Applied Geoinformatics (Master of Science)
After successfully graduating from my Bachelor’s, it was clear to me to study Applied Geoinformatics in Salzburg. The program offers a unique combination of practical relevance, interdisciplinarity, and international scope. Here, I am able to acquire knowledge of a diverse set of methods such as machine learning algorithms, web development, big data analyses and a broad range of fields such as smart city initiatives or geomarketing. As an internationally recognized center of excellence, the interfaculty department is deeply connected with academia, industry, and civic organizations, providing a broad range of practical seminars and real-world experiences to learn from during my studies.
The department
Please watch the video on the right to get better insights into the Department of Geoinformatics in Salzburg and the discipline in general. More information can be found here.
Completed courses (by October 2024)
Introductory seminar course which dealt with automatic image analysis of remotely sensed data. Topics included RADAR, LiDAR, radiometric corrections, CNNs, Object-based Image Analysis, advanced classifiers (SVMs, random forest etc.).
This course built upon the “Methods in Spatial Analysis” course and allowed the students to focus on a specific methodology of spatial analysis. I used landscape metrics to asses lynx habitats. Click here for the results.
Introductory course to Big Data and Machine Learning methods. It was graded upon a final assignment which dealt with predicting wines from their chemical characteristics using ML models.
This course dealt with disaster risk management and the role of geospatial information for managing natural hazards.
The course provided insights into primary geodata capture methods like GNSS, photogrammetry, and LiDAR.
Exam on the definition, usage and implementation of geodata models and basic geospatial data formats.
Exceptionally, this seminar explored different theoretical concepts of Geoinformation Science (GIScience) by reading and debating about its fundamental theory, societal implications, as well as the historic, current, and future developments of the research domain.
This project course dealt with the conduction of an own research project. Students had to work on a self-chosen topic, from the broad idea until the submission of a scientific paper. Acces the results here.
This course dealt with creating a dashboard on a migration topic by using a modern, transparent, and effective Spatial Data Infrastructure (SDI). This included the usage of Database Management Systems (e.g. PostGIS) and the publishing of Web Services (e.g. WMS, WFS). The results can be found here.
Weekly assignments about different topics and techniques of spatial analyses. This included Distance Analysis, Selection and Aggregation, Network Analysis, Spatial Interpolation, Terrain Analysis, Visibility Analysis and Solar Power Potential Analysis. Click here for the results.
Online seminar about the theory and usage of Object-based Image Analysis.
This exam provided architectural, organizational and legal foundations for accessing, using and delivering geodata in spatially enabled IT-service infrastructures.
Seminar about proper scientific writing. Weekly writing assignments, including the creation of a short paper.
This lecture series provided an overview of different topics in geoinformatics.
Introductory course to software development. Written exam, as well as weekly practical coding assignments with Java. For the final assignment, GeoTools was used to integrate data from a CSV file and a OGC WMS service in a KML which was opened with Google Earth.
This course was about relevant statistics for the geospatial domain. This encompassed weekly R assignments on global and local spatial autocorrelation, variography, probabilistic interpolation, Point Pattern Analysis, OLS regression analysis etc..