548-0069/03 – Spatial Problems Algorithm Development (APU)
| Gurantor department | Department of Geoinformatics | Credits | 5 |
| Subject guarantor | doc. Ing. Michal Kačmařík, Ph.D. | Subject version guarantor | doc. Ing. Petr Rapant, CSc. |
| Study level | undergraduate or graduate | Requirement | Compulsory |
| Year | 1 | Semester | winter |
| | Study language | English |
| Year of introduction | 2015/2016 | Year of cancellation | 2016/2017 |
| Intended for the faculties | HGF | Intended for study types | Follow-up Master |
Subject aims expressed by acquired skills and competences
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.
Teaching methods
Lectures
Tutorials
Summary
Algorithm, ways of algorithm description. Python language. Spatial algorithms for vector and raster data.
Compulsory literature:
NCGIA Core Curriculum on GIS.
Internet tutorials on Python language.
Recommended literature:
Mehta, P.: Handbook of Data Structures and Applications. Chapman & Hall/CRC Computer & Information Science Series, 2004. 1392 stran
Way of continuous check of knowledge in the course of semester
Programs (homework)
Lessons (perform tasks)
Written exams
E-learning
Other requirements
No additional requirements are imposed on the student.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
- The concept of algorithm, the importance of algorithms for spatial tasks in geoinformatics, the requirements of the algorithm, methods of registration algorithms, algorithm development, flowchart.
- The basic features of Python, why and what you can use Python for. Variables, data types, operators and expressions, logical expressions, numbers and strings, formatting.
- Lists (Field), tuples, and work with them. Conditions and cycles. The function definition functions.
- Sorting, searching - the most used algorithms vs.. built-in Python methods.
- Vector data - the intersection of lines, point in polygon, polygon intersection with the line, overlay operations with polygons, polygon triangulation.
- Dijkstra's algorithm, A * - finding the shortest path in the graph.
- Raster data - work with georeferenced raster images - image vs. map coordinates, determining the value of a pixel on the specified coordinates, affine transformation.
- Histogram of raster images - calculate the basic statistics characteristics.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
Předmět neobsahuje žádné hodnocení.