| Course Unit Code | 548-0069/02 |
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| Number of ECTS Credits Allocated | 4 ECTS credits |
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| Type of Course Unit * | Compulsory |
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| Level of Course Unit * | First Cycle |
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| Year of Study * | First Year |
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| Semester when the Course Unit is delivered | Winter Semester |
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| Mode of Delivery | Face-to-face |
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| Language of Instruction | Czech |
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| Prerequisites and Co-Requisites | There are no prerequisites or co-requisites for this course unit |
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| Name of Lecturer(s) | Personal ID | Name |
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| KAC072 | doc. Ing. Michal Kačmařík, Ph.D. |
| Summary |
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| Algorithm, ways of algorithm description. Python language. Spatial algorithms for vector and raster data. |
| Learning Outcomes of the Course Unit |
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| The main aim of the subject is to give students knowledge of subject, procedures and methods of computational procedures of spatial tasks. The goal is to understand and be able to explain and use basic algorithms and combine them to solve more complex spatial problems. |
| Course Contents |
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1) The concept of the algorithm, the importance of algorithms in geoinformatics spatial tasks, requirements on the algorithm notations, creating algorithms, flow chart.
2) The basic structure used in the implementation of algorithms - sequence, jump, condition, cycle.
3) Data types. Custom data types, their use for basic tasks - sorting, searching, indexing.
4) Vector data - the intersection of the lines, point in the polygon, polygon intersection with a line, overlay operations with polygons, polygon triangulation.
5) Graph tasks. Dijkstra's algorithm, A * - finding the shortest path in a graph.
6) Raster data - work with georeferenced raster image - image vs. map coordinates, determine the value of the pixel at the specified coordinates, affine transformation.
7) Reclassification of raster image, overlay operations, map algebra. Histogram of raster image - calculation of basic statistical characteristics. |
| Recommended or Required Reading |
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| Required Reading: |
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NCGIA Core Curriculum on GIS.
Internet tutorials on Python language. |
1. Harms, D., McDonald, K.: Začínáme programovat v jazyce Python. Computer
press, Brno 2003, ISBN 80-7226-799-X
2. Staňková, J.,Staněk, F.: Vytváření a realizace algoritmů. Skriptum VŠB,
Ostrava |
| Recommended Reading: |
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| Mehta, P.: Handbook of Data Structures and Applications. Chapman & Hall/CRC Computer & Information Science Series, 2004. 1392 stran |
| BAYER T. (2008): Algoritmy v digitální kartografii, nakladatelství Karolinum, skriptum, 250 s. PDF. |
| Planned learning activities and teaching methods |
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| Lectures, Tutorials |
| Assesment methods and criteria |
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| Task Title | Task Type | Maximum Number of Points
(Act. for Subtasks) | Minimum Number of Points for Task Passing |
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| Exercises evaluation and Examination | Credit and Examination | 100 (100) | 51 |
| Exercises evaluation | Credit | 33 | 17 |
| Examination | Examination | 67 | 30 |