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701-1674-00L 5 Credits DR , MSC D-USYS , D-BAUG , D-ERDW , D-MAVT , D-PHYS , D-ITET

GIS III: Advanced methods & Competencies

GIS III: Advanced Methods & Competencies

Lecturers & Examiners: Dr. Andri Baltensweiler, Monika Anna Maria Niederhuber

Prerequisites: 701-0951-00L GIS I: Basics of Geographic Information Systems and 252-0840-02L Anwendungsnahes Programmieren mit Python. Knowledge and skills equal those of these courses.

VVZ CR n/a

Last Updated: 2026-06-03 00:14:19

Abstract

This course provides an in-depth exploration of advanced spatial data modeling and analysis, including e.g. network or least-cost analyses. It introduces geoprocessing techniques using Python and ArcGIS, emphasizing the automation and scripting of complex GIS workflows.Upon completion, students will have acquired the technical and methodological foundations for advanced GIS analysis.

Objective

Upon successful completion of the course, students will be able to: 1. Apply advanced spatial data modelling and analytical methods to more complex geographic task and problems. 2. Design and implement automated geoprocessing workflows using ArcGIS Pro and Python to enhance analytical efficiency and reproducibility. 3. Critically evaluate the suitability of analytical techniques for specific spatial questions and datasets. 4. Integrate methodological, technical, and conceptual GIS competencies to solve real-world spatial planning and decision-making tasks.

Content

The course covers advanced spatial data modelling and analysis techniques, including suitability, visibility, shadow, network, and least-cost analyses. Emphasis is placed on geoprocessing and automation of complex workflows using ArcGIS (arcpy) and Python. Students also integrate open-source GIS packages into their scripts. Through applied project work, they combine multiple data sources, develop reproducible GIS methods, and critically evaluate analytical approaches in spatial planning and environmental contexts.

Resources

Literature

1) Chang Kang-tsun (2016): Introduction to Geographic Information Systems. University of Idaho - Eighth edition. 2) Silas T. (2022): Python for ArcGIS Pro: automate cartography and data analysis using ArcPy, ArcGIS API for Python, notebooks, and pandas. Packt Publishing. 3) Crawford D., Yaw D. (2025): Advanced Guide To Python in ArcGIS. ESRI Press.

General Information

Language: English
Levels: DR , MSC
Frequency: Yearly recurring

Examination

Type: ungraded semester performance

You should expect to spend approximately 10–12 hours completing the exercises.Upon completion of the GIS and Python modules, an intermediate examination will be conducted for each. Detailed information will be provided during the first week of the semester.

Registration & Places

Max Places: 25
Signup End: 03.03.2026

Course Components

Type	Title	Time & Place	Hours
lecture with exercise	GIS III: Advanced Methods & Competencies Lecture: Wednesday 10:15-12:00 Exercises: Wednesday 14:15-16:00	Wed 10:15-12:00 (RZ F 21) Wed 14:15-16:00 (NO D 39)	4 h weekly

Offered In

Spatial Development and Infrastructure Systems Master
- Master Studies (Programme Regulations 2021)
  - Major Courses
    - Major Courses for all Majors
Environmental Sciences Master
- Major in Forest and Landscape Management
  - Methods and Tools
- Major in Environmental Systems Policy
  - Modeling and Statistical Analysis
- Major in Forest and Landscape Management (from HS25 onwards) (Students who start the specialization in Forest and Landscape Management in HS25 or later study according to the 2013 regulations, edition 29.04.2025 - 8. The new structure of this specialization is shown in the current VVZ. Students who started the specialization in Forest and Landscape Management before HS25 can complete the specialization in accordance with the study guide 2024/25.)
  - Data
Doctorate Environmental Systems Sciences (More Information at: )
- Subject Specialisation
  - Environmental Sciences
    - Forest and Landscape Management
Space Systems Master
- Deep Track Courses (At least 20 credits must be completed within the deep track courses. Surplus credit points can be counted towards the electives.)
  - Earth Observation
    - Deep Track Earth Observation (These courses can be credited either as a specialization subject or as an elective subject.)