Course: Advanced Methods for Spatial Data Processing

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Course title Advanced Methods for Spatial Data Processing
Course code KGI/PGPMZ
Organizational form of instruction Lecture
Level of course Doctoral
Year of study not specified
Semester Winter and summer
Number of ECTS credits 10
Language of instruction Czech, English
Status of course unspecified
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Voženílek Vít, prof. RNDr. CSc.
  • Tuček Pavel, doc. Mgr. Ph.D.
Course content
Geographic data in R Attribute operations Spatial statistics Geometric operations Making Maps in R Bridges to standard GIS SWs Statistical learning for geographic data Applications in transport, ecology, geomarketing

Learning activities and teaching methods
unspecified
Learning outcomes
Prerequisites
unspecified

Assessment methods and criteria
unspecified
Practical work on advanced computational methods.
Recommended literature
  • Bivand, Roger, and Markus Neteler. Open Source Geocomputation: Using the R Data Analysis Language Integrated with GRASS GIS and PostgreSQL Data Base Systems. Proceedings of the 5th International Conference on GeoComputation.
  • Cheshire, James, and Robin Lovelace. (2015). Spatial Data Visualisation with R.In Geocomputation, edited by Chris Brunsdon and Alex Singleton. SAGE Publications.
  • Longley, Paul A., Sue M. Brooks, Rachael McDonnell, and Bill MacMillan. (1998). Geocomputation: A Primer. 1 edition. Chichester.
  • Muenchow, Jannes, Patrick Schratz, and Alexander Brenning. (2017). RQGIS: Integrating R with QGIS for Statistical Geocomputing.. The R Journal 9 (2): 409?28.
  • Openshaw, Stan, and Robert J. Abrahart, eds. (2000). Geocomputation. London ; New York: CRC Press.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester