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http://dx.doi.org/10.7780/kjrs.2022.38.6.1.24

A Real-time Correction of the Underestimation Noise for GK2A Daily NDVI  

Lee, Soo-Jin (Geomatics Research Institute, Pukyong National University)
Youn, Youjeong (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Sohn, Eunha (Satellite Planning Division, National Meteorological Satellite Center)
Kim, Mija (Satellite Planning Division, National Meteorological Satellite Center)
Lee, Yangwon (Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University)
Publication Information
Korean Journal of Remote Sensing / v.38, no.6_1, 2022 , pp. 1301-1314 More about this Journal
Abstract
Normalized Difference Vegetation Index (NDVI) is utilized as an indicator to represent the vegetation condition on the land surface in various applications such as land cover, crop yield, agricultural drought, soil moisture, and forest disaster. However, satellite optical sensors for visible and infrared rays cannot see through the clouds, so the NDVI of the cloud pixel is not a valid value for the land surface. This study proposed a real-time correction of the underestimation noise for GEO-KOMPSAT-2A (GK2A) daily NDVI and made sure its feasibility through the quantitative comparisons with Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI and the qualitative interpretation of time-series changes. The underestimation noise was effectively corrected by the procedures such as the time-series correction considering vegetation phenology, the outlier removal using long-term climatology, and the gap filling using rigorous statistical methods. The correlation with MODIS NDVI was higher, and the difference was lower, showing a 32.7% improvement compared to the original NDVI product. The proposed method has an extensibility for use in other satellite products with some modification.
Keywords
NDVI; Noise correction; GK2A; MODIS;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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