knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%", message = FALSE, warning = FALSE )
The main goal of {openairmaps}
is to combine the robust analytical methods found in {openair}
on a range of dynamic and static maps. Core 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. Static equivalents of most functions are also available for insertion into traditional reports and academic articles.
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("pak") pak::pak("davidcarslaw/openairmaps")
All functions in {openairmaps}
are thoroughly documented. The openairmaps website contains all documentation and a change log of new features. There are also many examples of {openairmaps}
functionality the openair book, which goes into great detail about its various functions.
knitr::include_graphics("man/figures/README-patchwork.png")
{openair}
toolkit{openair}
: Import, analyse, and visualise air quality and atmospheric composition data.
{worldmet}
: Access world meteorological data from NOAA's Integrated Surface Database.
{openairmaps}
: Visualise air quality data on interactive and static maps.
{deweather}
: Use machine learning to remove the effects of meteorology on air quality time series.
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