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Course, academic year 2024/2025
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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 2024
Semester: winter
E-Credits: 4
Examination process: winter s.:
Hours per week, examination: winter s.:2/2, C [HT]
Capacity: 66
Min. number of students: 1
4EU+: no
Virtual mobility / capacity: no
State of the course: taught
Language: Czech
Additional information: https://dl2.cuni.cz/course/view.php?id=1890
Note: enabled for web enrollment
Guarantor: Ing. Luboš Matějíček, Ph.D.
Teacher(s): Ing. Luboš Matějíček, Ph.D.
Annotation -
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.
Last update: Matějíček Luboš, Ing., Ph.D. (13.03.2024)
Literature -

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.

Last update: Matějíček Luboš, Ing., Ph.D. (13.03.2024)
Requirements to the exam -

The subject MO550P66 Introduction to environmental informatics is taught face-to-face or, in justifiable cases, via distance learning. Presentations of lectures and assignment of demo tasks are available on MOODLE: https://dl2.cuni.cz/course/view.php?id=1890 in PDF format.

To be awarded credit, demo tasks must be completed and, in case of absence from the exercise, the required results must be submitted for review in MOODLE by the end of the grading period. The task is completed when more than 50 points are obtained in the range of 0 to 100. The recommended submission deadline is the next exercise.

Last update: Matějíček Luboš, Ing., Ph.D. (13.03.2024)
Syllabus -

1. Overview of the functions of spreadsheet programs for data processing in the field of the environment.

1. Overview of the basic functions of statistical programs for data processing in the field of the environment.

2. Overview of data processing options in the MATLAB program.

4. Overview of programs focused on computer graphics, examples of image data processing.

5. Basic concepts of GIS, an overview of available GIS computer programs and their applications in the field of the environment.

6. Basic data formats in GIS focused on raster data, vector data, irregular triangular networks and attributes of spatial objects in relation to the environment.

7. Basic procedures for obtaining, processing and displaying spatially related data in GIS, creating thematic maps, visualization methods of spatial objects.

8. Raster data processing in GIS, calculation focused on terrain morphology, use of raster algebra, spatial optimization tasks.

9. Vector data processing in GIS, spatial interactions, use of set operations, selection procedures and interpretation of physico-chemical variables.

10. Processing of triangular irregular networks in GIS and their use in the construction of digital terrain models, display of physico-chemical variables.

11. Interpolation of spatial variables using deterministic techniques (IDW, spline) and geostatistical methods (kriging), integration within thematic maps.

12. Examples of projects focused on environmental data processing.

Last update: Matějíček Luboš, Ing., Ph.D. (13.03.2024)
 
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