Course Details

Geographical Information Systems 2

Academic Year 2026/27

NEA042 course is part of 1 study plan

​ NPC-GK Winter Semester 2nd year

  1. Introduction, definition of GIS, basic concepts. History of GIS, relationship between GIS and other fields. Geographic object, transformation of geographic data, homeomorphism. Issues of reverse engineering.
  2. Information systems (IS). General model and functions of IS, IS types (Anthony's paradigm). Methods of information systems design, UML diagrams.
  3. BIM technology, Digital Czech Republic, BIM concept in the Czech Republic, CDE, BIM - GIS relationship, building identification number, building life cycle.
  4. Information theory. DIKW pyramid, concept of data and information, system entropy, Hartley's information measure, unconditional and conditional entropy.
  5. Selected methods of artificial intelligence. Data mining, cluster analysis, artificial neural networks, genetic algorithms, simulated annealing.
  6. Graph theory. Definition, basic concepts (vertex, edge, sequence, stroke, path, circle, skeleton). Description of graph topology (adjacency and incidence matrices), dynamic data structures for storing graphs in a database (array, linear list, canonical representation).
  7. Basic algorithms on graphs: finding the minimum span, the minimum path between two given vertices, the minimum distance matrix (Floyd's algorithm), the Chinese postman problem, Hamiltonian cycle, planar graphs.
  8. Topology. Definition, history, classification of topology, mathematical and pragmatic concept of topology. Topology based on set theory and algebra. Syntactic and semantic topology. Topology according to the DIGEST standard.
  9. Organization of spatial data. Basic models of vector and raster representation according to topology, matrix data.
  10. Metadata, standards, data quality, data errors in GIS (error typology).
  11. Ontology, definitions, components, general ontology model (GOL).
  12. Spatial analyses. Definition, purpose, types of tasks, history, objectives, graphical and descriptive attributes. Basic types of spatial analysis methods (measurement and classification functions, overlay functions, interpolation functions, connection functions).
  13. Multicriteria analysis in GIS. Determination of weight values. Methods: OWA, WLC, TOPSIS, AHP.

Credits

5 credits

Language of instruction

Czech

Semester

winter

Course Guarantor

doc. Ing. Dalibor Bartoněk, CSc.

Institute

Institute of Geodesy

Forms and criteria of assessment

course-unit credit and examination

Entry Knowledge

computer skills, basic databases, statistics, applied mathematics

Aims

Understanding of information systems and databases with connection to spatial identification.
Basis knowledge needed for GIS design.
Ability to create a GIS project in Arc/Info Systems.

Offered to foreign students

Not to offer

Course on BUT site

https://www.vut.cz/en/students/courses/detail/303622

Lecture

13 weeks, 2 hours/week, elective

Syllabus

  • 1. Introduction, definition of GIS, history, structure, relation to other fields, geographic object, GIS processing chain, mathematical basis of geo-database (homeomorphism).
  • 2. Theory of information. Information Systems (IS), definitions and types of IS, UML diagrams, ISKN structure, IS in state administration (system of 4 basic registers), GeoInfoStrategie.
  • 3. Database systems. Relational and object data model, relational algebra, SQL language. Spatial data structures, SQL spatial queries, deductive databases.
  • 4. Data mining, methods (cluster analysis, artificial neural networks, genetic algorithms).
  • 5. Fundamentals of graph theory. Definitions, basic concepts, structure storage patterns, basic graph algorithms used in GIS (minimal framework, minimum path between two nodes, task of Chinese letterhead, Hamilton path). Planar charts, chart coloring.
  • 6. Topology. History, mathematical and pragmatic approach. Topology according to DIGEST standard.
  • 7. Data models in GIS. Raster, vector, matrix data. Data sources for GIS in the Czech Republic and abroad.
  • 8. Issues of processing large volume data (Big Data).
  • 9. Metadata, data quality, data errors. INSPIRE directive, ontology.
  • 10. Digital terrain models. Definitions, algorithms of creation and optimization, issues of 3D imaging.
  • 11. Map algebra, GIS on-line, web map services, web portals.
  • 12. Spatial analysis. History, Measurement and Classification Functions, focal Functions, Overlay Function, joining Functions.
  • 13. Multi-criteria analysis, methods, applications, reverse engineering, Building Information Modelling (BIM).

Exercise

13 weeks, 2 hours/week, compulsory

Syllabus

  • 1. Introduction, introduction to the topics, conditions for granting credit. Basic information about Arc / Info, the basics of working with ArcCatalog and ArcGIS.
  • 2. Vodohospodářský projekt – part 1.
  • 3. Vodohospodářský projekt – part 2.
  • 4. Image classification - supervised.
  • 5. Use of unsupervised classification – flood assessment.
  • 6. Distance analysis.
  • 7. Hydrological modelling.
  • 8. Work with database, DMT, profiles.
  • 9. QGIS product, basic information, familiarity with the program environment.
  • 10. Project in QGIS - Cloud Point Processing.
  • 11. Python Scripting Language, alternatively creating online geo-web applications.
  • 12. Using Python in QGIS.
  • 13. Final project.