SubjectsSubjects(version: 941)
Course, academic year 2022/2023
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Introduction to environmental informatics - MO550P66
Title: Úvod do environmentální informatiky
Czech title: Úvod do environmentální informatiky
Guaranteed by: Institute for Environmental Studies (31-550)
Faculty: Faculty of Science
Actual: from 2019
Semester: winter
E-Credits: 4
Examination process: winter s.:
Hours per week, examination: winter s.:2/2, C [HT]
Capacity: 33
Min. number of students: 1
For 4EU+ students: no
Virtual mobility / capacity: no
State of the course: taught
Language: Czech
Additional information:
Note: enabled for web enrollment
Guarantor: Ing. Luboš Matějíček, Ph.D.
Teacher(s): Ing. Luboš Matějíček, Ph.D.
Annotation -
Last update: Ing. Luboš Matějíček, Ph.D. (27.10.2019)
The lecture is primarily focused on data processing in the area of living environment. For the students of natural science, the lecture sums up the introductory course that is extended by other optional lectures, exercises and seminars. Presentations of individual aspects of data processing are based on the ESRI (Environmental Systems Research Institute) guidebooks. The lecture contains computer presentations of selected exercises, which are consecutively processed by students in the framework of exercises.
Literature -
Last update: Ing. Luboš Matějíček, Ph.D. (27.10.2019)

Bruce, B.C. (2014). Introductory Statistics and Analytics : A Resampling Perspective. New Jersey: Wiley.

Crawley, M.J. (2014). Statistics : An Introduction Using R. New Jersey: Wiley.

Dorman, M. (2014). Learning R for Geospatial Analysis. Birmingham: Packt Publishing.

Haas, T.C. (2013). Introduction to Probability and Statistics for Ecosystem Managers : Simulation and Resampling. New Jersey: Wiley.

Hand, D.J. (2008). Statistics : A Very Short Introduction. Oxford: Oxford University Press.

Okabe, A. and Sugihara, K. (2012). Spatial Analysis along Networks : Statistical and Computational Methods. New Jersey: Wiley.

Rong, Y. (2011). Practical Environmental Statistics and Data Analysis. Hertfordshire: ILM Publications.

Rugg, G. (2007). Using Statistics : A Gentle Introduction. New York: McGraw-Hill Education.

Requirements to the exam -
Last update: Ing. Luboš Matějíček, Ph.D. (28.06.2023)

News (2020/SEP28) see Czech version


Original information

1. Creation of selected tasks based on direction of the supervisor.

2. Missing exercise can be substituted by reports based on recommendation of the supervisor.

Note: Subject can be graduated by distance teaching using MOODLE

Syllabus -
Last update: Ing. Luboš Matějíček, Ph.D. (27.10.2019)

1. Overview of using database systems for data processing in the area of living environment, data accessibility in the Internet.
2. Overview of spreadsheet functionality and statistical programs for data processing in the area of living environment.
3. Overview of programs focused on computer graphic, examples of processing the image data.
4. Using of CAD for spatial data processing and visualization, examples of spatial models of urban areas with visualization of data focused on living environment.
5. Basic concepts of GIS, overview of available GIS computer programs and their applications in the area of living environment.
6. Basic data formats in GIS focused on raster data, vector data, irregular triangulated networks and attributes of spatial objects in relation to living environment.
7. Basic procedures for data acquisition, processing and display of spatially related data in GIS, creation of thematic maps, visualization methods of spatial objects.
8. Processing of raster data in GIS, calculation focused on terrain morphology, using of raster algebra, spatial optimization tasks.
9. Processing of vector data in GIS, spatial interactions, using of set operations, selection procedures and interpretation of physical-chemical variables.
10. Processing of triangulated irregular networks in GIS and their using in the framework of digital terrain model construction, display of physical-chemical variables.
11. Interpolation of spatial related variables with deterministic techniques (IDW, spline) and geostatistical methods (kriging), integration in the framework of thematic maps.
12. Construction of network models, route optimization, optimization of spatial object accessibility.
13. Basic methods of digital spatial data acquisition focused on digitization of paper maps, aerial and satellite images, development of spatial database, sharing data through the Internet.
14. Examples of the projects focused on processing data about living environment.

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