Rotating 360 Degree Rasters To 180 Degrees With R

The Problem: Rasters Displayed Incorrectly

Rasters containing geographic data often need to be displayed with a specific orientation for visualization or analysis. However, rasters generated from various sources may not aligned properly when loaded into R. A common issue is a raster that spans the 180 degree longitude line having an inappropriate 360 degree orientation. When plotted in R, this raster appears distorted or wraps inappropriately across the date line. To correctly display the data across the 180 line, the raster needs to be rotated 180 degrees.

Understanding Coordinate Systems and Transformations

Rasters contain grids of cells encoded with values. To map the cell locations, rasters rely on coordinate reference systems. Typically, geographic rasters use longitude/latitude. In longitude/latitude, the 180 degree longitude line demarcates East vs West hemispheres. Rasters using 360 degree systems encode longitude values from 0 to 360 degrees. 180 degree systems run from -180 to 180 degrees. Plotting 360 degree rasters in R’s default 180 degree layout causes visible distortions. Rotating the raster to a 180 system best aligns cell locations.

Loading a Raster Dataset

Before rotating, the target raster must be loaded into R’s memory. This uses the raster package’s brick function to import the file and store it as a RasterBrick object. The input file can use formats like GeoTIFF, NetCDF, GRIB and many others supported by GDAL. Here is example code loading a 360 degree GeoTIFF raster named my_raster.tif:

r <- brick("my_raster.tif")

Checking the Raster's Current Projection

Once loaded, print the raster's projection information to confirm the current coordinate reference system. The projection should indicate the raster is geographic using WGS 84 longitude/latitude coordinates. Additionally, check that the extent spans 0 to 360 degrees longitude, confirming the raster is currently stored in a 360 system. Example code to print the projection metadata:


Defining the Target Projection

Now define the desired 180 degree longitude target projection. This uses the CRS function to generate a coordinate reference system object centered on the date line. Passing the created CRS object to projectRaster will rotate the raster dataset. Here the CRS is created then displayed:

crs_180 = CRS("+proj=longlat +datum=WGS84") 

Performing the Rotation

The projectRaster function handles rotating the raster to the 180 degree CRS. Input the RasterBrick, the target CRS, rotation direction, and alignment method. The rotation direction should point from the center of the current extent to the center of the target projection. Here the center points are -180 degrees (180 system center) and 180 degrees (360 system center), requiring a 180 degree rotation. The rotation alignment uses the center cell center method:

r_rot = projectRaster(r, crs=crs_180, rotation=180, align=c("center","center"))

Example Code for 180 Degree Rotation

Combining the steps, this R code loads a raster, checks the initial projection, defines the 180 degree target CRS, rotates 180 degrees, and saves the output:


r = brick("my_raster.tif")

crs_180 = CRS("+proj=longlat +datum=WGS84")

r_rot = projectRaster(r, crs=crs_180, rotation=180, 

writeRaster(r_rot, "my_raster_rot.tif") 

Verifying the New Projection

Print the projection metadata of the rotated raster to verify the coordinate reference system changed to the 180 degree system. The extent should now span -180 to 180 degrees longitude. Additionally, visually check that data displays properly in R plots.


Visualizing the Rotated Raster

With an appropriate 180 degree projection, the rotated raster will display properly in R. Create maps and plots using various R graphics functions like plot, image, levelplot and spplot. Adjust scaling parameters, color palettes and plot dimensions as needed to best visualize the raster. The raster cells should now map correctly across the date line.

image(r_rot, col = topo.colors(100)) 

Alternative Approaches

The projectRaster method provides a simple raster rotation workflow in R. However, other options exist like the warp function from the rgdal package. Warp offers more control points and alignment methods at the cost of additional complexity. Another option is processing the rotation externally from R in GIS software then loading the aligned raster. Handling the rotation outside R simplifies the code.

Common Issues and Solutions

When rotating rasters, check for these common problems:

- Incorrect rotation direction: Try the opposite direction eg. from 180 to -180 degrees.
- Aliased borders and edges: Modify the rotation method's resample algorithm.
- Missing data after rotation: Expand raster canvas area to prevent clipping.
- Large file sizes: Reduce resolution if analysis allows.

Testing different rotation alignments and output cell sizes can also help troubleshoot display issues.


This covers a workflow for rotating 360 degree geographic rasters to a proper 180 degree layout for display across the date line in R. By defining a 180 degree CRS then projecting datasets using projectRaster, latitude/longitude rasters can be properly oriented. Check the code examples for handling typical raster rotation scenarios in your workflows. Proper transformations are key prior to visualizing and analyzing geographic rasters in R.

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