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SylabUZ

  1. SylabUZ
  2. Faculty of Computer Science, Electrical Engineering and Automatics
  3. winter term 2022/2023
  4. Computer Science - Second-cycle Erasmus programme
  5. Geographical information systems
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Geographical information systems - course description

General information
Course name Geographical information systems
Course ID 11.3-WE-INFD-GIS-Er
Faculty Faculty of Computer Science, Electrical Engineering and Automatics
Field of study Computer Science
Education profile academic
Level of studies Second-cycle Erasmus programme
Beginning semester winter term 2022/2023
Course information
Semester 3
ECTS credits to win 4
Course type optional
Teaching language english
Author of syllabus
  • dr hab. inż. Artur Gramacki, prof. UZ
Classes forms
The class form Hours per semester (full-time) Hours per week (full-time) Hours per semester (part-time) Hours per week (part-time) Form of assignment
Lecture 15 1 - - Credit with grade
Laboratory 30 2 - - Credit with grade

Aim of the course

The aim of the course is to provide students with basic information about spatial information systems (digital maps), the principles of their creation, IT tools supporting this field of knowledge, types of analyzes performed.

Prerequisites

Introduction to Databases

Scope

Definition of basic terms in the field of GIS (Geographical Information Systems). Digital maps versus traditional paper maps. Cartographic projections. Spatial Reference System for the correct location of objects on the globe. EPSG codes. Presentation of selected reference systems, including those used in Poland and in the GPS system. Selected data storage formats for numeric maps. Selected IT tools for working with numeric maps (free and commercial). Database support for storing and analyzing spatial data. Storage of spatial data in MySQL database, dedicated data types, functions supporting spatial analysis. Open Geospatial Consortium (OGC) specifications. Open GeoJSON geo-spatial data exchange format. Examples of spatial analysis. Geostatistics. Presentation of the Google Maps and OpenStreetMap systems and the basics of their programming.

Teaching methods

Lecture, laboratory exercises.

Learning outcomes and methods of theirs verification

Outcome description Outcome symbols Methods of verification The class form

Assignment conditions

Recommended reading

  1. Bivand, R.S., Pebesma, E.J., Gómez-Rubio V.: Applied Spatial Data Analysis with R, Springer, 2008.
  2. Lovelace R, Nowosad J., Muenchow J.: Geocomputation with R. CRS Press, 2019 (https://geocompr.robinlovelace.net/)
  3. Michael Dorman: Learning R for Geospatial Analysis, Packt Publishing, 2014
  4. R Project documentation (https://www.r-project.org/)
  5. MySQL database documentation wersja 8 (https://dev.mysql.com/doc/)
  6. GoogleMaps documentation (https://developers.google.com/maps/documentation)
  7. OpenStreetMap, documentation (https://www.openstreetmap.org/help)

Further reading

Notes


Modified by dr hab. inż. Artur Gramacki, prof. UZ (last modification: 20-04-2022 23:31)

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