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Course information

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

Week 1

  • Introduction to the course
  • Overview
  • Introduction to Spatial Analysis
  • Tutorial 1 - Spatial analysis with Python
  • Point pattern analysis
  • Spatial autocorrelation
  • Tutorial 1.1 - Meet Git
  • Exercise 1

Week 2

  • Overview
  • Analysis of spatial field data
  • Geostatistics: Kriging interpolation
  • Exercise 2

Week 3

  • Overview
  • Map overlay & algebra
  • Spatial network analysis
  • Exercise 3

Week 4

  • Overview
  • Spatial networks: Optimization & Centrality
  • Multivariate Spatial Analysis
  • Exercise 4

Week 5

  • Overview
  • Cartography and Map User Interfaces
  • Visual analytics
  • Conclusions, Exam & Practicalities
  • Repository
  • Suggest edit
  • .rst

Attribution

Attribution#

Inspiration and some of the materials represented on these pages have been adapted from:

  1. Geo-Python -course (Whipp, Tenkanen & Heikinheimo, 2020).

  2. Automating GIS processes -course (Tenkanen & Heikinheimo, 2020)

  3. Geographic Data Science with Python -book

The above courses (1-2) are licenced under Creative Commons BY-SA 4.0 in a similar manner as this course, and the course 3. is licenced under Creative Commons BY-NC-ND 4.0.

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License and terms of usage

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Introduction to the course

By Henrikki Tenkanen

© Copyright 2023, Henrikki Tenkanen, Dept. of Built Environment, Aalto University.