trajCluster: Calculate clusters for back trajectories

In openair: Tools for the Analysis of Air Pollution Data

Calculate clusters for back trajectories

Description

This function carries out cluster analysis of HYSPLIT back trajectories. The function is specifically designed to work with the trajectories imported using the openair importTraj function, which provides pre-calculated back trajectories at specific receptor locations.

Usage

trajCluster(
  traj,
  method = "Euclid",
  n.cluster = 5,
  type = "default",
  cols = "Set1",
  split.after = FALSE,
  map.fill = TRUE,
  map.cols = "grey40",
  map.alpha = 0.4,
  projection = "lambert",
  parameters = c(51, 51),
  orientation = c(90, 0, 0),
  by.type = FALSE,
  origin = TRUE,
  plot = TRUE,
  ...
)

Arguments

traj	An openair trajectory data frame resulting from the use of importTraj.
method	Method used to calculate the distance matrix for the back trajectories. There are two methods available: “Euclid” and “Angle”.
n.cluster	Number of clusters to calculate.
type	type determines how the data are split i.e. conditioned, and then plotted. The default is will produce a single plot using the entire data. Type can be one of the built-in types as detailed in cutData e.g. “season”, “year”, “weekday” and so on. For example, type = "season" will produce four plots — one for each season. Note that the cluster calculations are separately made of each level of "type".
cols	Colours to be used for plotting. Options include “default”, “increment”, “heat”, “jet” and RColorBrewer colours — see the openair openColours function for more details. For user defined the user can supply a list of colour names recognised by R (type colours() to see the full list). An example would be cols = c("yellow", "green", "blue")
split.after	For type other than “default” e.g. “season”, the trajectories can either be calculated for each level of type independently or extracted after the cluster calculations have been applied to the whole data set.
map.fill	Should the base map be a filled polygon? Default is to fill countries.
map.cols	If map.fill = TRUE map.cols controls the fill colour. Examples include map.fill = "grey40" and map.fill = openColours("default", 10). The latter colours the countries and can help differentiate them.
map.alpha	The transparency level of the filled map which takes values from 0 (full transparency) to 1 (full opacity). Setting it below 1 can help view trajectories, trajectory surfaces etc. and a filled base map.
projection	The map projection to be used. Different map projections are possible through the mapproj package. See ?mapproject for extensive details and information on setting other parameters and orientation (see below).
parameters	From the mapproj package. Optional numeric vector of parameters for use with the projection argument. This argument is optional only in the sense that certain projections do not require additional parameters. If a projection does not require additional parameters then set to null i.e. parameters = NULL.
orientation	From the mapproj package. An optional vector c(latitude, longitude, rotation) which describes where the "North Pole" should be when computing the projection. Normally this is c(90, 0), which is appropriate for cylindrical and conic projections. For a planar projection, you should set it to the desired point of tangency. The third value is a clockwise rotation (in degrees), which defaults to the midrange of the longitude coordinates in the map.
by.type	The percentage of the total number of trajectories is given for all data by default. Setting by.type = TRUE will make each panel add up to 100.
origin	If true a filled circle dot is shown to mark the receptor point.
plot	Should a plot be produced? FALSE can be useful when analysing data to extract plot components and plotting them in other ways.
...	Other graphical parameters passed onto lattice:levelplot and cutData. Similarly, common axis and title labelling options (such as xlab, ylab, main) are passed to levelplot via quickText to handle routine formatting.

Details

Two main methods are available to cluster the back trajectories using two different calculations of the distance matrix. The default is to use the standard Euclidian distance between each pair of trajectories. Also available is an angle-based distance matrix based on Sirois and Bottenheim (1995). The latter method is useful when the interest is the direction of the trajectories in clustering.

The distance matrix calculations are made in C++ for speed. For data sets of up to 1 year both methods should be relatively fast, although the method = "Angle" does tend to take much longer to calculate. Further details of these methods are given in the openair manual.

Value

an openair object. The data component contains both traj (the original data appended with its cluster) and results (the average trajectory path per cluster, shown in the trajCluster() plot.)

Author(s)

David Carslaw

References

Sirois, A. and Bottenheim, J.W., 1995. Use of backward trajectories to interpret the 5-year record of PAN and O3 ambient air concentrations at Kejimkujik National Park, Nova Scotia. Journal of Geophysical Research, 100: 2867-2881.

See Also

Other trajectory analysis functions: importTraj(), trajLevel(), trajPlot()

Other cluster analysis functions: polarCluster(), timeProp()

Examples

## Not run: 
## import trajectories
traj <- importTraj(site = "london", year = 2009)
## calculate clusters
clust <- trajCluster(traj, n.cluster = 5)
head(clust$data) ## note new variable 'cluster'
## use different distance matrix calculation, and calculate by season
traj <- trajCluster(traj, method = "Angle", type = "season", n.cluster = 4)

## End(Not run)

openair documentation built on May 29, 2024, 11:07 a.m.