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http://dx.doi.org/10.11108/kagis.2022.25.1.133

Rice Yield Estimation Using Sentinel-2 Satellite Imagery, Rainfall and Soil Data  

KIM, Kyoung-Seop (Geospatial Research Center, GEO C&I Co., Ltd.)
CHOUNG, Yun-Jae (Geospatial Research Center, GEO C&I Co., Ltd.)
JUN, Byong-Woon (Dept. of Geography, Kyungpook National University)
Publication Information
Journal of the Korean Association of Geographic Information Studies / v.25, no.1, 2022 , pp. 133-149 More about this Journal
Abstract
Existing domestic studies on estimating rice yield were mainly implemented at the level of cities and counties in the entire nation using MODIS satellite images with low spatial resolution. Unlike previous studies, this study tried to estimate rice yield at the level of eup-myon-dong in Gimje-si, Jeollabuk-do using Sentinel-2 satellite images with medium spatial resolution, rainfall and soil data, and then to evaluate its accuracy. Five vegetation indices such as NDVI, LAI, EVI2, MCARI1 and MCARI2 derived from Sentinel-2 images of August 1, 2018 for Gimje-si, Jeollabuk-do, rainfall and paddy soil-type data were aggregated by the level of eup-myon-dong and then rice yield was estimated with gamma generalized linear model, an expanded variant of multi-variate regression analysis to solve the non-normality problem of dependent variable. In the rice yield model finally developed, EVI2, rainfall days in September, and saline soils ratio were used as significant independent variables. The coefficient of determination representing the model fit was 0.68 and the RMSE for showing the model accuracy was 62.29kg/10a. This model estimated the total rice production in Gimje-si in 2018 to be 96,914.6M/T, which was very close to 94,470.3M/T the actual amount specified in the Statistical Yearbook with an error of 0.46%. Also, the rice production per unit area of Gimje-si was amounted to 552kg/10a, which was almost consistent with 550kg/10a of the statistical data. This result is similar to that of the previous studies and it demonstrated that the rice yield can be estimated using Sentinel-2 satellite images at the level of cities and counties or smaller districts in Korea.
Keywords
Rice Yield Estimation; Sentinel-2; Vegetation Indices; Rainfall Days; Paddy Soil Type; Gamma Generalized Linear Model;
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Times Cited By KSCI : 9  (Citation Analysis)
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