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http://dx.doi.org/10.7780/kjrs.2013.29.4.1

Land-Cover Vegetation Change Detection based on Harmonic Analysis of MODIS NDVI Time Series Data  

Jung, Myunghee (Department of digital Media, Anyang University)
Chang, Eunmi (Ziinconsulting Inc.)
Publication Information
Korean Journal of Remote Sensing / v.29, no.4, 2013 , pp. 351-360 More about this Journal
Abstract
Harmonic analysis enables to characterize patterns of variation in MODIS NDVI time series data and track changes in ground vegetation cover. In harmonic analysis, a periodic phenomenon of time series data is decomposed into the sum of a series of sinusoidal waves and an additive term. Each wave is defined by an amplitude and a phase angle and accounts for the portion of variance of complex curve. In this study, harmonic analysis was explored to tract ground vegetation variation through time for land-cover vegetation change detection. The process also enables to reconstruct observed time series data including various noise components. Harmonic model was tested with simulation data to validate its performance. Then, the suggested change detection method was applied to MODIS NDVI time series data over the study period (2006-2012) for a selected test area located in the northern plateau of Korean peninsula. The results show that the proposed approach is potentially an effective way to understand the pattern of NDVI variation and detect the change for long-term monitoring of land cover.
Keywords
Vegetation index Change Detection; Harmonic analysis; MODIS NDVI;
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Times Cited By KSCI : 2  (Citation Analysis)
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1 Zhang, X., M.A. Friedl, C.B. Schaaf, A.H. Strahler, J.C.F. Hodges, F. Gao, B.C. Reedb and A. Huetec, 2003. Monitoring vegetation phenology using MODIS, Remote Sensing of Environment, 84(3): 471-475.   DOI   ScienceOn
2 Jakubauskas, E. Mark, D.R. Legates, and J.H. Kastens, 2001. Harmonic Analysis of Time-Series AVHRR NDVI Data, Photogrammetric Engineering & Remote Sensing, 67(4): 461-470.
3 Jiang, Bo, S. Liang, J. Wang and Z. Xiao, 2010. Modeling MODIS LAI time series using three statistical methods, Remote Sensing of Environment, 114: 1432-1444.   DOI   ScienceOn
4 Jonsson, P. and L. Eklundh, 2002. Seasonality extraction by function fitting to time series of satellite sensor data, IEEE Trans. of Geoscience Remote Sensing, 40(8): 1824-1832.   DOI   ScienceOn
5 Jung, M.H., S.H. Lee, E.M Chang, S.W. Hong, 2012. Method of Monitoring Forest Vegetation Change based on Change of MODIS NDVI Time Series Pattern, Journal of Korea Spatial Information Society, 20(4): 47-55 (in Korean with English abstract)   과학기술학회마을   DOI   ScienceOn
6 Lee, S.H., 2009. Adaptive Reconstruction NDVI Image Times Series for Monitoring Vegetation Changes, Korean Journal of Remote Sensing, 25(2): 95-105 (in Korean with English abstract)   DOI
7 Lovell, J.L. and R.D. Graetz, 2001. Filtering pathfinder AVHRR Land NDVI data for Australia, International Journal of Remote Sensing, 22(13): 2649-2654.   DOI   ScienceOn
8 Ma, Mingguo and F. Veroustraete, 2006. Reconstructing pathfinder AVHRR land NDVI time-series data for the Northwest of China, Advances in Space Research, 37: 835-840.   DOI   ScienceOn
9 Pettorellia, N., J.O. Vika, A. Mysteruda, J. Gaillardb, C.J. Tuckerc and N.C. Stensetha, 2005. Using the satellite-derived NDVI to assess ecological responses to environmental change, Trends in Ecology and Evolution, 20(9): 503-510.   DOI   ScienceOn
10 Roerink, G., M. Menenti and W. Verhoef, 2000. Reconstructing cloud free NDVI composites using Fourier analysis of time series, International Journal of Remote Sensing, 21(9):1911-1917.   DOI   ScienceOn
11 Sakamoto, T., M. Yokozawa, H. Toritani, M. Shibayama, N. Ishitsuka, H. Ohno, 2005. A crop phenology detection method using time-series MODIS data, Remote Sensing of Environment, 96: 366-374.   DOI   ScienceOn
12 Bruce, L.M. and A. Mathur, 2005. Denoising and wavelet-based feature extraction of MODIS multi-temporal vegetation signatures, Analysis of Multi-Temporal Remote Sensing Images, 2005 International Workshop, pp.95-98.
13 Box, G., and G. Jenkins, 1976. Time series analysis forecasting and control, Prentice-Hall Englewood Cliffs, New Jersey, USA.
14 Bloomfield, P., 1976. Fourier Analysis of Time Series: An Introduction, John Wiley & Sons, New York, NY, USA.
15 Bradley, B., R. Jacob, J. Hermance, and J.F. Mustard, 2007. A curve-fitting technique to derive interannual phonologies from time series of noisy NDVI satellite data, Remote Sensing of Environment, 106: 137-145.   DOI   ScienceOn
16 Chappell, A., J.W. Seaquist and L. Eklundh, 2001. Improving the estimation of noise from NOAA AVHRR NDVI for Africa using geostatistics, International Journal of Remote Sensing, 22(6): 1067-1080.   DOI
17 Davis, J.C., 1986. Statistics and Data Analysis in Geology, 2nd Edition, J. Wiley and Sons, New York, NY, USA.
18 Doran, H.E. and J.J. Quilkey, 1972. Harmonic Analysis of Seasonal Data: Some Important Properties, American Journal of Agricultural Economics, 54(4): 646-651.   DOI   ScienceOn
19 Galford, G.L., J.F. Mustard, J. Melillo, A. Gendrin, C.C. Cerri, and C.E.P. Cerri, 2008. Wavelet analysis of MODIS time series to detect expansion and intensification of row-crop agriculture in Brazil, Remote Sensing of Environment, 112: 576-587.   DOI   ScienceOn