Convert jpg to png

source/part2/chapter-05/md/01-introduction-to-geographic-data-in-python.md

@@ -23,7 +23,7 @@ To be able to work with real world geographic objects (such as roads or lakes) o
 
 The vector representation of the road and building features (shown on the left in Figure 5.2) are constructed from points in geographical space which are connected to each other forming lines and polygons. The subplots on the right, shows raster representations of the same features. They are constructed from rectangular cells (also called as pixels) that form a uniform grid, i.e. a raster. The grid is associated to specific geographical location and each cell of the grid contains a value representing some information, such as elevation, temperature or presence/absence (as in this figure). Lastly, the roads on the top-left could be represented as a network, which is a vector-based data structure consisting of intersections (called *nodes*) that are represented as points, and streets connecting the nodes that are represented as lines (called *edges*). Because the vector and raster data models are very different, there are typically a different set of GIS tools and methodologies applied for raster and vector data. However, the vector and raster worlds are not totally isolated from each other, as in many cases it is useful to convert the data from one format to another for specific operations, as has been done in Figure 5.2.
 
-![_**Figure 5.2.** Vector and raster representations of roads and buildings._](../img/vector_vs_raster.jpg)
+![_**Figure 5.2.** Vector and raster representations of roads and buildings._](../img/vector_vs_raster.png)
 
 _**Figure 5.2.** Vector and raster representations of roads and buildings._
 

source/part2/chapter-05/nb/01-introduction-to-geographic-data-in-python.ipynb

@@ -21,7 +21,7 @@
     "\n",
     "The vector representation of the road and building features (shown on the left in Figure 5.2) are constructed from points in geographical space which are connected to each other forming lines and polygons. The subplots on the right, shows raster representations of the same features. They are constructed from rectangular cells (also called as pixels) that form a uniform grid, i.e. a raster. The grid is associated to specific geographical location and each cell of the grid contains a value representing some information, such as elevation, temperature or presence/absence (as in this figure). Lastly, the roads on the top-left could be represented as a network, which is a vector-based data structure consisting of intersections (called *nodes*) that are represented as points, and streets connecting the nodes that are represented as lines (called *edges*). Because the vector and raster data models are very different, there are typically a different set of GIS tools and methodologies applied for raster and vector data. However, the vector and raster worlds are not totally isolated from each other, as in many cases it is useful to convert the data from one format to another for specific operations, as has been done in Figure 5.2.\n",
     " \n",
-    "![_**Figure 5.2.** Vector and raster representations of roads and buildings._](../img/vector_vs_raster.jpg)\n",
+    "![_**Figure 5.2.** Vector and raster representations of roads and buildings._](../img/vector_vs_raster.png)\n",
     "\n",
     "_**Figure 5.2.** Vector and raster representations of roads and buildings._"
    ]