Algorithms and data structures in GIS

Course content

The purpose of this course is to provide the basic mathematical and computer science theory in GIS, building on to the general theory of GIS and learned to use GIS as a tool in spatial analysis that students were acquainted with in the basic GIS courses. The content of this advanced course is necessary to evaluate the results of the analysis and to perform more advanced analysis tools that are not available in a standard GIS software.

Teaching methods

The lectures in the course deal with the most important algorithms in a GIS. Exercises are mainly focused on programming these algorithms. The course concludes with an individual project. Teaching consists of lectures, exercises and project work.

Literature

Main course literature

• Harrie, L., 2020. Lecture notes in GIS algorithms.

Digital version is available in Canvas. Printed copies must be ordered at latest Wednesday 18 October by sending an e-mail to lars [dot] harrie [at] nateko [dot] lu [dot] se. The printed copies are bought from the Geolibrary. The compendium costs 70 SEK.

• Springer Handbook of Geographic Information (SP)

Available digitally from a link given in Canvas. Be aware that you have to use a computer connected to Lund University network to reach the book. You are only allowed to use this book for private studies, not for distributing material to someone else.

• Articles specified in the reading instructions. The articles can be found using links in the reading instructions in Canvas.

Recommended extra reading

• Worboys, M. F., and M. Duckham, 2004. GIS: A Computing Perspective, 2nd edition. Taylor & Francis. Bought at a bookstore or via Internet
• Xiao, N., 2016. GIS Algorithms, Sage.
• Think Python by Allen B. Downey. Found at a link provided in Canvas (Make sure you use the 2nd edition for Python 3.x).
• Matlab - a practical Introduction to Programming and Problem Solving.