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Algorithms and data structures in GIS

NGEN25 / EXTQ05

På svenska

Course contents

The course starts with geometric data structures that are used at storing and processing of geographic information in both 2D and 3D. This component also contains a description of spatial concepts, particularly topological relations. The second part of the course treats the basic algorithms in GIS for vector, raster and network representations. The theoretical parts treat basic algorithm theory; some of these algorithms are implemented and applied during the practical exercises using a standard programming language. This part is the most central and largest component of the course. The third part of the course is devoted to a project with focus on scientific writing that goes on during the whole course.

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., 2023. Lecture notes in GIS algorithms (LN)
    Digital version is available in Canvas. 
    Printed copies must be ordered at latest Sunday 18 August by sending an e-mail to lars [dot] harrie [at] nateko [dot] lu [dot] se (lars[dot]harrie[at]nateko[dot]lu[dot]se). The printed copies are bought from the Geolibrary. The compendium costs 80 SEK.
     
  • Duckham, M., Q. Sun, and M. F. Worboys, 2024. GIS: A Computing Perspective, 3rd edition. CRC press. (WD)
    Bought at a bookstore or via Internet.
     
  • Springer Handbook of Geographic Information (SP)
    Digitally available; links is 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.
     
  • Snyder, J. P., 1987. Map Projections - A Working Manual (MP)
    Digitally available; links is given in Canvas.
     
  • Articles specified in the reading instructions.
    The articles can be found using links in the reading instructions in Canvas.

 Recommended extra reading

  • Xiao, N., 2016. GIS Algorithms, Sage
    Bought at a bookstore or via Internet
  • Think Python by Allen B. Downey. 
    Digitally available; links is given in Canvas. (Make sure you use the 2nd edition for Python 3.x)
     

Course coordinator

Lars Harrie

Course facts

Level: Advanced
Credits: 7.5 ECTS
Period: Autumn, period 1
Language of instruction: English
Prerequisites: Admission to the course requires 90 credits studies in natural sciences or technology of which at least 15 credits should be in basic Geographic information science equivalent NGEA31, Geographic Information Systems, basic course, 15 credits and NGEN20, Programming for applications in GIS and remote sensing, 15 credits or the equivalent. English 6/English B.

Course syllabus (pdf, 221 kb, new window)
Course syllabus for students of the Faculty of Engineering (new window) 

For current students

Course schedule

Canvas

Canvas learning platform

Page manager: lars [dot] harrie [at] nateko [dot] lu [dot] se | 30 Apr 2024