Selected Topics in Big Geospatial Data WS 2023/24

Aim of this Lecture

In this module, students learn advanced techniques from big geospatial data management and analysis and are exposed to selected topics in a real-world context on the big geospatial data cluster and beyond. The module introduces examples and the students select one topic and apply this in real world in the seminar running in parallel. Thereby, we bridge the gap between theory and practice and enable students to apply techniques from the field of big geospatial data management in practice. Topics originate from latest research in big geospatial data management as presented on International Conferences such as ICDM, ICDE, and ACM SIGSPATIAL GIS and in journals such as TKDE or GeoInformatica. These topics cover aspects such as data analysis, data distribution, data management, and spatial algorithms.

By completing this module, students will be exposed to state-of-the-art techniques from the quickly evolving field of big geospatial data management thereby deepening their understanding of challenges and solutions in the field of big data and spatial machine learning.

Time Table

Sessions are anounced via the moodle page.

Information for the Course

Content of the Course:

  • Lectures on Fundamental Topics of Geospatial Data Science
  • Project Work on a real world Geospatial Dataset
    • Learn and code together (rather a hackathon)

Imporant: All responsibility and liability is with the student group itself

Feedback and Support

We appreciate your feedback and support. You can drop us a line at any time. If you have interesting examples, you want to share with your fellow students, you can either send it to me via email or create a pull request on GitHub. I would be happy to include your examples, solutions and portations in the lecture.

Previous Student projects

During the semester, each group works on projects that include fundamentals, as well as state-of-the-art techniques in the field of big geospatial data management. During this course we provide some project ideas, which can be selected. Everyone is welcome to come up with own ideas.

Here is a list of selected projects from previous semesters:

  • Spatial Data Platforms (Twitter)
  • Pointcloud Processing Pipeline
  • ObservaToriUM (Published on AGIT’2021)
  • Forest and vegetation monitoring using Sentinel-2 Imagery in the northern part of Democratic Republic of Congo (Published on AGILE’2021)
  • Surface water monitoring of Lake Starnberg (Published on AGIT’2021)
  • Analysing the impacts of a choke point in a well-connected road network using big data
  • Change detection of air pollution particles from remote sensing data 
  • Land surface temperature change detection 
  • Synthetic Trajectory Data Generation from Mobility Simulation 
  • HPCsim - mobility simulation on raspberry Pi
  • Exploring and Visualizing Social Media Text Features from Mental Health Research in Space and Time

© 2020 M. Werner