R
Oceanography
Data Visualization
Published

April 20, 2025

1. Plotting Coastlines and Simple Maps with oce

The oce package includes a built-in coastlineWorld dataset, which we can use to create a basic global map.

Code

Load data

Code
# Load built-in coastline data  
data("coastlineWorld")  

# Plot the world coastline  
plot(coastlineWorld, col = "darkblue", main = "Global Coastline")

Adding Bathymetry (Optional)

If you have bathymetry data (e.g., from ETOPO1), you can overlay it:

Code
# Example: Simulated depth data (in practice, load real bathymetry)  
lon <- seq(-180, 180, by = 5)  
lat <- seq(-90, 90, by = 5)  
depth <- outer(lon, lat, function(x, y) -5000 * cos(x/50) * sin(y/50)) # Mock data  

# Plot  
imagep(lon, lat, depth, col = oceColorsTurbo,  
       xlab = "Longitude", ylab = "Latitude",  
       main = "Simulated Ocean Depth (m)")  
plot(coastlineWorld, add = TRUE, col = "black")

World map with bathymetry contours

Global map with simplified bathymetry contours.

2. Advanced Ocean Maps with ggplot2

For more customization, we can use ggplot2 with oce data.

A. Plotting Coastlines with ggplot2

Code
library(ggplot2)  

# Convert oce coastline to a data frame  
coast_df <- data.frame(  
  lon = coastlineWorld[["longitude"]],  
  lat = coastlineWorld[["latitude"]]  
) 

# ignore the warning message

ggplot(coast_df, aes(x = lon, y = lat)) +  
  geom_path(color = "navy", linewidth = 0.3) +  
  labs(title = "Global Coastline", x = "Longitude", y = "Latitude") +  
  theme_minimal()

World coastline in ggplot2

Global coastline plotted using ggplot2.

B. Adding Oceanographic Data (Example: Temperature Gradient)

If you have a temperature dataset (e.g., from a CSV or NetCDF file), you can visualize it like this:

Code
# Create simulated temperature data
set.seed(123)
temp_data <- expand.grid(
  lon = seq(-180, 180, by = 10),
  lat = seq(-90, 90, by = 10)
)
temp_data$temp <- with(temp_data, 20 + 10 * cos(lat/30) * sin(lon/30))

# Plot with proper layer separation
ggplot() +
  geom_tile(data = temp_data, aes(x = lon, y = lat, fill = temp)) +
  geom_path(data = coast_df, aes(x = lon, y = lat), color = "black") +
  scale_fill_viridis_c(name = "Temperature (°C)") +
  labs(title = "Simulated Sea Surface Temperature", 
       x = "Longitude", y = "Latitude") +
  theme_minimal()

Simulated SST map with ggplot2

Example temperature gradient visualization.