Short-Term Prediction of Fall Foliage Coloration from VIIRS Data
Near Real Time VIIRS NDVI Vegetation Index
Foliage Phase Prediction Derived from VIIRS NDVI
15 October 2014 - 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 fall foliage coloration 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.
Fall foliage coloration is a phenomenon that occurs in many deciduous trees and shrubs worldwide. Although easily observed in field, this new data product is the first to measure and predict fall foliage coloration 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. Read more