Learning goals

After each week you should be able to achieve following learning goals.

Class

Learning goals

After lesson 1 you should be able to:
  • search for information about the available GIS packages in Python

  • understand how geometric objects are represented in Python using Shapely

  • create geometric objects based on coordinate values

  • (optionally) install Python packages on your own computer using conda

After lesson 2 you should be able to:
  • Read and write spatial data from/to common file formats

  • Conduct simple analysis on spatial and non-spatial data

  • Manage coordinate reference systems and re-project data

After lesson 3 you should be able to:
  • Do geocoding, i.e. converting addresses into Points (and vice versa)

  • Conduct Point in Polygon queries

  • Read data from KML file

  • Make spatial and table joins between layers

  • Find the nearest neighbour from Point -objects

After lesson 4 you should be able to:
  • Reclassify data based on different criteria (custom or common classifiers)

  • Do overlay analysis & select data e.g. based on boundaries of another layer

  • Aggregate data & merge geometric objects together, based on common id

  • Simplify geometries

After lesson 5 you should be able to:
  • Create a static map with background basemap using Geopandas & contextily

  • Create a simple interactive map using either Bokeh or Folium (or both)

  • Share your maps (static / interactive) on the internet using GitHub pages

After lesson 6 you should be able to:
  • Retrieve and save data from OpenStreetMap using Python

  • Extract simple street network properties and statistics

  • Do simple route optimization using shortest path algorithm in osmnx / networkx

Optional self-study

After going through the optional materials you should be able to:
  • understand the basics of raster data processing using rasterio

  • be familiar with Python scripting in QGIS