論文

査読有り 国際共著 国際誌
2022年7月15日

Estimation of Rice Yield Considering Heading Stage Using Satellite Imagery and Ground-Based Data in Indonesia

Journal of Agricultural Science
  • Yuki Sofue
  • ,
  • Chiharu Hongo
  • ,
  • Naohiro Manago
  • ,
  • Gunardi Sigit
  • ,
  • Koki Homma
  • ,
  • Budi Utoyo

14
8
開始ページ
1
終了ページ
1
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.5539/jas.v14n8p1
出版者・発行元
Canadian Center of Science and Education

Understanding the temporal and spatial variability in crop yield is considered as one of the key steps in agricultural risk assessment. Therefore, a study of an irrigated area in Cihea, West Java, Indonesia, was conducted to assess rice yield per field using SENTINEL-2 imagery and yield observation data in 2018 and 2019. The study area is located in the Citarum River basin. SENTINEL-2 images were used to derive paddy rice’s growth curve and estimate rice growth stages based on the normalized difference vegetation index. Using these results, the regression model formula using Band 4 (665 nm) and the normalized difference water index in the ripening stage was created (R2 = 0.40, RMSE = 1.21 t/ha). The results from this model were used to generate yield maps, which illustrated a distinct spatial variation in rice yield, such as the average rice productivity in the study area was relatively high, however, the difference between years tended to be small in the upper stream area. The results of this study show that this method is effective in this area to monitor rice yield condition and distribution.Understanding the temporal and spatial variability in crop yield is considered as one of the key steps in agricultural risk assessment. Therefore, a study of an irrigated area in Cihea, West Java, Indonesia, was conducted to assess rice yield per field using SENTINEL-2 imagery and yield observation data in 2018 and 2019. The study area is located in the Citarum River basin. SENTINEL-2 images were used to derive paddy rice’s growth curve and estimate rice growth stages based on the normalized difference vegetation index. Using these results, the regression model formula using Band 4 (665 nm) and the normalized difference water index in the ripening stage was created (R2 = 0.40, RMSE = 1.21 t/ha). The results from this model were used to generate yield maps, which illustrated a distinct spatial variation in rice yield, such as the average rice productivity in the study area was relatively high, however, the difference between years tended to be small in the upper stream area. The results of this study show that this method is effective in this area to monitor rice yield condition and distribution.

リンク情報
DOI
https://doi.org/10.5539/jas.v14n8p1
URL
https://ccsenet.org/journal/index.php/jas/article/download/0/0/47456/50878
ID情報
  • DOI : 10.5539/jas.v14n8p1
  • ISSN : 1916-9752
  • eISSN : 1916-9760

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