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Short-Term Prediction of Fall Foliage Coloration from VIIRS Data

Near Real Time VIIRS NDVI Vegetation Index

Foliage Phase Prediction Derived from VIIRS NDVI

Foliage Phase Prediction - click to enlarge

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:

Assisting farmers to predict the optimum timing for cultivation practices and for monitoring drought occurrences and crop germination;
Helping foresters detecting disturbances related to hurricane destruction, forest pests, disease outbreaks, and species invasion;
Informing the work of environmental and weather modelers regarding the accurate modeling of seasonal carbon sequestration and land-surface physical properties; and,
Assisting tourists and tourism businesses to plan activities around viewing spring wildflowers and fall foliage colors.