GEO DATA

Seungtaek Jeong

2 Articles

The Spatial Maps of Paddy Rice Yield over Northeast Asia Using COMS Geostationary Satellite and Reanalysis Meteorological Data: Seungtaek Jeong, Jonghan Ko, Jong-Min Yeom; GEO DATA. 2021;3(2):20-24. Published online July 21, 2021; DOI: https://doi.org/10.22761/DJ2021.3.2.003

280 View
8 Download

Abstract PDF: This study estimated rice yield maps for Northeast Asia by using the Communication, Ocean and Meteorological satellite (COMS), Terra satellite, and Regional Data Assimilation and Prediction System (RDAPS) of the numerical model. The rice yield is highly useful in the study for crop information monitoring according to climate change as well as agriculture information, industry, and economy. This study produced rice yield maps for Northeast Asia including Korea, North Korea, Japan, and three northeastern provinces of China (Heilongjiang, Jilin, and Liaoning) from 2011 to 2017. The estimated spatial resolution of the rice yield maps in Northeast Asia is 500 m. The spatial observation range is 25 ° N ~ 47 ° N and 115 ° E ~ 145 ° E. In order to estimate rice yield, Remote Sensing-integrated Crop Model was employed in this study. The inputs of the RSCM are vegetation indices from Geostationary Ocean Color Imager (GOCI) of the COMS, solar radiation from Meteorological Imager of the COMS, Land Surface Water Index from the MODerate Resolution Imaging Spectroradiometer, and the temperature from the RDAPS were considered as input data. In particular, this study applied the Bidirectional Reflectance Distribution Function to the GOCI time-series images to calculate more improved vegetation indices by minimizing the directional error generated in the satellite observation location. These indices were very effective in the simulation of the rice yield.

The spatial data of paddy rice classification over Northeast Asia using COMS geostationary satellite: Seungtaek Jeong, Jonghan Ko, Jong-Min Yeom; GEO DATA. 2021;3(1):18-22. Published online March 31, 2021; DOI: https://doi.org/10.22761/DJ2021.3.1.003

457 View
13 Download
2 Citations

The Korea Aerospace Research Institute (KARI) estimated paddy rice classification maps over Northeast Asia using the Cheonian geostationary orbiting satellite (COMS: Communication, Ocean and Meteorological Satellite) data. In the case of classification map of rice paddy, it is not only used as input data for estimating rice yield, but also for various fields such as agriculture, weather, climate change, bio energy, and ecology. The spatial resolution of the classified rice map is 500 m, and the classification map was estimated yearly temporal resolution from 2011 to 2017. The spatial coverage of the classification map was the Northeast Asia with the latitude 25 ° N ~ 47 ° N and the longitude 115 ° E ~ 145 ° E as shown in Fig. 1 including Heilongjiang Sheng, Jilin Sheng, and Liaoning Sheng. In this classification map of paddy rice, it was calculated by applying geostationary orbiting satellites based on value-added products from Geostationary Ocean Color Imager (GOCI). In this study, we additionally used MODIS Land Surface Water Indices (LSWI) to support rice classification by considering the physical characteristics of rice cultivation area in the transplanting season. Basically, the radiance value of the top of atmosphere (TOP) observed in GOCI satellite was corrected to the surface reflectance at the top of the canopy through radiative transfer model. After that, NDVI, which can reflect the time series growth characteristics of rice, was estimated first. In addition, the MODIS LSWI index was used to determine the rice cultivation area with the NDVI in Northeast Asia by reflecting the water characteristics of the rice cultivation area during the transplanting period. More details of validation results for this algorithm can be found in previous studies.

Citations

Citations to this article as recorded by

The Spatial Maps of Paddy Rice Yield over Northeast Asia Using COMS Geostationary Satellite and Reanalysis Meteorological Data
Seungtaek Jeong, Jonghan Ko, Jong-Min Yeom
GEO DATA.2021; 3(2): 20. CrossRef
The Map Data of BRDF-Adjusted Surface Reflectance from GOCI Geostationary Satellite Imagery over Korean Peninsula
Jong-Min Yeom
GEO DATA.2021; 3(4): 66. CrossRef

Author index