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Course information

  • Introduction to the course
  • General info
  • Grading
  • Course environment
  • Communicating with Slack
  • 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 and growth
  • Spatial econometrics
  • Tutorial 4 - Spatial Regression in Python
  • Recommended readings
  • Exercise 4

Lesson 5

  • Lesson overview
  • Agent-based simulation with spatial data
  • Recommended readings

Final Assignment

  • Instructions
Theme by the Executable Book Project
Contents
  • Sustainability
  • Spatial Data Science

Recommended readings¶

Thinking of the breadth of the scope in this course (sustainability + SDS), there are countless of valuable articles, books and other resources that are “good reads”. Here, we list only a fraction of resources that we have found useful or which have been important in these fields in one way or another. Note: These are not obligatory readings for the registered students, but good places to start if the topics interest you more broadly. We will specify in the Exercises if there are any articles that you should read in addition to the lecture materials (unlikely during this year).

Sustainability¶

  • Rockström, J. et al. (2009). A safe operating space for humanity. Nature.

  • Steffen, W. et al. (2015). Planetary boundaries: Guiding human development on a changing planet. Science (80-. ). 347, 1259855.

  • Steffen, W. et al. (2015). The trajectory of the Anthropocene: The Great Acceleration. Anthr. Rev. 2, 81–98.

  • Steffen, W. et al. (2018). Trajectories of the Earth System in the Anthropocene. Proc. Natl. Acad. Sci. U. S. A.

  • Meyer, K. & Newman, P. (2018). The Planetary Accounting Framework: a novel, quota-based approach to understanding the impacts of any scale of human activity in the context of the Planetary Boundaries. Sustain. Earth 1, 4.

  • Sachs, J. et al. (2019). Six Transformations to achieve the Sustainable Development Goals. Nat. Sustain. 2, 805–814.

Spatial Data Science¶

  • Singleton, A. & Arribas‐Bel, D. (2019). Geographic Data Science. Geogr. Anal. 1–15.

  • Wolf, L. et al. (2020). Quantitative geography III: Future challenges and challenging futures. Prog. Hum. Geogr. 1–13.

  • Yuan, M. (2020). Geographical information science for the United Nations’ 2030 agenda for sustainable development. Int. J. Geogr. Inf. Sci. 1–8.

  • Dodge, S. (2021). A Data Science Framework for Movement. Geogr. Anal. 53, 92-112.

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Tutorial 1.2 - Spatial analysis with Python

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Exercise 1

By Henrikki Tenkanen
© Copyright 2022, Henrikki Tenkanen, Dept. of Built Environment, Aalto University.