diff --git a/shean_ICESat-2_hackweek_tutorial_GeospatialAnalysis.ipynb b/shean_ICESat-2_hackweek_tutorial_GeospatialAnalysis.ipynb
index 01d78fc..deba5a1 100644
--- a/shean_ICESat-2_hackweek_tutorial_GeospatialAnalysis.ipynb
+++ b/shean_ICESat-2_hackweek_tutorial_GeospatialAnalysis.ipynb
@@ -9,7 +9,7 @@
     "*Not intended for trillions of ATL03 points\n",
     "\n",
     "ICESat-2 hackweek  \n",
-    "June 18, 2019  \n",
+    "June 19, 2019  \n",
     "David Shean"
    ]
   },
@@ -62,17 +62,22 @@
     "\n",
     "## The Scientific Python landscape\n",
     "\n",
-    "* Python, iPython, Jupyter\n",
+    "* Python\n",
+    "* iPython, Jupyter\n",
     "* NumPy, Pandas, Matplotlib, SciPy\n",
-    "* xarray, scikit-learn, \n",
+    "* xarray, scikit-image, scikit-learn\n",
+    "\n",
+    "One interpretation of this stack:\n",
     "\n",
     "![2017 Scientific Python Stack](https://ryanwingate.com/assets/images/python/python-1-1.png)\n",
     "Slide from Jake VanderPlas’s presentation at PyCon 2017, entitled “The Unexpected Effectiveness of Python in Science.”\n",
     "\n",
     "## The Geospatial Python landscape\n",
     "* GDAL/OGR, GEOS, PROJ\n",
-    "* shapely, fiona\n",
-    "* geopandas, rasterio, Ccrtopy\n",
+    "* shapely, fiona, pyproj\n",
+    "* geopandas, rasterio, cartopy\n",
+    "\n",
+    "[Insert shiny new figure here]\n",
     "\n",
     "## Complementary approaches for ICESat-2 data\n",
     "\n",
@@ -81,14 +86,15 @@
     "    * Basic array manipulations\n",
     "    * Array size limited by memory\n",
     "2. Higher-level data science - *analysis, interpetation, and visualization*\n",
-    "    * NumPy under the hood, convenience/functionality comes with small performance hit\n",
+    "    * NumPy under the hood\n",
+    "    * Convenience and flexibility comes with small performance hit\n",
     "    * Labels make life easier (don't need to remember integer indices)\n",
     "\n",
-    "At the end of the day, most of us just want/need (x,y,z,t) with ICESat.\n",
+    "Here, we're going to explore #2 with an existing dataset.\n",
     "\n",
-    "As with all things in the *nix/open-source/Python world, there are always multiple approaches that can be used to accomplish the same goals.  The user must decide on an approach based on complexity, time constraints, etc.\n",
+    "At the end of the day, most of us just want/need (x,y,z,t) with ICESat-2.\n",
     "\n",
-    "Here, we're going to explore #2 with an existing dataset."
+    "As with all things in the *nix/open-source/Python world, there are always multiple approaches that can be used to accomplish the same goals.  The user must decide on an approach based on complexity, time constraints, etc."
    ]
   },
   {
@@ -129,7 +135,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Wait a minute, I thought this was an ICESat-2 hackweek!\n",
+    "## Wait, I thought this was an ICESat-2 hackweek?\n",
     "\n",
     "Note that we could (and should!) swap similarly processed/filtered ATL06 points over CONUS for this tutorial.  I did not have time to do this before the hackweek, but it would make a great project (nudge).  After opening this updated file with Pandas, it should mostly be a matter of updating field names throughout the notebook."
    ]
@@ -235,8 +241,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "glas_df = pd.read_csv(glas_fn)\n",
-    "#That's it!"
+    "glas_df = pd.read_csv(glas_fn)"
    ]
   },
   {
@@ -1558,12 +1563,14 @@
     "\n",
     "Note that leaflet uses tiled basemaps: https://en.wikipedia.org/wiki/Tiled_web_map \n",
     "\n",
-    "Default projection is Web Mercator (EPSG:3857): https://en.wikipedia.org/wiki/Web_Mercator_projection.  This works well for lower latitudes, but not the polar regions.  I know QGIS can reproject tiled basemaps on the fly - I haven't tested with ipyleaflet."
+    "Default projection is Web Mercator (EPSG:3857): https://en.wikipedia.org/wiki/Web_Mercator_projection.  This works well for lower latitudes, but not the polar regions.  I know QGIS can reproject tiled basemaps on the fly - I haven't tested with ipyleaflet.\n",
+    "\n",
+    "FYI, `folium` provides similar functionality outside of the iPython/Jupyter stack: https://python-visualization.github.io/folium/"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 155,
    "metadata": {},
    "outputs": [],
    "source": [