With the availability of high frequent satellite data, crop phenology could be accurately
mapped using time-series remote sensing data. Vegetation index time-series data derived …

Six key phenological stages were defined based on NOAA/AVHRR NDVI time series data
collected in the Huang-Huai-Hai (HHH) Plain of China from 1990 through 2000. In a winter …

Timely and efficient monitoring of crop phenology at a high spatial resolution are crucial for
the precise and effective management of agriculture. Recently, satellite-derived vegetation …

In recent years, the use of high temporal resolution satellite data has been emerging as an
important tool to study crop phenology. Most methods to detect phenological events based …

Vegetation typically elicits dynamics at the seasonal and annual level. Time-series of
normalized difference vegetation index (NDVI) datasets, such as the pathfinder AVHRR land …

Multi-sensor remote sensing data fusion technologies have been developed and widely
applied in recent years, providing a feasible and economical solution to increase the …

Accurate and updated information on winter wheat distribution is vital for food security. The
intra-class variability of the temporal profiles of vegetation indices presents substantial …

Timely and accurate mapping of winter crop planting areas in China is important for food
security assessment at a national level. Time-series of vegetation indices, such as the …

Crop phenology is critical for agricultural management, crop yield estimation, and
agroecosystem assessment. Traditionally, crop growth stages are observed from the ground …

Remote sensing technology allows monitoring the progress of vegetation and crop
phenology in large regions. Seasonal vegetation trends are commonly estimated from high …