openairmaps: tools to create maps of air pollution data the openairmaps logo. It shows a stylised pollution rose overlaid with a typical teardrop shaped map marker.

R-CMD-check CRAN status

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.

Installation

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")

Overview

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 %>%
  openair::cutData("daylight") %>%
  buildPopup(
    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"
  )
A screenshot of a leaflet map. It shows an OpenStreetMap map layer, overlaid with bivariate polar plots. Polar plots are visualisations on polar coordinates with wind direction on the spoke axes, wind speed on the radial axes, and a smooth surface showing pollutant concentrations. A menu is found at the top-right of the map, which allows users to swap between daylight and nighttime observations.

An example polarMap() showing NO2 concentrations in central London.

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().

Static maps require users to provide a ggmap tileset, which at the time of writing requires an API key for either Google or Stadia Maps.