Course information

Introduction to the course
General info
Grading
Course environment
Communicating with Slack
Pair programming
License and terms of usage
Attribution

Lesson 1

Lesson overview
What is Sustainability?
What is Spatial Data Science?
Tutorial 1.1 - Meet Git
Tutorial 1.2 - Spatial analysis with Python
Recommended readings
Exercise 1

Lesson 2

Lesson overview
Human wellbeing and capabilities
Network analytics and spatial accessibility modelling
Tutorial 2 - Spatial Network analysis
Recommended readings
Exercise 2

Lesson 3

Lesson overview
Sustainable Cities and Mobilities
Mobility analytics
Tutorial 3 - Trajectory data mining in Python
Recommended readings
Exercise 3

Lesson 4

Lesson overview
Economic inequalities, growth and green economy
Spatial Regression
Tutorial 4 - Spatial Regression in Python
Recommended readings
Exercise 4

Lesson 5

Lesson overview
Agent-based simulation with spatial data
Recommended readings
Exercise 5

Lesson 6

Lesson overview
Conservation planning & Spatial prioritization
Tutorial/Exercise 6 - Spatial prioritization with Zonation
Recommended readings

Final Assignment

Instructions
Grading criteria for the final assignment

Theme by the Executable Book Project

Spatial Regression¶

previous

Economic inequalities, growth and green economy

next

Tutorial 4 - Spatial Regression in Python

By Henrikki Tenkanen
© Copyright 2020, Henrikki Tenkanen, Dept. of Built Environment, Aalto University.