Skip to main content
Ctrl+K
 - Home  - Home

Course information

  • General info
  • Learning goals
  • Grading
  • Course environment
  • Install Python + libraries (optional)
  • Communicating with Slack
  • License and terms of usage
  • Attribution

Week 1

  • Introduction to the course
  • Lesson overview
  • What is Sustainability?
  • What is Spatial Data Science?
  • Tutorial 1 - Spatial analysis with Python
  • Tutorial 1.1 - Meet Git
  • Recommended readings
  • Exercise 1

Week 2

  • Lesson overview
  • Human wellbeing and capabilities
  • Network analytics and spatial accessibility modelling
  • Tutorial 2.1 - Shortest path analysis
  • Tutorial 2.2: Spatial accessibility modelling with r5py
  • Recommended readings
  • Exercise 2

Week 3

  • Lesson overview
  • Economic inequalities and growth
  • Spatial econometrics
  • Tutorial 3 - Spatial Regression in Python
  • Recommended readings
  • Exercise 3

Week 4

  • Lesson overview
  • Natural disaster management with user-generated data

Week 5

  • Lesson overview
  • Sustainable Cities and Mobilities
  • Mobility analytics
  • Agent-based simulation with spatial data
  • Tutorial 4: Trajectory data mining in Python
  • Recommended readings
  • Exercise 4

Final Assignment

  • Overview (video)
  • Instructions
  • Starting your final assignment on Github
  • Repository
  • Suggest edit
  • .rst

Human wellbeing and capabilities

Human wellbeing and capabilities#

previous

Lesson overview

next

Network analytics and spatial accessibility modelling

By Henrikki Tenkanen

© Copyright 2025, Henrikki Tenkanen, Dept. of Built Environment, Aalto University.