Korean J. Remote Sens. 2023; 39(6): 1483-1490
Published online: December 31, 2023
https://doi.org/10.7780/kjrs.2023.39.6.1.25
© Korean Society of Remote Sensing
이경도 1)·김숙경2)·류재현3)·안호용 1)*
1) 농촌진흥청 국립농업과학원 기후변화평가과 연구사(Researcher, Climate Change Assessment Division, National Institute of Agricultural Sciences, Rural Development Administration, Wanju, Republic of Korea) 2) 농촌진흥청 국립농업과학원 기후변화평가과 연구원(Research Assistant, Climate Change Assessment Division, National Institute of Agricultural Sciences, Rural Development Administration, Wanju, Republic of Korea) 3) 농촌진흥청 국립농업과학원 기후변화평가과 박사후연구원(Postdoctoral Reseacher, Climate Change Assessment Division, National Institute of Agricultural Sciences, Rural Development Administration, Wanju, Republic of Korea)
We analyzed the potential for joint utilization of Visible Infrared Imaging Radiometer Suite (VIIRS) satellite imagery Normalized Difference Vegetation Index (NDVI) in crop assessment, considering the aging of MODerate resolution Imaging Spectroradiometer (MODIS) satellites. Over 11 years from 2012 to 2022, we examined the characteristics of NDVI changes in corn and soybean cultivation areas in Illinois, USA. VIIRS and MODIS satellite imagery NDVI exhibited a high correlation coefficient of over 0.98. However, during periods of rapid crop growth or decline, VIIRS NDVI showed values approximately 0.12 to 0.14 higher than MODIS. Estimating crop anomaly classes based on NDVI, we observed similar trends in corn and soybean crop anomaly classes in 2018 and 2019. However, in 2022, there appeared to be a significant divergence in crop anomaly classes, suggesting the need for further investigation. The correlation coefficients between MODIS and VIIRS satellite imagery NDVI and corn and soybean yields were consistently high, exceeding 0.8, indicating the potential for quantity estimation using both MODIS and VIIRS satellite imagery. Specifically, for VIIRS NDVI, excluding the increasing trend in crop quantity estimation for soybeans enhanced the correlation, and compared to MODIS, it showed a consistently high correlation with quantity from approximately 16 days earlier, indicating the potential for early estimation.
Keywords MODIS, VIIRS, NDVI, Crop condition
Korean J. Remote Sens. 2023; 39(6): 1483-1490
Published online December 31, 2023 https://doi.org/10.7780/kjrs.2023.39.6.1.25
Copyright © Korean Society of Remote Sensing.
이경도 1)·김숙경2)·류재현3)·안호용 1)*
1) 농촌진흥청 국립농업과학원 기후변화평가과 연구사(Researcher, Climate Change Assessment Division, National Institute of Agricultural Sciences, Rural Development Administration, Wanju, Republic of Korea) 2) 농촌진흥청 국립농업과학원 기후변화평가과 연구원(Research Assistant, Climate Change Assessment Division, National Institute of Agricultural Sciences, Rural Development Administration, Wanju, Republic of Korea) 3) 농촌진흥청 국립농업과학원 기후변화평가과 박사후연구원(Postdoctoral Reseacher, Climate Change Assessment Division, National Institute of Agricultural Sciences, Rural Development Administration, Wanju, Republic of Korea)
이경도 1)·김숙경2)·류재현3)·안호용 1)*
We analyzed the potential for joint utilization of Visible Infrared Imaging Radiometer Suite (VIIRS) satellite imagery Normalized Difference Vegetation Index (NDVI) in crop assessment, considering the aging of MODerate resolution Imaging Spectroradiometer (MODIS) satellites. Over 11 years from 2012 to 2022, we examined the characteristics of NDVI changes in corn and soybean cultivation areas in Illinois, USA. VIIRS and MODIS satellite imagery NDVI exhibited a high correlation coefficient of over 0.98. However, during periods of rapid crop growth or decline, VIIRS NDVI showed values approximately 0.12 to 0.14 higher than MODIS. Estimating crop anomaly classes based on NDVI, we observed similar trends in corn and soybean crop anomaly classes in 2018 and 2019. However, in 2022, there appeared to be a significant divergence in crop anomaly classes, suggesting the need for further investigation. The correlation coefficients between MODIS and VIIRS satellite imagery NDVI and corn and soybean yields were consistently high, exceeding 0.8, indicating the potential for quantity estimation using both MODIS and VIIRS satellite imagery. Specifically, for VIIRS NDVI, excluding the increasing trend in crop quantity estimation for soybeans enhanced the correlation, and compared to MODIS, it showed a consistently high correlation with quantity from approximately 16 days earlier, indicating the potential for early estimation.
Keywords: MODIS, VIIRS, NDVI, Crop condition
Taehee Kim 1)· Jinmu Choi 2)†
Korean J. Remote Sens. 2020; 36(5): 1125-1137