diff --git a/book/geospatial/rasterio.ipynb b/book/geospatial/rasterio.ipynb
index e43b990..f816c43 100644
--- a/book/geospatial/rasterio.ipynb
+++ b/book/geospatial/rasterio.ipynb
@@ -480,9 +480,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "red_band = src.read(1)\n",
+    "elev_band = src.read(1)\n",
     "plt.figure(figsize=(8, 8))\n",
-    "plt.imshow(red_band, cmap=\"terrain\")\n",
+    "plt.imshow(elev_band, cmap=\"terrain\")\n",
     "plt.colorbar(label=\"Elevation (meters)\", shrink=0.5)\n",
     "plt.title(\"DEM with Terrain Colormap\")\n",
     "plt.show()"
@@ -1349,7 +1349,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.2"
+   "version": "3.11.8"
   }
  },
  "nbformat": 4,
diff --git a/book/geospatial/rasterio.md b/book/geospatial/rasterio.md
index a424f08..9529188 100644
--- a/book/geospatial/rasterio.md
+++ b/book/geospatial/rasterio.md
@@ -241,9 +241,9 @@ When visualizing raster data, colormaps help map pixel values to colors, while c
 Let's read the first band and plot it with a colormap:
 
 ```{code-cell} ipython3
-red_band = src.read(1)
+elev_band = src.read(1)
 plt.figure(figsize=(8, 8))
-plt.imshow(red_band, cmap="terrain")
+plt.imshow(elev_band, cmap="terrain")
 plt.colorbar(label="Elevation (meters)", shrink=0.5)
 plt.title("DEM with Terrain Colormap")
 plt.show()