diff --git a/examples/gallery/images/rgb_image.py b/examples/gallery/images/rgb_image.py
new file mode 100644
index 00000000000..9d9506b2ffb
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+++ b/examples/gallery/images/rgb_image.py
@@ -0,0 +1,40 @@
+"""
+RGB Image
+---------
+The :meth:`pygmt.Figure.grdimage` method can be used to plot Red, Green, Blue
+(RGB) images, or any 3-band false color combination. Here, we'll use
+:py:func:`rioxarray.open_rasterio` to read a GeoTIFF file into an
+:class:`xarray.DataArray` format, and plot it on a map.
+
+The example below shows a Worldview 2 satellite image over
+`Lāhainā, Hawaiʻi during the August 2023 wildfires
+<https://en.wikipedia.org/wiki/2023_Hawaii_wildfires#L%C4%81hain%C4%81>`_.
+Data is sourced from a Cloud-Optimized GeoTIFF (COG) file hosted on
+`OpenAerialMap <https://map.openaerialmap.org>`_ under a
+`CC BY-NC 4.0 <https://creativecommons.org/licenses/by-nc/4.0/>`_ license.
+"""
+import pygmt
+import rioxarray
+
+###############################################################################
+# Read 3-band data from GeoTIFF into an xarray.DataArray object:
+with rioxarray.open_rasterio(
+    filename="https://oin-hotosm.s3.us-east-1.amazonaws.com/64d6a49a19cb3a000147a65b/0/64d6a49a19cb3a000147a65c.tif",
+    overview_level=5,
+) as img:
+    # Subset to area of Lāhainā in EPSG:32604 coordinates
+    image = img.rio.clip_box(minx=738000, maxx=755000, miny=2300000, maxy=2318000)
+    image = image.load()  # Force loading the DataArray into memory
+image
+
+###############################################################################
+# Plot the RGB imagery:
+fig = pygmt.Figure()
+with pygmt.config(FONT_TITLE="Times-Roman"):  # Set title font to Times-Roman
+    fig.grdimage(
+        grid=image,
+        # Use a map scale where 1 cm on the map equals 1 km on the ground
+        projection="x1:100000",
+        frame=[r"WSne+tL@!a¯hain@!a¯, Hawai`i on 9 Aug 2023", "af"],
+    )
+fig.show()