style: replace em dashes with colons and splits in lonboard quickstart prose

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Author: aboydnw

quickstarts/lonboard.ipynb

@@ -9,13 +9,13 @@
     "\n",
     "This notebook walks through interactive geospatial visualization with [Lonboard](https://developmentseed.org/lonboard/). Lonboard renders large vector datasets on a GPU-accelerated WebGL map directly in Jupyter. Key benefits:\n",
     "\n",
-    "1. **GPU rendering** — pan and zoom through *millions* of features without breaking interactivity.\n",
-    "2. **No tile server** — geometry streams to the browser as [Apache Arrow](https://arrow.apache.org/); there's no intermediate vector-tile service to stand up.\n",
-    "3. **Cloud-native vector** — read a STAC GeoParquet partition straight off Azure Blob into a `GeoDataFrame`.\n",
-    "4. **Composable** — stack multiple vector layers in one `Map`.\n",
-    "5. **Data-driven styling** — color features by an attribute and mutate the layer in place.\n",
+    "1. **GPU rendering**: pan and zoom through *millions* of features without breaking interactivity.\n",
+    "2. **No tile server**: geometry streams to the browser as [Apache Arrow](https://arrow.apache.org/); there's no intermediate vector-tile service to stand up.\n",
+    "3. **Cloud-native vector**: read a STAC GeoParquet partition straight off Azure Blob into a `GeoDataFrame`.\n",
+    "4. **Composable**: stack multiple vector layers in one `Map`.\n",
+    "5. **Data-driven styling**: color features by an attribute and mutate the layer in place.\n",
     "\n",
-    "We'll render [Microsoft Building Footprints](https://planetarycomputer.microsoft.com/dataset/ms-buildings) over Portland, Oregon — hundreds of thousands of polygons in a single layer.\n",
+    "We'll render [Microsoft Building Footprints](https://planetarycomputer.microsoft.com/dataset/ms-buildings) over Portland, Oregon: hundreds of thousands of polygons in a single layer.\n",
     "\n",
     "The companion [Lonboard tutorial](../overview/lonboard.md) has the full narrative."
    ]
@@ -215,7 +215,7 @@
    "source": [
     "## Render the footprints\n",
     "\n",
-    "`PolygonLayer.from_geopandas()` uploads the geometry to the GPU as Arrow. The map below is fully interactive — pan and zoom through every building with no tile server in the loop.\n",
+    "`PolygonLayer.from_geopandas()` uploads the geometry to the GPU as Arrow. The map below is fully interactive. Pan and zoom through every building with no tile server in the loop.\n",
     "\n",
     "**Expected result:** an interactive map of Portland's building footprints."
    ]
@@ -253,7 +253,7 @@
    "source": [
     "## Color by building height\n",
     "\n",
-    "Each footprint carries a `meanHeight`. Map it through a continuous colormap to shade every polygon — data-driven styling across the whole layer, evaluated on the GPU.\n",
+    "Each footprint carries a `meanHeight`. Map it through a continuous colormap to shade every polygon: data-driven styling across the whole layer, evaluated on the GPU.\n",
     "\n",
     "**Expected result:** the same footprints, now colored by height (`plasma`: purple = low, yellow = tall)."
    ]
@@ -320,7 +320,7 @@
    "source": [
     "## You're done\n",
     "\n",
-    "If every cell above rendered a map, the stack is wired up end-to-end: STAC search → cloud GeoParquet → Arrow upload → GPU-rendered vector → data-driven styling — all with no tile server.\n",
+    "If every cell above rendered a map, the stack is wired up end-to-end: STAC search → cloud GeoParquet → Arrow upload → GPU-rendered vector → data-driven styling, all with no tile server.\n",
     "\n",
     "Swap in your own bbox, collection, or `GeoDataFrame` and the same pattern applies. For pixel-level *raster* analysis (window reads, overview traversal), see the [async-geotiff tutorial](../overview/async-geotiff.md). For a standalone web app rather than a notebook, the [deck.gl-raster tutorial](../overview/deckgl-raster.md) builds a raster renderer in TypeScript."
    ]