diff --git a/docs/workshops/EarthCube_2023.ipynb b/docs/workshops/EarthCube_2023.ipynb
index efe60d73e2..2023a405d5 100644
--- a/docs/workshops/EarthCube_2023.ipynb
+++ b/docs/workshops/EarthCube_2023.ipynb
@@ -11,7 +11,7 @@
     "\n",
     "**Interactive Geospatial Analysis and Data Visualization with Leafmap**\n",
     "\n",
-    "This [notebook](https://leafmap.org/workshops/EarthCube_2023) provides an introduction to interactive geospatial analysis and data visualization with leafmap. It is designed for the notebook demo at the [EarthCube 2023](https://isi-usc-edu.github.io/building-upon-the-earthcube-community). "
+    "This [notebook](https://leafmap.org/workshops/EarthCube_2023) provides an introduction to interactive geospatial analysis and data visualization with leafmap. It is designed for the notebook demo at the [EarthCube 2023](https://isi-usc-edu.github.io/building-upon-the-earthcube-community)."
    ]
   },
   {
@@ -20,7 +20,7 @@
    "source": [
     "## Installation\n",
     "\n",
-    "Uncomment and run the following cell to install necessary packages for this notebook. **Restart the kernel/runtime after installation**. "
+    "Uncomment and run the following cell to install necessary packages for this notebook. **Restart the kernel/runtime after installation**."
    ]
   },
   {
@@ -231,6 +231,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "## SpatioTemporal Asset Catalog\n",
+    "\n",
     "The SpatioTemporal Asset Catalog (STAC) specification provides a common language to describe a range of geospatial information so that it can more easily be indexed and discovered. A **SpatioTemporal Asset** is any file that represents information about the earth captured in a certain space and time. STAC aims to enable that next generation of geospatial search engines, while also supporting web best practices so geospatial information is more easily surfaced in traditional search engines. More information about STAC can be found at the [STAC website](https://stacspec.org/). The [STAC Index website](https://stacindex.org/) is a one-stop-shop for discovering STAC catalogs, collections, APIs, software and tools. In this example, we will use the [STAC SPOT Orthoimages of Canada](https://stacindex.org/catalogs/spot-orthoimages-canada-2005)."
    ]
   },
@@ -309,7 +311,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### GeoPandas supported vector format"
+    "### Other vector formats"
    ]
   },
   {
@@ -350,7 +352,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Add points from XY coordinates"
+    "### XY coordinates"
    ]
   },
   {
@@ -467,7 +469,6 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "\n",
     "The image sources (downloadable URLs) are stored in the uuid column of the GeoDataFrame."
    ]
   },
@@ -485,7 +486,6 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "\n",
     "Download all images using the download_files() function."
    ]
   },
@@ -516,7 +516,7 @@
     "m.add_gdf(gdf, layer_name='Footprints')\n",
     "m.add_cog_layer(images[0], nodata=0, name='OpenAerialMap')\n",
     "# m.add_tile_layer(tiles[0], attribution='OpenAerialMap', name='OpenAerialMap')\n",
-    "m\n"
+    "m"
    ]
   },
   {
@@ -543,7 +543,7 @@
    "source": [
     "## AWS Open Data\n",
     "\n",
-    "The [AWS Open Data Program](https://registry.opendata.aws/) hosts a lots of open and public datasets on AWS, including Landsat 8, Sentinel-2, NAIP, and many more. Check out https://github.com/opengeos#data-catalogs for a list of open and public datasets on AWS.\n"
+    "The [AWS Open Data Program](https://registry.opendata.aws/) hosts a lots of open and public datasets on AWS, including Landsat 8, Sentinel-2, NAIP, and many more. Check out https://github.com/opengeos#data-catalogs for a list of open and public datasets on AWS."
