Earth Observation Training for Official Statistics
Online Training | January 2026
This online training series is designed for National Statistical Institutes (NSIs) and other organisations involved in the production of official statistics. The programme provides a practical introduction to the use of Earth Observation (EO) data, tools and workflows that can support and enhance statistical processes.
Across three sessions, participants will gain both conceptual understanding and hands-on experience with EO resources, including Copernicus datasets and QGIS-based workflows.
Who Should Attend
This training series is intended for:
- Professionals working in National Statistical Institutes
- Public authorities involved in geospatial analysis or statistical production
- Users seeking to incorporate Earth Observation into statistical workflows
Expected Outcomes
By the end of the series, participants will:
- Gain a foundational understanding of EO in official statistics
- Learn to access and visualise Copernicus data in QGIS
- Explore advanced EO applications across thematic domains
- See practical examples of EO integration in operational settings
If your organisation aims to strengthen its geospatial and EO capacities, this training series provides a clear and structured starting point. We look forward to your participation.
AGENDA & RESOURCES
Session 1 – Introduction to EO for Official Statistics
Time: 16 January 2026 | 14:00–15:30 CET
Content: A high-level overview of EO concepts, Copernicus missions, and key datasets relevant for NSIs and other public bodies.
Materials
Session 2 – Practical Session: QGIS & Copernicus Use Cases
Time: 23 January 2026 | 14:00–16:00 CET
Content: Hands-on guidance on how to access, download, and visualise Copernicus data directly in QGIS.
Materials
- Remarks: Please download QGIS (link) and register for Copernicus Browser (link) before the session.
- Recording: Youtube.
- Slides: No slides.
- Useful links:
Session 3 – Advanced EO Applications
Time: 30 January 2026 | 14:00–15:30 CET
Content: An exploration of more advanced EO workflows, including agricultural statistics, land cover change detection, SDG-related applications, and case studies on integrating EO-based products into existing statistical production systems.
Materials
