Guest lecture, Technical University Munich: Spatial data and approaches to study sustainable transport deals with the use of spatial data science approaches to study sustainable mobility and accessibility in urban environments.

After participating in the event, the student is able to:

• Understand how human well-being and capabilities relate to mobility, and how those can be analyzed using computational approaches

• Understand how modern computational technologies can be used to support open science and reproducible research

• Assess the selected analytical tools and understand their benefits and limitations

Program

The planned schedule 6.7.2023:

• 08:00 - 9:30: Intro lecture: The role of spatial data science in understanding sustainable mobility

• 11:30 - 13:00: Tutorial: Using open source Python tools to analyze the levels of access by different travel modes

Contents

Course information

• Introduction to the course
• Install Python + libraries
• Recommended readings
• License and terms of usage
• Attribution

Contents

• SDS & Sustainable mobility
• Tutorial 1.1 - Meet Git
• Tutorial 1.2 - Spatial analysis with Python
• Tutorial 2 - Spatial Network analysis

Looking for earlier versions?

This website is a living document that changes slightly each time I teach these materials. However, all the earlier versions of the site are available from here:

• Materials for workshop at Aalto in May 2023

• Materials for short course at Augsburg University in Sep 2022