The necessity and availability of noise-free daily satellite-observed NDVI during rapid phonological changes in terrestrial ecosystems in East Asia

General, global, long-term, and comprehensive phenological observations are required to evaluate the variability of photosynthetic activities due to environmental changes in terrestrial ecosystems. The observation of seasonal changes and detection of interannual variation in canopy phenology over regional and global scales require satellite data with high temporal resolution (i.e. a daily time step). However, satellite data often include noise caused by snow cover on vegetation, cloud contamination, and atmospheric aerosols. To accurately detect the timing of leaf-expansion and leaf-fall, which occur rapidly, and their rates, it is necessary to examine the observational frequency of noise-free satellite-observed vegetation index data during each phenological period. In this study, we investigated the spatiotemporal distribution of the number of observational days (NUMdays) in the Terra/MODIS (Moderate Resolution Imaging Spectroradiometer)-observed daily high-quality normalized difference vegetation index (NDVI_high) data with no effects of snow cover, cloud contamination, or atmospheric noise. These data were examined for each month over 10 years in the various ecosystems of East Asia. To ground-truth the relationship between the Terra/MODISobserved daily NDVI_high data and canopy surface images, we performed a long-term continuous field study in a cooltemperate deciduous broad-leaved forest in central Japan. During the leaf-expansion and leaf-fall periods, the NUMdays for NDVI_high data in southern Russia, northeastern China, the Tibetan Plateau, Korea, and maritime Japan was about 3-7 for each month. The NUMdays for NDVI_high data exceeded 10 for each month in arid regions during the growing season and in the subtropical region including northeastern India, Myanmar, and southwestern China during the dry season. In contrast, the NUMdays for NDVI_high data was almost 0 for each month in southeastern China throughout the year and in the subtropical region during the southeastern monsoon season (July and August). By considering observations from both the Terra/MODIS and Aqua/MODIS satellites, the NUMdays for NDVI_high data in the deciduous broad-leaved forest in Japan was increased by 40% compared with only Terra/ MODIS satellite observations. Our findings indicate that daily NDVI data from multiple satellites detect the seasonal changes in the various ecosystems of East Asia more accurately than 8-day or biweekly composite NDVI data.