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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

Recommended readings¶

  • Crooks, A., Malleson, N., Manley, E., Heppenstall, A., (2019). Agent-Based Modelling and Geographical Information Systems, 1st ed, Spatial Analytics and GIS. SAGE Publications.

  • Heppenstall, A.J., Crooks, A.T., See, L.M. and Batty, M. eds., (2011). Agent-based models of geographical systems. Springer Science & Business Media.

  • Macal, C.M. and North, M.J., 2010. Tutorial on agent-based modelling and simulation. Journal of simulation, 4(3), pp.151-162

  • Galán, J. M., Izquierdo, L. R., Izquierdo, S. S., Santos, J. I., Del Olmo, R., López-Paredes, A., & Edmonds, B. (2009). Errors and artefacts in agent-based modelling. Journal of Artificial Societies and Social Simulation, 12(1), 1.

  • Bouarfa, S., Blom, H. A., Curran, R., & Everdij, M. H. (2013). Agent-based modeling and simulation of emergent behavior in air transportation. Complex Adaptive Systems Modeling, 1(1), 1-26.

  • Polhill, G., & Salt, D. (2017). The importance of ontological structure: why validation by ‘fit-to-data’is insufficient. In Simulating social complexity (pp. 141-172). Springer, Cham.

  • Kazil, J., Masad, D., Crooks, A., (2020). Utilizing Python for Agent-Based Modeling: The Mesa Framework. In: Thomson R., Bisgin H., Dancy C., Hyder A., Hussain M. (eds) Social, Cultural, and Behavioral Modeling. SBP-BRiMS 2020. Lecture Notes in Computer Science, vol 12268. Springer, Cham

  • Owen, A., Heppenstall, A., (2018). Making the case for simulation: Unlocking carbon reduction through simulation of individual “middle actor” behaviour. Environ. Plan. B Urban Anal. City Sci. 1–16.

  • Ying, F., O’Clery, N., 2021. Modelling COVID-19 transmission in supermarkets using an agent-based model. PLOS ONE 16, e0249821.

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Agent-based simulation with spatial data

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Instructions

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