Choropleth visualisation

Introduction

This vignette shows how polygon data included in spatialrisk can be used to display aggregated values. The emphasis is on reporting and visualisation after a spatial aggregation step.

Choropleth maps are useful for showing variation across administrative areas. They should not be interpreted as a substitute for fixed-radius concentration analysis on point-level data.

Data

library(spatialrisk)
library(sf)
library(dplyr)

data(nl_gemeente)

The object nl_gemeente contains municipal geometries for the Netherlands as a simple feature object. For illustration, we create a small table with one value per municipality. In applied work, this table would typically contain observed or modelled values aggregated at municipality level.

set.seed(1)
municipality_values <- nl_gemeente |>
  st_drop_geometry() |>
  select(id, code, areaname) |>
  mutate(value = runif(n(), min = 0, max = 100))

Join values to geometries

The values are joined back to the municipal geometries before plotting.

map_data <- nl_gemeente |>
  left_join(municipality_values, by = c("id", "code", "areaname"))

Choropleth map

The choropleth() function uses tmap. The id argument identifies the column used for polygon labels in interactive maps.

choropleth(
  map_data,
  value = "value",
  id = "areaname",
  legend_title = "Value"
)

Relation to concentration analysis

A choropleth map represents values attached to predefined polygons. Fixed-radius concentration analysis answers a different question: what is the total value within a circle of a specified radius around a possible centre?

In insurance applications, both views can be useful. The fixed-radius calculation identifies local accumulation of exposure, while the choropleth map can be used to communicate summaries by municipality, province, or another reporting unit.

Summary

This vignette demonstrated how to:

• use an included simple feature object;
• join aggregated values to polygon geometries;
• create a choropleth map for reporting.