WORKSHOP | Interactive (geospatial) data analysis at HPC scales with RS-DAT and Python

With the volume of Remote Sensing (RS) and Earth Observation (EO) data increasing incessantly, existing and future workflows often must be scaled up beyond the computational and storage resources available in workstations. In this regard, solutions using high-throughput and high-performance computing (HTC/HPC) systems, which offer full control over available hardware, software, and data, are excellently suited to serve the needs of researchers and can readily support the migration of existing workflows. Furthermore, they are generally available through national infrastructure providers on a merit-driven no-cost basis.

This workshop will introduce participants to the RS-DAT framework and Python-Dask based ecosystem, providing low-barrier access to and scaling of python-based workflows on HPC systems, with particular focus on the infrastructure provided for the Dutch community by SURF. The session will cover the tools for data access, retrieval, and storage, and demonstrate the scaling up of processing and analysis workflows focused on EO datasets.