Land-Surface Phenologies from AVHRR Using the Discrete Fourier Transform

The first and second harmonics of the discrete Fourier transform (DFT) concisely summarize the amplitude and phase of annual and biannual signals embedded in time-series of Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) data. We applied and evaluated the DFT using monthly composited NDVI data over a 7-year period for a 150 × 150-km study area in southern California. The study area contains strong gradients in environmental conditions and basic vegetation formations. Analysis of the DFT harmonics for six point-locations provided a basis for linking the DFT results to basic vegetation types according their characteristic phenologies. The mean NDVI, or 0th-order harmonic, indicated overall productivity, allowing the differentiation of unproductive, moderately productive, and highly productive sites. The amplitude of the first harmonic indicated the variability of productivity over the year as expressed in a single annual pulse of net primary production. This summarized the relative dominance of evergreen vs. deciduous or annual habit. The phase of the first harmonic summarized the timing of green-up relative to the timing of winter and spring rains. This differentiated rapidly responding annual grasslands, slowly responding evergreen life-forms, and irrigated agriculture. The second harmonic indicated the strength and timing of any biannual signal. This provided information on secondary vegetation types, such as subcanopy grasses beneath evergreen woodlands or mixtures of annual grasslands and irrigated agriculture. The point-based analysis provided the foundation for a regional analysis of the entire study area. The mean NDVI and first- and second-order amplitude and phase, in conjunction with 148 field-sampled polygons, were used to produce an unsupervised classification of basic vegetation formations for the study area. These results were evaluated by comparison with other land cover products, and through assessment using field-sampled test regions.