Summary

In this chapter, we started our exploration of geospatial analysis by looking at the types of problems you would typically have to solve and the types of data that you will be working with. We discovered and installed two major Python libraries to work with geospatial data: GDAL/OGR to read (and write) data, and Shapely to perform geospatial analysis and manipulation. We then downloaded a simple but useful shapefile containing country data, and learned how to use the OGR library to read the contents of that shapefile.

Next, we saw how to convert an OGR geometry object into a Shapely geometry, and then used the Shapely library to analyze and manipulate that geometry. Finally, we created a simple Python program that combines everything we have learned, loading country data into memory and then using Shapely to find countries which border each other.

In the next chapter, we will delve deeper into the topic of geospatial data, learning more about geospatial data types and concepts, as well as exploring some of the major sources of freely available geospatial data. We will also learn why it is important to have good data to work with—and what happens if you don't.