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Analysis and transformation of geospatial data using Python


A tutorial covering some general concepts of geospatial data, main formats in which it is distributed and some common places where this data can be acquired. We will also learn how to read, process and visualise this data using Python and QGIS. This talk will cover some typical problems one can experience when working with geospatial data.


  1. Installing tools and packages (ansible scripts/cloud machine will be provided)
  2. Basic concepts
  3. geometries. Fixing invalid geometries.
  4. basic operations (union, intersection, difference)
  5. advanced operations (buffer, convex hull, skeleton, voronoi)
  6. Formats and tools
  7. Shapefile
  8. GeoJSON
  9. TopoJSON
  10. GeoTIFF
  11. OSM data
  12. Projections
  13. common projections and their use
  14. how to chose the projection
  15. reprojecting datasets
  16. Using geospatial index
  17. Open Geospatial datasets
  18. UK specific datasets
  19. OpenStreetMap
  20. elevation data
  21. Geocoding
  22. Storing geospatial data in databases (PostgreSQL, SpatiaLite, MongoDB, ElasticSearch)


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