In this chapter, we combine the Python libraries and geo-spatial data covered earlier to accomplish a variety of tasks. These tasks have been chosen to demonstrate various techniques for working with geo-spatial data in your Python programs; while in some cases there are quicker and easier ways to achieve these results (for example, using command-line utilities), we will create these solutions in Python so you can learn how to work with geo-spatial data in your own Python programs.
This chapter will cover:
- Reading and writing geo-spatial data in both vector and raster format
- Changing the datums and projections used by geo-spatial data
- Representing and storing geo-spatial data within your Python programs
- Using Shapely to work with points, lines, and polygons
- Converting and standardizing units of geometry and distance
This chapter is formatted like a cookbook, detailing various real-world tasks you might want to perform and providing "recipes" for accomplishing them.
If you want to follow through the examples in this chapter, make sure you have the following Python libraries installed on your computer:
- GDAL/OGR version 1.7 or later (http://gdal.org)
pyprojversion 1.8.6 or later (http://code.google.com/p/pyproj)- Shapely version 1.2 or later (http://trac.gispython.org/lab/wiki/Shapely)
For more information about these libraries and how to use them, including references to the API documentation for each library, please refer to Chapter 3.