Spatial Data Analysis in Urban Cartography#

What You’ll Create & Learn#

In this course, you will apply basic programming skills to analyze and visualize urban environment. Through hands-on tasks, you’ll explore fundamental GIS and cartographic concepts and become familiar with Python libraries for geospatial data analysis and visualization.

The course is divided into modules, each covering core topics and including an assignment. These assignments are not just technical exercises, but they are parts of a larger course project. In o case, you will assess a city’s accessibility within the 15-minute city framework and create interactive maps to visualize your findings.

For Whom This Course is Intended#

  • Urban Planners looking to enhance their skills in spatial data analysis and cartography.

  • Anyone Curious about using Python to analyze and visualize urban data.

Format#

The course consists of a set of Jupyter notebooks (combined into a Jupyter Book) for each module, which you can use either separately or all together. Each module includes basic theory and links to additional resources for self-learning, code-examples and tasks.

The course is accompanied by short videos explaining key concepts.

It is self-paced with approximately 12–15 hours of content.

At the start and at the end of each module, you may be asked to participate in a short survey to help assess your knowlwge and skills. Additionally, you may be asked to submit the results of the tasks (optional). It will help to make the next iterations of the course better.

Quick Facts#

  • Format: Online, hands-on projects

  • Length: Self-paced with approximately 12-15 hours of content

  • Prerequisites: This course does not cover Python basics. If you’re new to Python, please complete an introductory course before starting this one.

Other information#

This course is part of a master’s thesis by Bella Mironova within the Erasmus Mundus Master Programme in Cartography (2025), under the supervision of Georg Gartner and Juliane Cron.

More information about this master’s thesis research will be available in the coming months.