@article {Jeganathan:2010:0143-1161:5777,
title = "Mapping the phenology of natural vegetation in India using a remote sensing-derived chlorophyll index",
journal = "International Journal of Remote Sensing",
parent_itemid = "infobike://tandf/tres",
publishercode ="tandf",
year = "2010",
volume = "31",
number = "22",
publication date ="2010-07-01T00:00:00",
pages = "5777-5796",
itemtype = "ARTICLE",
issn = "0143-1161",
eissn = "1366-5901",
url = "https://www.ingentaconnect.com/content/tandf/tres/2010/00000031/00000022/art00005",
doi = "doi:10.1080/01431161.2010.512303",
author = "Jeganathan, C. and Dash, J. and Atkinson, P. M.",
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\textdegree \texttimes 1\textdegree grids (representing 1:250000 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.",
}