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Abstract
Seven years of the MERIS Global Vegetation Index (MGVI) data have been obtained for a national-scale study of vegetation seasonality in Ireland from 2003 to 2009. The selection of an appropriate composite period for the daily MGVI data was guided by in situ observations of vegetation spring greening and cloud cover from two representative point locations across the island. A period of 10 days was selected as an optimum, minimising the amount of cloud cover across the island while still capturing vegetation seasonality change. Short-term variation in the MGVI time series after time-compositing had been applied was found to be unrelated to vegetation dynamics, suggesting that external factors, such as cloud cover compromise the quality of daily MGVI values. A verification study, using the METEOSAT Cloud Mask (CLM), was conducted to validate this hypothesis. The results suggest that for 7 out of 10 MGVI images over half the values may be in error due to the presence of cloud cover, indicating that the MERIS cloud screening approaches are sub-optimal for conditions experienced over Ireland. A review of the MGVI atmospheric model indicates that MERIS atmospheric corrections may only partially correct for scattering by aerosols or absorption by water vapour.
Acknowledgements
The Environmental Protection Agency (EPA), Ireland, has provided funding for this PhD project under the STRIVE initiative, 2007–2010 (Project 2007-S-ET-4). The authors are grateful to the staff at the Institute for Environment and Sustainability, JRC, Ispra, Italy, especially Nadine Gobron for advice given. The G-POD technical team at the European Space Agency's ESRIN facility provided the MGVI data and the Armagh Observatory provided the cloud data.