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Create thematic maps for indicators

Source: R/visualization.R
plot_indicators_map.Rd

Generates publication-ready maps visualizing indicator values across spatial units.

Usage

plot_indicators_map(
  data,
  indicators = NULL,
  palette = c("viridis", "RdYlGn", "YlOrRd", "Greens", "Blues"),
  direction = 1,
  title = NULL,
  legend_title = NULL,
  breaks = NULL,
  labels = NULL,
  alpha = 0.9,
  border_color = "white",
  border_size = 0.3,
  facet = TRUE,
  ncol = 2,
  base_size = 11
)

Arguments

data

An sf object with indicator values

indicators

Character vector of indicator column names to plot. If NULL and multiple indicators present, creates faceted plot.

palette

Character. Color palette to use. Options:

  • "viridis" - Perceptually uniform, colorblind-friendly (default)

  • "RdYlGn" - Red-Yellow-Green diverging (low-medium-high)

  • "YlOrRd" - Yellow-Orange-Red sequential

  • "Greens" - Green sequential

  • "Blues" - Blue sequential

direction

Numeric. Direction of color scale: 1 (default) or -1 (reversed)

title

Character. Plot title. If NULL, auto-generated.

legend_title

Character. Legend title. If NULL, uses "Value" or indicator name.

breaks

Numeric vector. Manual breaks for color scale. If NULL, automatic.

labels

Character vector. Labels for breaks. Same length as breaks.

alpha

Numeric. Transparency (0-1). Default 0.9.

border_color

Character. Border color for polygons. Default "white".

border_size

Numeric. Border line width. Default 0.3.

facet

Logical. Create faceted plot for multiple indicators? Default TRUE.

ncol

Integer. Number of columns for faceted plot. Default 2.

base_size

Numeric. Base font size for theme. Default 11.

Value

A ggplot object

Details

Creates thematic choropleth maps using ggplot2. Supports:

  • Single indicator maps

  • Multi-indicator faceted maps

  • Custom color palettes

  • Flexible styling

The function uses geom_sf() for spatial rendering and applies perceptually uniform color scales by default (viridis).

Examples

if (FALSE) { # \dontrun{
# Single indicator map
plot_indicators_map(
  results,
  indicators = "carbon",
  palette = "Greens",
  title = "Carbon Stock Distribution"
)

# Multiple indicators (faceted)
plot_indicators_map(
  normalized,
  indicators = c("carbon_norm", "biodiversity_norm", "water_norm"),
  palette = "viridis",
  facet = TRUE,
  ncol = 3
)

# Composite index with custom breaks
plot_indicators_map(
  results,
  indicators = "ecosystem_health",
  palette = "RdYlGn",
  breaks = c(0, 25, 50, 75, 100),
  labels = c("Low", "Medium-Low", "Medium-High", "High", "Very High")
)
} # }