01c Coverage analysis.ipynb -> 01c Coverage Analysis.ipynb

sources/01b Visualization.ipynb

@@ -557,9 +557,11 @@
    "source": [
     "We can see each the red, green and blue band peaking higher in the prerendered TCI around a value of 50 - the curves match closely. Most of the pixels are using the designated nodata-value 0, which is the black stripe in the top left corner of the image.\n",
     "\n",
+    "Because the purpose of this visualization is not creating a one-to-one replica of the included TCI but rather demonstrate how to interpret and manipulate the raster file contents, the approximation is sufficient.\n",
+    "\n",
     "### Creating a Subset of the Area of Interest\n",
     "\n",
-    "It is rare to plot the entire product because the data in this product can be partially missing depending on the orbit position (see [](01c Coverage analysis.ipynb) for more information).\n",
+    "It is rare to plot the entire product because the data in this product can be partially missing depending on the orbit position (see [](01c Coverage Analysis.ipynb) for more information).\n",
     "\n",
     "We can create a rectangular cutout of the created image using code provided in the `rasterio` library for its `rio` command line tool. The code uses a data structure called `Window`, which is a rectangle with an x- and y-offset that is provided by `rasterio` to partially read or write raster data.\n",
     "\n",
@@ -667,6 +669,14 @@
     "            berlin.to_crs(out_kwargs['crs']).plot(ax=ax, facecolor='none', edgecolor='#FBC15E', linewidth=2)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The plot shows that the region of interest exceeds the boundaries of a single product.\n",
+    "The following chapter will provide an analysis of product shapes and data availability."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,