Learning goals

Below you find the intended learning outcomes after each study week. Please use this table to monitor your learning progress: you can always go back to revisit a previous week’s material.

After lesson 1, you should be able to:

• search for information about GIS packages available in/for Python,

• understand how geometric objects are represented in Shapely,

• create geometric object based on coordinate values, and

• (optionally) install Python packages on your own computer.

After lesson 2, you should be able to: - read and write spatial data from and to common file formats, - conduct simple analysis on spatial and non-spatial data sets, and - manage coordinate reference systems and re-project data.

After lesson 3, you should be able to: - carry out geocoding, i.e., convert addresses into coordinates, and vice versa, - conduct Point-in-Polygon queries, - read data from a KML file, - join layers on spatial and attribute values, and - find the nearest neighbour among point objects.

After lesson 4, you should be able to: - reclassify data based on different criteria (common and custom classifiers), - carry out overlay analysis, e.g., select data based on the boundaries of another layer, - aggregate data and merge geometric objects, and - simplify geometries.

After lesson 5, you should be able to: - create a static map image with a background map, - create a simple interactive map, and - share your static or interactive map on the internet.

After lesson 6, you should be able to: - retrieve and save data from OpenStreetMap, - extract simple street network properties and statistics, and - carry out simple route optimisation, using a shortest-path algorithm.

After lesson 7, you should be able to: - read and explore single-band and multi-band raster data in Python, - process raster data using clipping, raster mosaics, reclassification, and - perform different raster data analysis including slope analysis and map algebra (raster-raster calculation).