NASA engineers used MATLAB to develop the two key components of ForWarn: the Time Series Product Tool (TSPT), which temporally processes MODIS data, and the Phenological Parameters Estimation Tool (PPET), which uses the processed data to calculate the greenness magnitude and the day of year for the peak of the growing season and for other phenological parameters of interest to the U.S. Forest Service.
For TSPT, the team at NASA wrote a MATLAB script that retrieves MODIS data stored in hierarchical data format (HDF) files in the NASA archive and imports the data into MATLAB. TSPT invokes Mapping Toolbox™ functions to convert imported latitude and longitude data to a projected map coordinate system.
The TSPT Band Processing module, also developed in MATLAB, generates the normalized difference vegetation index (NDVI) from the time-series data, as well as soil, moisture, water, and other indices.
Working in MATLAB, the team developed algorithms for TSPT to eliminate pixels distorted by clouds, shadows, the view zenith angle, and other effects.
After merging data from the Aqua and Terra satellites into a single time series, TSPT uses Signal Processing Toolbox™ functions to identify and remove spikes and other outlying data points.
Once the TSPT algorithms have removed the outliers they further filter and resample the time series using Optimization Toolbox™ and Image Processing Toolbox™. The TSPT algorithms apply a Savitzky-Golay filter from Signal Processing Toolbox to interpolate values for any missing pixels.
The engineers used MATLAB, Optimization Toolbox, and Image Processing Toolbox to develop PPET, which performs curve fitting on the time-series data to identify vegetative states related to annual cyclical growing seasons, such as green-up, maturity, senescence, and dormancy. They later enhanced PPET to detect forest disturbances by identifying differences between daily satellite data and time-series baselines.
Using MATLAB Compiler™, the team created standalone executable versions of their MATLAB based algorithms, which can be run by users who do not have MATLAB installed.
The ForWarn team has won multiple awards for their efforts, including the Interagency Partnership Award, which recognizes federal employees from at least two different agencies who have “collaboratively accomplished outstanding work in transferring a technology.” The ForWarn team consists of the U.S. Forest Service, NASA, DOE Oak Ridge National Lab, U.S. Geological Survey, and University of North Carolina at Asheville.