Using MERIS MTCI derived Land Surface Phenology to Predict the Start of Birch and Grass Pollen Season in the UK
Khwarahm, Nabaz; Dash, Jadunandan; Atkinson, Peter M.
Southampton University, UNITED KINGDOM

Grass and Birch pollen are two major causes of seasonal allergic rhinitis (hay fever) in the United Kingdom and parts of Europe affecting around 15-20% of the population. Current prediction of these allergens in the UK are based on measurements of pollen counts at limited number monitoring stations across the country, thus provides a significant uncertainty in spatial representations. Furthermore, this approach (station -based) does not explicitly consider the phenological developments related to the timing of pollination or pollen release, such as flowering, at sources of pollen release which varies significantly across the country. Pollens released by these plants can be linked to flowering phenophase or green up period. Time series of satellite derived vegetation index data provides a potential opportunity to estimate the phenological variables related to pollen release and in turn can be used to predict pollen release at finer spatial scales. Therefore, in this study time series of the MERIS Terrestrial Chlorophyll Index (MTCI) data were used to derive two key phenological variables: start of the season and peak of the season. The MTCI provides information on canopy chlorophyll content (product of both the leaf area index and the leaf chlorophyll concentration) thus provides accurate information on both the amount and condition of vegetation. A technique was developed to predict the timing of flowering and hence the pollen release from the start of growing season derived from the MTCI time series. For Birch the timing of flowering was defined as the time after the start of the growing season when the MTCI value reaches 25% of the maximum. Similarly for grass this was defined as the time when MTCI reached 75% of the maximum. The pollen release dates were validated with the data from the pollen monitoring stations. Both Birch and grass had a strong positive relationship between MTCI derived start of pollen season and ground data, with a slightly stronger relationship for Birch than grass. The technique was applied to produce a detail pollen map of birch and grass across the UK for each year from 2003 to 2010. Future work will involve using this map, phenological model, meteorological data and an atmospheric transport model to provide a pollen prediction map at 1 km spatial resolution across the UK.