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Abstract
This study presents a normalized difference vegetation index (NDVI)-based land-cover change detection method based on harmonic analysis. Multi-temporal NDVI data show seasonal variation characteristics in the time domain. A harmonic model represents the characterization of the temporal variability in a data set over a local region corresponding to a pixel through its harmonic components. In this research, annual land-cover change detection is performed by tracking the temporal dynamics through analysing harmonic components. A simple but effective noise reduction process is also proposed to provide the necessary high-quality data stream for the multi-temporal NDVI analysis based on the statistics of the observed oscillations. The proposed algorithm was tested and evaluated with the multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI time series of the MYD13Q1, 16 day L3 global 250 m SIN grid (v005) VI data set. The results indicate that the proposed algorithm provides a computationally inexpensive automatic method to monitor vegetation conditions and long-term land-cover change over large regions. The method described here is particularly useful for monitoring changes in well-established deciduous forests with developed canopies.
Acknowledgements
The authors would like to thank the two anonymous referees and Prof. Peter Webley in the Geophysical Institute at the University of Alaska Fairbanks for their comments on this manuscript.