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Abstract
Time series of MEdium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) level-3 data product, with a spatial resolution of ∼4.6 km composited at 8-day intervals for the years 2003 to 2007, were used to map the phenology of natural vegetation in India. Initial dropouts and noise in the MTCI data were corrected using a temporal moving window filter, Fourier-based smoothing using the first four harmonics was applied and then the phenological variables were extracted through a temporal iterative search of peaks and valleys in the time series for each pixel. The approach was fine-tuned to extract reliable phenological variables from the complex and multiple phenology cycles. A global land cover map (GLC2000) was used as a reference to extract the spatial locations of the vegetation types to infer their phenology. The median of each phenological variable was derived and a spatial majority filter was applied to the 1° × 1° grids (representing 1:250 000 Survey of India toposheet) covering the whole of India. This study presents the results derived for the evergreen, semi-evergreen, moist deciduous and dry deciduous vegetation types of India. A general trend of earlier onset of greenness at lower latitudes than at higher latitudes was observed for the natural vegetation in India.
Acknowledgements
We are grateful to the Natural Environmental Research Council (NERC) Earth Observation Data Centre for providing MTCI data, Dr Thomas Lankester, Infoterra Ltd, UK for providing valuable suggestions on the MTCI composite data, the School of Geography for providing financial support to C.J., and two anonymous reviewers for their valuable comments. Data for MTCI composites were provided by ESA and processed at Infoterra Ltd.