Land surface vegetation phenology is an important process for the real-time monitoring and detecting inter-annual
variability in terrestrial ecosystem carbon exchange and climate-biosphere interactions. Crop phenology is an important
factor that influences crop growth and yield estimation models. Since the mid-1980s, coarse-resolution,
temporally-composited satellite data have been used to study vegetation phenology. View-angle corrected nadir
reflectances from the 16-day, 1km operational MODIS BRDF/Albedo product are currently used to monitor global land
cover dynamics. In this paper, we developed an improved methodology for using the new 500-m MODIS BRDF/Albedo
Version 005 product to monitor global vegetation phenology by utilizing time series of the Normalized Difference
Vegetation Index (NDVI). The method adopts a rolling strategy for the continuous updating of the underlying anisotropy
(or BRDF shape), so that the latest land surface BRDF information can be used as prior-knowledge for next retrieval.
Using this approach, transition dates for vegetation phenology in time series of NDVI can be determined from MODIS
data at finer temporal and spatial resolution. Preliminary results based on monitoring crops in northern China
demonstrate the effectiveness of our rolling retrievals coupled with the improved spatial resolution of the new MODIS
product.
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