This function plots back trajectories on a `leaflet`

map. This function
requires that data are imported using the `openair::importTraj()`

function.

## Usage

```
trajLevelMap(
data,
longitude = "lon",
latitude = "lat",
pollutant,
control = "default",
smooth = FALSE,
statistic = "frequency",
percentile = 90,
lon.inc = 1,
lat.inc = 1,
min.bin = 1,
.combine = NA,
sigma = 1.5,
cols = "default",
alpha = 0.5,
tile.border = NA,
provider = "OpenStreetMap"
)
```

## Arguments

- data
Data frame, the result of importing a trajectory file using

`openair::importTraj()`

.- latitude, longitude
The decimal latitude/longitude.

- pollutant
Pollutant to be plotted. By default the trajectory height is used.

- control
Used for splitting the trajectories into different groups which can be selected between using a "layer control" menu. Passed to

`openair::cutData()`

.- smooth
Should the trajectory surface be smoothed? Defaults to

`FALSE`

. Note that, when`smooth = TRUE`

, no popup information will be available.- statistic
Statistic to use for

`trajLevel()`

. By default, the function will plot the trajectory frequencies (`statistic = "frequency"`

). As an alternative way of viewing trajectory frequencies, the argument`method = "hexbin"`

can be used. In this case hexagonal binning of the trajectory*points*(i.e., a point every three hours along each back trajectory). The plot then shows the trajectory frequencies uses hexagonal binning.There are also various ways of plotting concentrations.

It is possible to set

`statistic = "difference"`

. In this case trajectories where the associated concentration is greater than`percentile`

are compared with the the full set of trajectories to understand the differences in frequencies of the origin of air masses. The comparison is made by comparing the percentage change in gridded frequencies. For example, such a plot could show that the top 10\ tend to originate from air-mass origins to the east.If

`statistic = "pscf"`

then a Potential Source Contribution Function map is produced. This statistic method interacts with`percentile`

.If

`statistic = "cwt"`

then concentration weighted trajectories are plotted.If

`statistic = "sqtba"`

then Simplified Quantitative Transport Bias Analysis is undertaken. This statistic method interacts with`.combine`

and`sigma`

.- percentile
The percentile concentration of

`pollutant`

against which the all trajectories are compared.- lon.inc, lat.inc
The longitude and latitude intervals to be used for binning data.

- min.bin
The minimum number of unique points in a grid cell. Counts below

`min.bin`

are set as missing.- .combine
When statistic is "SQTBA" it is possible to combine lots of receptor locations to derive a single map.

`.combine`

identifies the column that differentiates different sites (commonly a column named`"site"`

). Note that individual site maps are normalised first by dividing by their mean value.- sigma
For the SQTBA approach

`sigma`

determines the amount of back trajectory spread based on the Gaussian plume equation. Values in the literature suggest 5.4 km after one hour. However, testing suggests lower values reveal source regions more effectively while not introducing too much noise.- cols
Colours to be used for plotting. Options include "default", "increment", "heat", "turbo" 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`grDevices::colours()`

to see the full list). An example would be`cols = c("yellow", "green", "blue")`

.- alpha
Opacity of the tiles. Must be between

`0`

and`1`

.- tile.border
Colour to use for the border of binned tiles. Defaults to

`NA`

, which draws no border.- provider
The base map to be used. See http://leaflet-extras.github.io/leaflet-providers/preview/ for a list of all base maps that can be used.

## See also

the original `openair::trajLevel()`

`trajLevelMapStatic()`

for the static `ggplot2`

equivalent of `trajLevelMap()`

Other interactive trajectory maps:
`trajMap()`