this paper, we reviewed several methods to increase the survey accuracy of rice production statistics, gained from satellite images. Rice was selected for this study because its cultivated area and production amount could be more easily identified than other crops by using satellite images. The MODIS images were used because they involved more appropriate images to estimate and analyze rice production. This study estimated yield functions by using the NDVIs, gained from paddy rice yields and annual average isothermal lines, and the meteorological variables such as sunshine hours, rainfall, and temperature during ripening stage. As a result of yield function estimation, the goodness of fit(R-squared) for the models was shown from 0.768 to 0.891. In this study, it is noteworthy academically and practically that vegetation index(NDVIs) identified by annual average isothermal lines and meteorological variables are very useful for estimating yield functions." @default.
- W1999900919 created "2016-06-24" @default.
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- W1999900919 date "2013-11-30" @default.
- W1999900919 modified "2023-10-01" @default.
- W1999900919 title "An Approach for Improvement of Goodness of Fit on the Estimation of Paddy Rice Yield Using Satellite(MODIS) Images" @default.
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- W1999900919 doi "https://doi.org/10.5762/kais.2013.14.11.5417" @default.
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