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- W107584516 abstract "Vegetation phenology is considered as one of the key indicators that has provided real evidence of climate change (Cleland, 2007). Observation records suggest that spring has advanced globally at the rate of 2 to 5 days per decade (Parmesan and Yohe, 2003; Root et al., 2003) and that senescence has been delayed, mostly as a function of increases in global mean temperature (Menzel, 2003). However, the effects of climate change on vegetation phenology are species-dependent and, therefore, using ground observations of phenological events it is difficult to provide a global-scale picture. On the contrary, satellite-derived vegetation indices provide indirect estimates of vegetation phenological events through repeat coverage over the globe. From the point-of-view of vegetation phenology, several geo-computational techniques have been used to correct and smooth time series vegetation index data, such as to estimate phenological variables accurately. Some of the frequently used methods in smoothing time-series satellite sensor data are Fourier harmonics based methods (classical and discrete), threshold based methods, curve fitting methods and point of inflection methods (Vivoy et al., 1992, Roerink et al., 2000, Jakubauskas et al., 2001; Wagenseil, 2006; Chen et al., 2001; Chen et al., 2006; Jonsson and Eklundh, 2002; Bradley et al., 2007; Zhang" @default.
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- W107584516 date "2009-01-01" @default.
- W107584516 modified "2023-09-27" @default.
- W107584516 title "Analysing the effect of different geocomputational techniques on estimating phenology in India" @default.
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