This function calculates the start and the end of pollen season for each year
pollen_season(value, date, method, threshold = NULL)pollen concentration values
dates
the pollen season method - "90", "95", "98", "Mesa", "Jager", "Lejoly", or "Driessen"
a threshold value used for the "Driessen" method
a data.frame object with year, date of pollen season start and date of pollen season end
Nilsson S. and Persson S.: 1981, Tree pollen spectra in the Stockholm region (Sweden) 1973-1980, Grana 20, 179-182.
Andersen T.B.: 1991, A model to predict the beginning of the pollen season, Grana 30, 269-275.
Torben B.A.: 1991, A model to predict the beginning of the pollen season, Grana 30, 269-275.
Galan C., Emberlin J., Dominguez E., Bryant R.H. and Villamandos F.: 1995, A comparative analysis of daily variations in the Gramineae pollen counts at Cordoba, Spain and London, UK, Grana 34, 189-198.
Sanchez-Mesa J.A., Smith M., Emberlin J., Allitt U., Caulton E. and Galan C.: 2003, Characteristics of grass pollen seasons in areas of southern Spain and the United Kingdom, Aerobiologia 19, 243-250.
Jager S., Nilsson S., Berggren B., Pessi A.M., Helander M. and Ramfjord H.: 1996, Trends of some airborne tree pollen in the Nordic countries and Austria, 1980-1993. A comparison between Stockholm, Trondheim, Turku and Vienna, Grana 35, 171-178.
Lejoly-Gabriel and Leuschner: 1983, Comparison of air-borne pollen at Louvain-la-Neuve (Belgium) and Basel (Switzerland) during 1979 and 1980, Grana 22, 59-64.
Driessen M. N. B. M., Van Herpen R. M. A. and Smithuis, L. O. M. J.: 1990, Prediction of the start of the grass pollen season for the southern part of the Netherlands, Grana, 29(1), 79-86.
data(pollen_count)
df <- subset(pollen_count, site=='Oz')
pollen_season(value=df$birch, date=df$date, method="95")
#> year start end
#> 1 2007 2007-03-31 2007-05-03
#> 2 2008 2008-04-19 2008-05-07
#> 3 2009 2009-04-09 2009-05-09
#> 4 2010 2010-04-14 2010-05-07
#> 5 2011 2011-04-20 2011-05-17
#> 6 2012 2012-04-09 2012-05-14
#> 7 2013 2013-04-09 2013-05-09
#> 8 2014 2014-04-08 2014-05-10
#> 9 2015 2015-04-08 2015-04-30
#> 10 2016 2016-04-06 2016-05-09
df2 <- subset(pollen_count, site=='Atlantis')
pollen_season(value=df2$alder, date=df2$date, method="95")
#> Warning: NA values were found in the input data.
#> year start end
#> 1 2007 <NA> <NA>
#> 2 2008 2008-03-23 2008-04-14
#> 3 2009 2009-03-16 2009-04-03
#> 4 2010 2010-03-26 2010-04-07
#> 5 2011 2011-03-28 2011-04-14
#> 6 2012 2012-02-13 2012-04-05
#> 7 2013 2013-02-05 2013-03-16
#> 8 2014 2014-02-11 2014-04-29
#> 9 2015 2015-03-19 2015-04-04
#> 10 2016 2016-03-14 2016-04-23
library('purrr')
pollen_count %>% split(., .$site) %>%
map_df(~pollen_season(value=.$hazel, date=.$date, method="95"), .id="site")
#> site year start end
#> 1 Atlantis 2007 2007-01-29 2007-03-19
#> 2 Atlantis 2008 2008-03-23 2008-04-14
#> 3 Atlantis 2009 2009-03-15 2009-04-11
#> 4 Atlantis 2010 2010-03-24 2010-04-14
#> 5 Atlantis 2011 2011-03-26 2011-04-12
#> 6 Atlantis 2012 2012-01-21 2012-03-26
#> 7 Atlantis 2013 2013-02-02 2013-03-29
#> 8 Atlantis 2014 2014-02-07 2014-04-09
#> 9 Atlantis 2015 2015-03-01 2015-03-30
#> 10 Atlantis 2016 2016-03-11 2016-04-06
#> 11 Hundred Acre Wood 2007 2007-01-29 2007-03-31
#> 12 Hundred Acre Wood 2008 2008-03-10 2008-05-10
#> 13 Hundred Acre Wood 2009 2009-02-08 2009-03-31
#> 14 Hundred Acre Wood 2010 2010-01-24 2010-04-16
#> 15 Hundred Acre Wood 2011 2011-03-25 2011-04-16
#> 16 Hundred Acre Wood 2012 2012-01-10 2012-03-29
#> 17 Hundred Acre Wood 2013 2013-01-24 2013-03-12
#> 18 Hundred Acre Wood 2014 2014-03-04 2014-03-31
#> 19 Hundred Acre Wood 2015 2015-02-26 2015-03-31
#> 20 Hundred Acre Wood 2016 2016-02-06 2016-03-31
#> 21 Oz 2007 2007-02-03 2007-03-18
#> 22 Oz 2008 2008-03-10 2008-04-03
#> 23 Oz 2009 2009-02-17 2009-03-26
#> 24 Oz 2010 2010-03-18 2010-04-10
#> 25 Oz 2011 2011-03-27 2011-04-13
#> 26 Oz 2012 2012-01-12 2012-03-14
#> 27 Oz 2013 2013-01-22 2013-03-25
#> 28 Oz 2014 2014-03-05 2014-04-05
#> 29 Oz 2015 2015-03-19 2015-04-02
#> 30 Oz 2016 2016-03-10 2016-03-30
#> 31 Shire 2007 2007-01-28 2007-03-24
#> 32 Shire 2008 2008-02-22 2008-04-01
#> 33 Shire 2009 2009-02-03 2009-03-27
#> 34 Shire 2010 2010-02-07 2010-04-07
#> 35 Shire 2011 2011-02-20 2011-04-12
#> 36 Shire 2012 2012-01-10 2012-03-18
#> 37 Shire 2013 2013-01-21 2013-03-02
#> 38 Shire 2014 2014-03-01 2014-03-27
#> 39 Shire 2015 2015-02-19 2015-03-30
#> 40 Shire 2016 2016-01-17 2016-03-28