    ]
   },
   {
@@ -867,18 +867,6 @@
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.9"
   }
  },
  "nbformat": 4,
diff --git a/examples/workshops/EarthCube_2023.ipynb b/examples/workshops/EarthCube_2023.ipynb
index efe60d73e2..2023a405d5 100644
--- a/examples/workshops/EarthCube_2023.ipynb
+++ b/examples/workshops/EarthCube_2023.ipynb
@@ -11,7 +11,7 @@
     "\n",
     "**Interactive Geospatial Analysis and Data Visualization with Leafmap**\n",
     "\n",
-    "This [notebook](https://leafmap.org/workshops/EarthCube_2023) provides an introduction to interactive geospatial analysis and data visualization with leafmap. It is designed for the notebook demo at the [EarthCube 2023](https://isi-usc-edu.github.io/building-upon-the-earthcube-community). "
+    "This [notebook](https://leafmap.org/workshops/EarthCube_2023) provides an introduction to interactive geospatial analysis and data visualization with leafmap. It is designed for the notebook demo at the [EarthCube 2023](https://isi-usc-edu.github.io/building-upon-the-earthcube-community)."
    ]
   },
   {
@@ -20,7 +20,7 @@
    "source": [
     "## Installation\n",
     "\n",
-    "Uncomment and run the following cell to install necessary packages for this notebook. **Restart the kernel/runtime after installation**. "
+    "Uncomment and run the following cell to install necessary packages for this notebook. **Restart the kernel/runtime after installation**."
    ]
   },
   {
@@ -231,6 +231,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "## SpatioTemporal Asset Catalog\n",
+    "\n",
     "The SpatioTemporal Asset Catalog (STAC) specification provides a common language to describe a range of geospatial information so that it can more easily be indexed and discovered. A **SpatioTemporal Asset** is any file that represents information about the earth captured in a certain space and time. STAC aims to enable that next generation of geospatial search engines, while also supporting web best practices so geospatial information is more easily surfaced in traditional search engines. More information about STAC can be found at the [STAC website](https://stacspec.org/). The [STAC Index website](https://stacindex.org/) is a one-stop-shop for discovering STAC catalogs, collections, APIs, software and tools. In this example, we will use the [STAC SPOT Orthoimages of Canada](https://stacindex.org/catalogs/spot-orthoimages-canada-2005)."
    ]
   },
@@ -309,7 +311,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### GeoPandas supported vector format"
+    "### Other vector formats"
    ]
   },
   {
@@ -350,7 +352,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Add points from XY coordinates"
+    "### XY coordinates"
    ]
   },
   {
@@ -467,7 +469,6 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "\n",
     "The image sources (downloadable URLs) are stored in the uuid column of the GeoDataFrame."
    ]
   },
@@ -485,7 +486,6 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "\n",
     "Download all images using the download_files() function."
    ]
   },
@@ -516,7 +516,7 @@
     "m.add_gdf(gdf, layer_name='Footprints')\n",
     "m.add_cog_layer(images[0], nodata=0, name='OpenAerialMap')\n",
     "# m.add_tile_layer(tiles[0], attribution='OpenAerialMap', name='OpenAerialMap')\n",
-    "m\n"
+    "m"
    ]
   },
   {
@@ -543,7 +543,7 @@
    "source": [
     "## AWS Open Data\n",
     "\n",
-    "The [AWS Open Data Program](https://registry.opendata.aws/) hosts a lots of open and public datasets on AWS, including Landsat 8, Sentinel-2, NAIP, and many more. Check out https://github.com/opengeos#data-catalogs for a list of open and public datasets on AWS.\n"
+    "The [AWS Open Data Program](https://registry.opendata.aws/) hosts a lots of open and public datasets on AWS, including Landsat 8, Sentinel-2, NAIP, and many more. Check out https://github.com/opengeos#data-catalogs for a list of open and public datasets on AWS."
    ]
   },
   {
@@ -867,18 +867,6 @@
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.9"
   }
  },
  "nbformat": 4,