Held in Ljubljana from 22nd to 25th of September 2025, this intensive summer school offers a unique opportunity to delve into the cutting-edge intersection of Artificial Intelligence (AI) and Earth Observation (EO), combined with the essential skills for managing large-scale data and workflows in modern computing environments. Participants will gain theoretical knowledge and practical experience in applying AI techniques to analyze EO data, optimizing AI performance, managing complex workflows with Kubernetes, and handling massive datasets.

Introduction

The delineation of agricultural field boundaries from satellite imagery is crucial for precision agriculture, land management, policymaking and crop monitoring.

It can be a stand-alone solution or as the first stage for crop classification, advanced soil moisture analysis, yield forecast, the estimation of damages to crop yield due to natural (e.g. drought, floods) and more.

In the DaFab project, field delineation, which involves outlining agricultural parcels with polygons, offers a solution to several difficulties encountered in yield forecasting and crop classification tasks. This approach is more effective than traditional pixel-by-pixel classification maps because of the reasons:

DaFab workshop will be held at High Performance, Edge And Cloud computing conference HiPEAC 2025 in Barcelona. Project members will showcase project plans and technologies and present an on-line demonstration of existing prototype. The workshop will be held on January 20th in Barcelona.