In this chapter, we have looked at various techniques for using OGR, GDAL, Shapely, and pyproj within Python programs to solve real-world problems. We have learned:
- How to read from and write to vector-format geo-spatial data in Shapefiles.
- How to read and analyze raster-format geo-spatial data.
- How to change the datum and projection used by a Shapefile.
- That the Well-Known Text (WKT) format can be used to represent geo-spatial features and spatial references in plain text.
- That WKT can be used to transfer geo-spatial data from one Python library to another.
- That WKT can be used to store geo-spatial data in plain text format.
- That you can use the Shapely library to perform various geo-spatial calculations on geometries, including distance calculations, dilation, and intersections.
- That you can use the
pyproj.Projclass to convert coordinates from one projection and datum to another. - That you can use the
pyproj.Geodclass to convert from geometry coordinates to distances, and vice versa.
Up to now, we have written programs that work directly with Shapefiles and other datasources to load and then process geo-spatial data. In the next chapter, we will look at ways that databases can be used to store and work with geo-spatial data. This is much faster and more scalable than storing geo-spatial data in files that have to be imported each time.
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