SylabUZ
PL | EN |
  • Language
  • polski
  • english
  • Obtain login and password
  • User's manual (available after logging in)
  • Login

SylabUZ

  1. SylabUZ
  2. Faculty of Engineering and Technical Sciences
  3. winter term 2018/2019
  4. WIEiA - oferta ERASMUS / Informatics - Second-cycle Erasmus programme
  5. Geographical information systems
Generate PDF for this page

Geographical information systems - course description

General information
Course name Geographical information systems
Course ID 11.3-WE-INFD-GIS-Er
Faculty Faculty of Engineering and Technical Sciences
Field of study WIEiA - oferta ERASMUS / Informatics
Education profile -
Level of studies Second-cycle Erasmus programme
Beginning semester winter term 2018/2019
Course information
Semester 3
ECTS credits to win 5
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

  • Familiarize students with the principles of the Geographical Information Systems (GIS).
  • To develop skills in the creation of GIS systems.
  • Familiarize students with the methods of spatial data analysis.
     

Prerequisites

none

Scope

Fundamentals of GIS: History of GIS development, The main applications of GIS, Definitions of terms related to cartographic coordinate systems, Cartographic coordinate systems in Poland, Digital maps, Data sources for GIS, Types of geographical objects, GIS software.

GIS data models: Discrete and continuous spatial data, Precision of spatial data, Spatial data representation using raster and vector graphics, Qualitative and quantitative properties of geographical objects, Raster to vector transformation, Multi-layered representation of spatial data.

GIS architecture: Entering and verification of spatial data, Spatial databases, Designing spatial databases, Database management systems of spatial data, Spatial data processing procedures, Imaging of the spatial data, Presentation of spatial data on the Internet and on mobile devices.

Spatial data analysis: Sampling of spatial data, Geostatistics, Network analysis, Path finding problems, Spatial relationships and interactions, Spatial interpolation, Spatial regression, Spatial simulations using cellular automata.
 

Teaching methods

Lecture, laboratory exercises.

Learning outcomes and methods of theirs verification

Outcome description Outcome symbols Methods of verification The class form

Assignment conditions

  • Lecture – the passing condition is to obtain a positive mark from the final test.
  • Laboratory – the passing condition is to obtain positive marks from all laboratory exercises to be planned during the semester.
  • Calculation of the final grade: lecture 50% + laboratory 50%
     

Recommended reading

  1. Bivand R.S., Pebesma E.J., Gómez-Rubio V.: Applied Spatial Data Analysis with R, Springer,2008.
  2. Kolvoord R., Keranen K.: Making Spatial Decisions Using GIS, A Workbook, ESRI, 2011.
  3. Bolstad P.: GIS Fundamentals: A First Text on Geographic Information Systems, Eider Press, 2004.



 

Further reading

  1. Haining R.: Spatial Data Analysis. Theory and Practice, Cambridge University Press, 2003.
  2. Riple B. D.: Spatial statistics John Wiley & Sons, 2004.
  3. Gorr W. L, Kurland K. S: GIS Tutorial Basic Workbook, ESRI, 2007.
  4. Kolvoord R., Keranen K.: Making Spatial Decisions Using GIS, A Workbook, ESRI, 2011.

Notes


Modified by dr hab. inż. Artur Gramacki, prof. UZ (last modification: 06-04-2018 13:10)

SylabUZ

(Build 175) © 2016 Computer Center - University of Zielona Góra