A Study of the Method for Retrieving the Vegetation Index from FY-3D MERSI-II Data

Abstract

NDVI data have been widely used to detect and monitor vegetation status at regional, continental, and global scales. FY-3D MERSI-II NDVI (FNDVI) is a critical operational product used in many studies monitoring ecosystems and agriculture and assessing climate change and its risks, including drought and fire. MERSI-II and MODIS have very similar spectral response functions in the red and near-infrared channels, making MERSI/NDVI an effective replacement for MODIS/NDVI (MNDVI). Therefore, it is critical to conduct a thorough evaluation of the product’s quality. In this study, the consistency characteristics of two normalized difference vegetation index (NDVI) products, FY-3D MERSI-II NDVI and MODIS NDVI, were compared and validated at national and regional scales in China from 2020 to 2021. To assess the consistency of these two NDVI datasets, the correlation coefficient, root-mean-square error, and mean bias error were used. The findings revealed that the spatial distribution patterns of FNDVI and MNDVI were highly consistent across the country at the monthly time scale. The correlation coefficients were greater than 0.9475 for the two years 2020–2021, while the average deviation was between 0.02 and 0.05, and the root-mean-square error was 0.11. Based on the difference in the time consistency between FNDVI and MNDVI, the changes in the monthly NDVI values of the two types of satellites are generally consistent across the country. Among the three typical experimental areas, the relative deviation of the regional time series for products was the highest in Xinjiang. The relative average deviation of FNDVI in other regions was low, and its change trend was consistent with that of MODIS.