Abstract
NDVI time series data exhibit cyclic behaviors derived from the phenological characteristics of the vegetation. Different forms of Fourier analysis have been effectively used to analyze remote sensed NDVI data, allowing the simultaneous fitting of secular and cyclic components. However, variations in frequencies and/or phases of the cyclic components may exist, that are not considered in typical spectral analysis. In this work, MODIS derived NDVI biweekly time series data are analyzed considering secular and quasi-periodic components, fitted to the data using a smoothing algorithm based on a spectral time-frequency analysis. The algorithm works well with equispaced data, and allows the analysis of temporal variations in cyclic frequencies and phases. Examples of applications in different types of vegetation and conditions in Southeast Spain are shown.
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