Mapping the birch and grass pollen seasons in the UK using satellite sensor time-series

Abstract

Grass and birch pollen are two major causes of seasonal allergic rhinitis (hay fever) in the UK and parts of Europe affecting around 15-20% of the population. Current prediction of these allergens in the UK is based on (i) measurements of pollen concentrations at a limited number of monitoring stations across the country and (ii) general information about the phenological status of the vegetation. Thus, the current prediction methodology provides information at a coarse spatial resolution only. Most station-based approaches take into account only local observations of flowering, while only a small number of approaches take into account remote observations of land surface phenology. The systematic gathering of detailed information about vegetation status nationwide would therefore be of great potential utility. In particular, there exists an opportunity to use remote sensing to estimate phenological variables that are related to the flowering phenophase and, thus, pollen release. In turn, these estimates can be used to predict pollen release at a fine spatial resolution. In this study, time-series of MERIS Terrestrial Chlorophyll Index (MTCI) data were used to predict two key phenological variables: the start of season and peak of season. A technique was then developed to estimate the flowering phenophase of birch and grass 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 reached 25% of the maximum. Similarly, for grass this was defined as the time when the MTCI value reached 75% of the maximum. The predicted pollen release dates were validated with data from nine pollen monitoring stations in the UK. For both birch and grass, we obtained large positive correlations between the MTCI-derived start of pollen season and the start of the pollen season defined using station data, with a slightly larger correlation observed for birch than for grass. The technique was applied to produce detailed maps for the flowering of birch and grass across the UK for each of the years from 2003 to 2010. The results demonstrate that the remote sensing-based maps of onset flowering of birch and grass for the UK together with the pollen forecast from the Meteorology Office and National Pollen and Aerobiology Research Unit (NPARU) can potentially provide more accurate information to pollen allergy sufferers in the UK.

Mapping the Flowering of an Invasive Plant Using Unmanned Aerial Vehicles: Is There Potential for Biocontrol Monitoring?

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Pear Flower Cluster Quantification Using RGB Drone Imagery

“…Imaging methods ranging from spaceborne to proximal platforms can deliver the inputs needed to automate flower mapping. However, existing satellite flower mapping methods are mainly focused on the detection of the onset of flowering in trees but are usually too coarse (>10 m) to accurately determine the flower number [4,5]. Flower number mapping with manned airborne platforms is feasible but demands more expensive sensors with a higher spectral resolution to compensate for the lack in spatial resolution [6,7].…”

Google Trends and pollen concentrations in allergy and airway diseases in France

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“…For patients who are allergic to pollen, knowledge regarding the onset and duration of the pollen season is of great importance . It is therefore essential to be able to forecast the onset of the pollen season as well as to characterize seasons in different places using sentinel networks . Pollen concentrations can assess the exposure of pollen‐allergic patients .…”