Readings

There are various useful resources to support your learning. Below, we list a few recommended resources that you can use to learn more about the topics covered on this course:

• Rey, S., D. Arribas-Bel, L. Wolf. (2023). Geographic Data Science with Python. –> Is freely available online.

• Tenkanen, H., V. Heikinheimo & D. Whipp (2025). Introduction to Python for Geographic Data Analysis –> Is freely available online.

• Paez, A. (2021). An introduction to spatial data analysis and statistics: A course in R. –> Is freely available online.

• Haining, R. & G. Li (2020). Modelling Spatial and Spatial-Temporal Data - A Bayesian Approach.

• Chun, Y. & D. Griffith. (2013). Spatial statistics & Geostatistics.

• O’Sullivan, D. & D. Unwin (2010). Geographic information analysis. –> Is available from the Aalto’s library.

• Franklin, R. (2022). Quantitative methods I: Reckoning with uncertainty

• Kraak M., R.E. Roth, B. Ricker, A. Kagawa & G. Le Sourd (2020). Mapping for a Sustainable World. United Nations: New York, NY (USA).