Before diving into some of the most used GIS data types, a little background is required about what type of information geographical data represents. Earlier in this book, the distinction between raster and vector data was mentioned. All GIS data is comprised of one or the other, but a combination of both vectors and rasters is also possible. When deciding on which data type to use, consider the scale and type of geographical information represented by the data, which in turn determines what Python data libraries to use. As is illustrated in the following examples, the choice for a certain Python library can also depend on personal preference, and there may be various ways to do the same task.
In the geospatial world, raster data comes in the form of aerial imagery or satellite data, where each pixel has an associated value that corresponds to a different color or shade. Raster data is used for large continuous areas, such as differentiating between different temperature...