Module Title: Bridging AI and Earth Observation (AI+EO)

Module Description:

In this educational module, we will delve into the exciting intersection of Artificial Intelligence (AI) and Earth Observation (EO). AI and EO are two powerful technologies that, when combined, have the potential to transform our understanding of our planet, drive innovation, and address critical global challenges.

Recommended Prerequisites:

Basic knowledge of AI concepts and some familiarity with Earth Observation data would be beneficial but not mandatory.

Module Objectives:

1. Introduction to AI and EO: Begin with an overview of the intersection of AI and EO, explaining their individual significance and how they complement each other.
2. Use Cases: Explore real-world use cases where AI and EO have been successfully applied in the domains of energy, agriculture, health, and energy.
3. AI Tools and Services for EO: Explore various AI techniques, including machine learning and deep learning, and how they are applied to EO data for analysis and interpretation.
4. Ethical Considerations: Discuss the ethical considerations and challenges related to AI and EO, including privacy and data security.

Modules:

The program comprises the following modules:

• Module 1: Introduction to AI and EO Data link
  • The European EO ecosystem and the Copernicus programme
  • The European AI ecosystem and the AIoD platform
  • AI and EO initiatives and the AI4Copernicus project
• Module 2: AI and EO Data for Security link
  • The Classic Security concept
  • The New Security concept
  • AI in the Space and Security Domain
• Module 3: AI and EO Data for Agriculture link
  • Why Food Security & Agriculture?
  • AI & Remote Sensing in Food Security & Agriculture
  • Indicative scenarios
• Module 4: AI and EO Data for Health link
  • Air pollution and the effect on health
  • The role of AI in air quality monitoring and the Copernicus CAMS service
  • Indicative scenarios
• Module 5: AI and EO Data for Energy link
  • Where can energy installations be built?
  • Where will there be energy demand?
  • How to improve renewable energy production efficiency?
• Module 6: Technical Services for AI and EO Data link
  • Bootstrapping services targeting security, agriculture, and health domains
  • Preprocessing tools, AI services and ML models for EO Data
• Module 7: Semantic and QA tools for EO link
  • Semantic and linked data tools for EO (Tools for transformation, querying, interlinking, federating and visualizing big linked geospatial data)
  • The EarthQA question answering engine
• Module 8: Responsible AI Perspectives for AI and EO Data link
  • Trustworthy AI perspectives: an overview
  • AI Legal Aspects
  • How to ensure that you AI&EO solution is Trustworthy ?
• Module 9: AI & EO Business Aspects link
  • Why AI matters for EO?
  • Overview of the AI & Earth Observation Market & Trends
  • Ecosystem approach for AI&EO companies
  • How to kick-start your own company

Mode:

Self-paced

Target Audience:

This module is designed for students, researchers, start-ups, and anyone interested in harnessing the combined power of AI and Earth Observation to address environmental, societal, and economic challenges. By the end of this module, participants will have gained a comprehensive understanding of how AI and EO can work together to unlock new insights, drive innovation, and contribute to a more sustainable future.

Acknowledgement

This workshop is partially supported by the EC H2020 project AI4Copernicus, grant agreement No. 101016798.