Time-series NDVI product has been proven to be a powerful tool to investigate from past-events to the extraction of phonological information. This paper describes the application of discrete Fourier transform (DFT) analysis over the 9 years of MODIS data for the identification of the two types of vegetation cover, Pinus densiflora(Pd) and Querqus mongolica(Qm) which are dominant species of evergreen and broadleaved deciduous forest, respectively. We also demonstrated the potential of detecting the different pattern of the vegetation growth within the same species by latitude. Reference NDVI cycle was extracted from the entire MODIS scene based on a pixel. 324 reference cycles, 135 Pd and 189 Qm, were selected over the 9 years from 2000 to 2008 of South Korea. The DFT analysis was mainly focused on the 0^th harmonic and 1^st harmonic, each of which represents the mean value and the variation amplitude of the NDVI over the years, respectively.   

Results/Conclusions

.   The average over the 9 years of the 0^th harmonic shows that Pd is 0.74 and Qm is 0.65, which implies that Pd has a higher NDVI than Qm. Similarly obtained 1^st harmonic reveals that Pd is 0.1 and Qm is 0.3, which can be intuitively understood because the seasonal variation of Qm is much larger than Pd. In addition to this general trend, an interesting feature is found on the variation of each harmonics with respect to the latitude, where the 0^st harmonic of Pd shows a rapid increase from the point of latitude 37°, while the 1^st harmonic shows decrease at the same latitude. This manifests that Pd has different environmental conditions with the boundary of 37°. Based on the same principles, inter-annual vegetation changes can be monitored with the possibility to distinguish between coverage fluctuations and phonological variations/changes. This result can be used to assess the long-term land use/land cover change due to the global warming.