Adding_Basic

library(ggmapcn)
#> Loading required package: ggplot2
# Define Azimuthal Equidistant projection centered on China
china_proj <- "+proj=aeqd +lat_0=35 +lon_0=105 +ellps=WGS84 +units=m +no_defs"

Introduction

The ggmapcn package provides various tools for visualizing geographic data in China and beyond. This vignette demonstrates the basic and advanced usage of geom_mapcn() and geom_world() for plotting administrative boundaries and combining geographic data.

Example 1: Basic Map of China

To draw a simple map of China with provincial boundaries, use geom_mapcn(). By default, it uses an Azimuthal Equidistant projection centered on China.

ggplot() +
  geom_mapcn() +
  geom_boundary_cn() +
  theme_bw()

Basic Map

Example 2: Adding Buffer Zones and Coastlines

This example illustrates how to layer multiple geographic features—such as mainland buffers, coastlines, and administrative boundaries—onto a single map.

ggplot() +
  geom_buffer_cn(mainland_dist = 40000) +
  geom_buffer_cn(mainland_dist = 20000, fill = "#BBB3D8") +
  geom_mapcn(fill = "white") +
  geom_boundary_cn() +
  theme_bw()
#> Warning: attribute variables are assumed to be spatially constant throughout
#> all geometries
#> Warning: attribute variables are assumed to be spatially constant throughout
#> all geometries

Map of China

Example 3: Adding Spatial Point Data

The geom_loc function allows you to overlay spatial point data onto your map. It supports both sf objects and data frames containing longitude and latitude columns, and can map aesthetics like color to categorical variables.

# Create a ggplot with spatial points colored by 'Category'
set.seed(123)
data_sim <- data.frame(
   Longitude = runif(100, 80, 120),
   Latitude = runif(100, 28, 40),
   Category = sample(c("Type A", "Type B", "Type C"), 100, replace = TRUE)
   )
ggplot() +
   geom_boundary_cn() +
   geom_loc(
     data = data_sim, lon = "Longitude", lat = "Latitude",
     mapping = aes(color = Category), size = 1, alpha = 0.7
   ) +
   theme_bw()

Sample site

Example 4: basemap_vege: Vegetation Map of China Layer for ggplot2

Before using the function, ensure that the necessary data files are available by running:

# This function checks if the required data files are available
# It may take some time, especially if your network connection is slow.
  check_geodata(files = c("vege_1km_projected.tif"), quiet = FALSE)

The basemap_vege function adds a vegetation raster map of China with color-coded vegetation types to a ggplot.

# Add vegetation raster of China to a ggplot
ggplot() +
  basemap_vege() +
  guides(fill = guide_none()) +
  theme_bw()

Example 5: basemap_dem: Elevation Map of China Layer for ggplot2

The basemap_dem function adds a digital elevation model (DEM) raster map of China as a layer to ggplot2.

# Apply Azimuthal Equidistant projection centered on China
ggplot() +
  basemap_dem(crs = china_proj, within_china = TRUE) +
  geom_boundary_cn(crs = china_proj) +
  tidyterra::scale_fill_hypso_c(
    palette = "dem_print",
    breaks = c(0, 2000, 4000, 6000),
    limits = c(0, 7000)
  ) +
  labs(fill = "Elevation (m)") +
  theme_minimal() +
  theme(legend.position = "bottom")
#> <SpatRaster> resampled to 1000968 cells.

Elevation Map of China

Example 6: coord_proj: Transforming Limits for Custom Projections

The coord_proj function simplifies working with custom projections. It accepts map limits (xlim, ylim) in standard WGS84 longitude/latitude coordinates and automatically transforms them into the specified CRS.

Here, the Azimuthal Equidistant projection centered on China is applied, with transformed map limits specified in longitude and latitude.

ggplot() +
  geom_mapcn(fill = "white") +
  geom_boundary_cn() +
  coord_proj(
    crs = china_proj,
    xlim = c(60, 140),
    ylim = c(10, 50)
  ) +
  theme_bw()

clip region

Additionally, we can focus the map on the South China Sea Islands. The longitude and latitude range shown here is for demonstration purposes only.

ggplot() +
  geom_mapcn(fill = "white") +
  geom_boundary_cn() +
  theme_bw() +
  coord_proj(
    crs = china_proj,
    expand = FALSE,
    xlim = c(105, 126),
    ylim = c(2, 23)
  )

Naihai