The goal of this class are:

1. Knowledge and understanding

To provide students with an in-depth understanding of signal and imaging acquisition and analysis techniques relevant to environmental applications, with a focus on advanced methodologies such as remote sensing, hyperspectral imaging, and satellite or telescope-based observation systems.

2. Applying knowledge and understanding

To enable students to apply signal and image processing techniques to high-resolution data acquired through complex remote sensing systems, and to extract meaningful features using state-of-the-art Machine Learning and Artificial Intelligence tools.

3. Making judgements

To develop students’ ability to critically assess the quality and reliability of acquired environmental data, to select appropriate AI models and processing pipelines, and to interpret results in light of application-specific constraints and objectives.

4. Communication skills

To enhance students’ capacity to effectively communicate complex signal and image analysis processes and results, through technical reports, visual presentations, and interdisciplinary collaboration, using appropriate terminology and data visualization tools.

5. Learning skills

To foster autonomous learning in the rapidly evolving fields of environmental sensing, imaging technologies, and AI-based data analysis, enabling students to keep pace with emerging tools, methodologies, and scientific literature.