548-0129/01 – Programming in GIS 1 (PGIS1)
| Gurantor department | Department of Geoinformatics | Credits | 4 |
| Subject guarantor | doc. Ing. Michal Kačmařík, Ph.D. | Subject version guarantor | doc. Ing. Michal Kačmařík, Ph.D. |
| Study level | undergraduate or graduate | Requirement | Compulsory |
| Year | 2 | Semester | winter |
| | Study language | Czech |
| Year of introduction | 2021/2022 | Year of cancellation | |
| Intended for the faculties | HGF | Intended for study types | Bachelor |
Subject aims expressed by acquired skills and competences
The main aim of the course is to introduce students in procedures and methods of spatial tasks algoritmization. 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
Course is focused on basic programming in language Python. Student is introduced to basic structures which form a programm, and learn how to create simple scripts for solving of selected spatial tasks.
Compulsory literature:
YANG, Ch. Introduction to GIS Programming and Fundamentals with Python and ArcGIS (R). Taylor & Francis Inc, 2017, ISBN: 9781466510081, 302 s.
ALLEN, D. GIS Tutorial for Python Scripting. ESRI Press, 2014, ISBN: 9781589483569, 460 s.
YATSKO, A. a Suslow, W. Insight into Theoretical and Applied Informatics. De Gruyter, 2015, ISBN: 978-3-11-046987-5, 122 s.
JACKSON, C. Learn Programming in Python with Cody Jackson. Packpub, 2018, ISBN 13: 9781789531947, 304 s.
Recommended literature:
SWEIGART, A. Automate the Boring Stuff with Python: Practical Programming for Total Beginners. No Starch Press, 2015, ISBN-10: 1593275994, 504 s.
BAUGH, T. Software Development I: with Python. SoftBaugh, Inc., 2010, ISBN-10: 0975475940, 589 s.
BRAJENDRA, S., JIGNESH, R., PATHIK, R. Algorithm, Pseudocode and Flowchart: Learn Algorithm in Simple Steps. BeITReady, 2015.
The Python Tutorial. Dostupné online: https://docs.python.org/3/tutorial/index.html
Way of continuous check of knowledge in the course of semester
Students are asked about knowledge from areas that they should have already known from previous lectures. They also work on individual tasks. Written and oral exam.
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:
1, Algorithm, history of alghoritmization
2, Basic data types and data structures
3, Program Control Structures
4, Work with (text) files
5, Flowcharts
6, Algorithms for sorting and finding
7, Functions for basic operations with vector data
8, Algorithms for vector data - finding the intersection of two lines, calculating the distance of a point from a line
9, Algorithms for vector data - finding a point in a polygon
10, Algorithms for vector data - polygon area calculation
11, Algorithms for vector data - triangulation
12, Algorithms for raster data - overview, filtration, erosion algorithm, raster transformation
13, Algorithms in graphs, route finding
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction