Excel
Course title Programming in Geoinformatics I
Course code InfT3046
Credit points (ECTS) 3
Total Hours in Course 81
Number of hours for lectures 16
Number of hours for seminars and practical classes 16
Independent study hours 49
Date of course confirmation 19/01/2022
Responsible Unit Institute of Computer Systems and Data Science
 
Course developers
Dr. sc. ing., asoc. prof. Tatjana Rubina
Dr. sc.ing., asoc. prof. Laima Bērziņa
Mg. sc. ing., lekt. Ingus Šmits

There is no prerequisite knowledge required for this course
 
Course abstract
The course introduces programming required for GIS tasks. The fundaments of programming in GIS using Python and C# language is covered. The course introduces Python to integrate programming with GIS analysis. Students learn to automate geoprocessing tasks using Python and create GIS tools with C#. After successfully completed the course students will be able to understand scripting in Python for data analyses within the ArcGIS environment, will be able to use the basic principles of writing useful code for spatial analyses and develop tools and algorithms for spatial analyses.
Learning outcomes and their assessment
After the course complement the student will have:
knowledge - of different programming languages commonly used in GIS analysis and customization and how to use these technologies to expand upon exiting desktop GIS software and create new tools (theory test);
skills – demonstrate an understanding of GIS programming techniques to perform programming tasks; using languages such as Python and C# for geoproccesing tasks and development of program small-scale GIS models and tools (reports of practical works); competence - understand software engineering concepts, good programming methods and practices for geoinformatics; critically evaluate different tools for GIS analysis and developing applications in GIS; conceptualize, plan, implement, and understand scripts for GIS mapping applications, customizations and automation (reports of practical works and individual work).
Course Content(Calendar)
Full-time studies:
1.Overview of common programming languages for geoinformatics 1 h
2.Python and R for spatial data processing, analysis and modelling 2 h
3.C#, C++ and Java for GIS development and map servers 2 h
4.JavaScript, Python and PHP for web mapping and interactive webpages 2 h
5.SQL using for geospatial databases 1 h
6.Fundamentals of Python programming: raster and vector data access 2 h
7.Fundamentals of Python programming: exploring spatial data 2 h
8.Fundamentals of Python programming: manipulating spatial data 2h
9.Geoprocessing with Python to automating map production and printing 4 h
10.Python and ArcPy to manage projects, maps, layers and layouts 4 h
11.Fundamentals of C# programming: creating customized GIS tools 5 h
12.Fundamentals of C# programming: developing GIS tools 5 h

Part-time studies: All topics specified for full-time studies are implemented, but the number of contact hours is 1/2 of the specified number of hours
Requirements for awarding credit points
Laboratory works must be completed and submitted, individual work must be presented, theory test must be positively evaluated.
Description of the organization and tasks of students’ independent work
By completing the individual task, students must acquire the skills to independently prepare a solution for the automation of a GIS task (s) using the Phyton scripting language and the chosen programming language.
Criteria for Evaluating Learning Outcomes
Knowledge is evaluated on a 10-point scale. The mark consists of:
• completeness and timely submissions of laboratory works (40%);
• defense of independent work (20%); • test on theory questions (40%).
Compulsory reading
Zandbergen A. Python Scripting for ArcGIS. Redlands, California: Esri Press, 2014. 358 p.
Crampton J. Mapping: A Critical Introduction to Cartography and GIS. John Wiley & Sons, 2011. 232 p.
Yang C. Introduction to GIS Programming and Fundamentals with Python and ArcGIS. CRC Press, 2020. 328 p.
Stephenson B., The Python Workbook. Springer, 2014. 165 p. Lee Kent D., Hubbard S. Data Structures and Algorithms with Python. , Springer, 2015. 363 p.
Further reading
Carreira P. Geospatial Development By Example with Python. Birmingham; Mumbai: Packt Publishing, 2016. 340 p. E-grāmata. EBSCO. Resurss pieejams ar LLU IS lietotājkontu. Pieejams: https://search-ebscohost-com.ezproxy.llu.lv/login.aspx?direct=true&db=e000xww&AN=1163843&site=ehost-live&scope=site Fundamentals of Computer Programming with C# [tiešsaiste] [skatīts 17.01.2022]. Pieejams: https://introprogramming.info/wp-content/uploads/2013/07/Books/CSharpEn/Fundamentals-of-Computer-Programming-with-CSharp-Nakov-eBook-v2013.pdf
Periodicals and other sources
Latvijas ģeotelpiskās informācijas aģentūra. Publikācijas. [tiešsaiste] [skatīts 17.01.2022]. Pieejams: https://www.lgia.gov.lv/lv/dokumenti
ESRI mājas lapa [tiešsaiste] [skatīts 17.01.2022]. Pieejams: http://www.esri.com Envirotech mājas lapa [tiešsaiste] [skatīts 17.01.2022] Pieejams: https://www.gisbaltic.eu/lv-lv/home
Notes
Professional higher education bachelor’s study program “Geoinformatics and Remote Sensing”in full-time studies and part-time studies