- 2025-07-14 –, Club E
- 2025-07-14 –, Club E
All times in Europe/Prague
GeoData isn’t just about shapefiles and small satellite images anymore. With the explosion of open data portals, satellite constellations, and IoT devices, geospatial datasets can easily reach terabytes in size. This advanced, hands-on workshop will teach you how to efficiently load, process, and analyze large-scale geospatial data in Python. We’ll cover distributed frameworks like Dask for parallelizing vector and raster processing, advanced data structures for high-performance spatial operations, and best practices for memory and I/O optimization. Whether you’re dealing with national-scale road networks or multi-temporal satellite imagery, you’ll come away with concrete strategies and code examples to tackle big GeoData on modern hardware and in the cloud.
Intermediate
Martin Christen is a specialist in Geoinformatics and Computer Graphics with a strong focus on Python-based geospatial technologies. His interests include 3D geoinformation, virtual and augmented reality, interactive 3D maps, and deep learning. Martin is an active member of the Python community: he contributes to open-source projects, teaches Python-related topics, and organizes the annual GeoPython conference. He also serves on the board of the Python Software Verband e.V.
Martin Christen is a specialist in Geoinformatics and Computer Graphics with a strong focus on Python-based geospatial technologies. His interests include 3D geoinformation, virtual and augmented reality, interactive 3D maps, and deep learning. Martin is an active member of the Python community: he contributes to open-source projects, teaches Python-related topics, and organizes the annual GeoPython conference. He also serves on the board of the Python Software Verband e.V.