The main goal of {openairmaps}
is to combine the robust
analytical methods found in openair with the
highly capable {leaflet}
package.
{openairmaps}
is thoroughly documented in the openair
book.
You can install the release version of {openairmaps}
from CRAN with:
install.packages("openairmaps")
You can install the development version of {openairmaps}
from GitHub with:
# install.packages("devtools")
::install_github("davidcarslaw/openairmaps") devtools
library(openairmaps)
The openairmaps
package is thoroughly documented in the
openair
book, which goes into great detail about its various functions.
Functionality includes visualising UK AQ networks
(networkMap()
), putting “polar directional markers” on maps
(e.g., polarMap()
) and overlaying HYSPLIT trajectories on
maps (e.g., trajMap()
), all using the
{leaflet}
package.
%>%
polar_data ::cutData("daylight") %>%
openairbuildPopup(
c("site", "site_type"),
names = c("Site" = "site", "Site Type" = "site_type"),
control = "daylight"
%>%
) polarMap(
pollutant = "no2",
limits = c(0, 180),
control = "daylight",
popup = "popup"
)
While an interactive map is preferred for exploratory directional
analysis, it is limited to the HTML format. Some applications (for
example, academic journals) demand “static” formats like .docx and .pdf.
For this reason, “static” versions of {openairmaps}
polar
marker functions have been provided which are written in
{ggplot2}
. A benefit of being written in
{ggplot2}
is that additional layers can be added (e.g.,
geom_label()
could be used to label sites) and limited
further customisation is available using theme()
and
guides()
.
%>%
polar_data ::cutData("daylight") %>%
openairpolarMapStatic(
pollutant = "no2",
limits = c(0, 180),
facet = "daylight",
alpha = .75,
d.icon = 100,
d.fig = 2.5
)