Tomaž Žagar
I’ve been building GIS solutions at the Geodetic Institute of Slovenia for over 15 years, working across the stack on everything from web mapping applications to data processing pipelines. My background is in biomedical engineering, but I found my way into geospatial tech through the field of automation — and I’ve been streamlining processes and visualizing data ever since.
Sessions
This paper introduces a scalable open-source system using GRASS, TorchGeo, Python libraries, and HDF5 to map impervious surfaces from orthophotos and Sentinel-2 imagery. Outputs are vectorized, compared with agricultural and forested lands, and analyzed for environmental impacts like soil sealing to support sustainable land management and restoration.
We present i.hyper, a multimodular toolset for processing hyperspectral satellite imagery in GRASS. It supports the import of PRISMA, EnMAP and Tanager products through a dedicated import module and provides preprocessing, visualization and export. The i.hyper addon is available in the official GRASS Addons repository.