Short-Term Prediction of Spring Foliage Coloration from VIIRS Data
Near Real Time VIIRS Daily Vegetation Index
Updated to reflect images through mid June
Foliage Phase Prediction Derived from VIIRS Daily Vegetation Index
June 12, 2015 - Xiaoyang Zhang (formerly at STAR and currently at South Dakota State University) and Bob Yu (STAR/SMCD/EMB) have developed a new method to monitor and predict short-term spring green foliage development using the VIIRS daily vegetation index. Developed with the support of the JPSS Proving Ground and Risk Reduction Program, the new system currently monitors foliage development across the United States every 3 days and further makes prediction to 10 days ahead.
Spring foliage development indicates the occurrence of spring events across the vegetated land surface. Although easily observed in field, it is very challenging to detect in near real time from satellite data. This preliminary product is the first time to measure and predict green foliage progress from a satellite data time series.
Monitoring and predicting the development of vegetation phenology from satellite data are particularly important for:
Data, algorithms, and images presented on STAR websites are intended for experimental use only and are not supported on an operational basis. More information