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Explores land cover classification using Fourier analysis of multi-temporal vegetation data, suggesting effective monitoring methods.
A signal processing technique is presented and applied to annual patterns of the Global Vegetation Index (GVI) derived from the Advanced Very High Resolution Radiometer (AVHRR) to examine the frequency distribution of the multi-temporal signal. It is shown that frequencies of the signal are linked to integrated GVI, seasonal variability and subseasonal variability of the land cover type. These characteristics are used to derive a land cover classification.
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Andres et al. (1994) studied this question.
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