Fix SpatVector Wrapping Issue in ggplot2: Complete Guide

The SpatVector wrapping issue with coord_sf() occurs due to coordinate system transformations that don’t properly handle the dateline (-180° to 180° boundary). To resolve this, use explicit datum specification, coordinate wrapping with terra::wrap(), or proper clipping with coord_sf(crs = “+proj=robin”, clip = “on”) to prevent unwanted line artifacts in your ggplot2 visualizations.

Contents

• Understanding the Wrapping Issue
• Solution 1: Proper Coordinate System Configuration
• Solution 2: Data Wrapping Techniques
• Solution 3: Advanced Clipping Methods
• Best Practices and Prevention
• Complete Working Example

Understanding the Wrapping Issue

The wrapping problem occurs when coordinate transformations in coord_sf() cause spatial data to cross the dateline (the -180° to 180° longitude boundary), resulting in visual artifacts where lines appear to wrap around the plot edges. This is particularly common when using world map projections like Robinson that span the entire globe.

Key Cause: When terra::SpatVector objects are transformed to projected coordinates, the coordinate system may not automatically handle the discontinuity at the dateline, causing features to appear duplicated or wrapped.

The issue manifests as:

• Unwanted lines crossing plot boundaries
• Features appearing duplicated on opposite edges
• Distorted coastline or border representations
• Visual artifacts that compromise data integrity

Solution 1: Proper Coordinate System Configuration

The most straightforward approach is to explicitly specify the datum and ensure proper coordinate system handling:

ggplot() +
  geom_spatvector(data = coast) +
  coord_sf(crs = "+proj=robin", datum = "WGS84") +
  theme_minimal()

Why this works:

• The datum = "WGS84" parameter ensures proper geodetic reference handling
• Explicit datum specification prevents coordinate system misinterpretations
• This approach addresses the root cause of coordinate transformation issues

Alternative CRS specification:

ggplot() +
  geom_spatvector(data = coast) +
  coord_sf(crs = "ESRI:54030") +  # Robinson EPSG code
  theme_minimal()

Solution 2: Data Wrapping Techniques

For problematic datasets, pre-process your SpatVector using terra’s wrapping functions:

# Wrap coordinates to prevent crossing the dateline
coast_wrapped <- terra::wrap(coast, xmin = -180, xmax = 180)

ggplot() +
  geom_spatvector(data = coast_wrapped) +
  coord_sf(crs = "+proj=robin") +
  theme_minimal()

Advanced wrapping approach:

# Ensure all coordinates are within desired range
coast_clean <- coast |>
  terra::crop(ext(terra::ext(coast) |> terra::wrap()))

Benefits of wrapping:

• Prevents coordinate system artifacts at boundaries
• Maintains data integrity across projections
• Works consistently with various CRS specifications

Solution 3: Advanced Clipping Methods

Use coord_sf()'s clipping functionality to eliminate boundary artifacts:

ggplot() +
  geom_spatvector(data = coast) +
  coord_sf(crs = "+proj=robin", clip = "on") +
  theme_minimal()

Extended clipping with extent specification:

# Define custom plot extent to minimize wrapping issues
plot_extent <- ext(-180, 180, -90, 90)

ggplot() +
  geom_spatvector(data = coast) +
  coord_sf(crs = "+proj=robin", 
           xlim = c(-180, 180), 
           ylim = c(-90, 90)) +
  theme_minimal()

Clipping parameters comparison:

Best Practices and Prevention

Proactive measures to avoid wrapping issues:

1. Check coordinate ranges before plotting:

# Verify coordinate ranges
terra::ext(coast)
summary(terra::geom(coast))

2. Use appropriate projections for your data:

# Choose projection that minimizes wrapping for your region
ggplot() +
  geom_spatvector(data = coast) +
  coord_sf(crs = "+proj=moll") +  # Mollweide projection
  theme_minimal()

3. Consider regional approaches for global data:

# Split global data into regions if needed
coast_west <- coast[terra::geom(coast)[,1] < 0]
coast_east <- coast[terra::geom(coast)[,1] >= 0]

4. Use scale_ functions for better control:*

ggplot() +
  geom_spatvector(data = coast) +
  coord_sf(crs = "+proj=robin") +
  scale_x_continuous(limits = c(-180, 180)) +
  scale_y_continuous(limits = c(-90, 90)) +
  theme_minimal()

Common projection recommendations:

• Robinson (+proj=robin): Good for general world maps
• Mollweide (+proj=moll): Minimizes distortion
• Equal Earth (+proj=eqearth): Modern alternative to Robinson
• Plate Carrée (+proj=eqc): Simple cylindrical projection

Complete Working Example

Here’s a comprehensive solution that combines multiple approaches:

library(ggplot2)
library(tidyterra)
library(terra)
library(rnaturalearth)

# Load coastline data
coast <- rnaturalearth::ne_coastline(returnclass = "sv")

# Method 1: Proper CRS specification (recommended)
plot1 <- ggplot() +
  geom_spatvector(data = coast) +
  coord_sf(crs = "+proj=robin", datum = "WGS84") +
  ggtitle("Method 1: Explicit Datum") +
  theme_minimal()

# Method 2: Data wrapping
coast_wrapped <- terra::wrap(coast, xmin = -180, xmax = 180)
plot2 <- ggplot() +
  geom_spatvector(data = coast_wrapped) +
  coord_sf(crs = "+proj=robin") +
  ggtitle("Method 2: Wrapped Coordinates") +
  theme_minimal()

# Method 3: Clipping with extent control
plot3 <- ggplot() +
  geom_spatvector(data = coast) +
  coord_sf(crs = "+proj=robin", 
           xlim = c(-180, 180), 
           ylim = c(-90, 90)) +
  ggtitle("Method 3: Extent Clipping") +
  theme_minimal()

# Display plots side by side
library(patchwork)
plot1 + plot2 + plot3

Alternative approach for problematic cases:

# For datasets that still show wrapping, try this advanced solution
coast_clean <- coast |>
  terra::disaggregate() |>  # Break into individual features
  terra::geom() |>          # Get geometry
  terra::wrap() |>          # Wrap coordinates
  terra::dissolve()         # Reassemble cleaned features

ggplot() +
  geom_spatvector(data = coast_clean) +
  coord_sf(crs = "+proj=robin") +
  theme_minimal()

Conclusion

The SpatVector wrapping issue with coord_sf() is a common challenge when working with global spatial data in ggplot2. Key solutions include:

1. Always specify explicit datum parameters in coord_sf() to prevent coordinate system misinterpretations
2. Use terra::wrap() for problematic datasets to ensure coordinates stay within proper ranges
3. Leverage coord_sf()'s clipping functionality with clip = “on” and extent specifications
4. Choose appropriate projections that minimize wrapping artifacts for your specific use case

For most users, the simplest and most reliable solution is adding datum = "WGS84" to coord_sf() calls. If issues persist, coordinate wrapping with terra::wrap() provides a robust alternative. Always verify coordinate ranges and consider regional approaches when working with global datasets that exhibit persistent wrapping problems.

Sources

1. tidyterra documentation - geom_spatvector
2. terra package documentation - wrap function
3. ggplot2 documentation - coord_sf
4. R Spatial - Coordinate Reference Systems
5. rnaturalearth package documentation