This presentation covers how advanced machine learning algorithms can analyze large volumes of satellite imagery and remote sensing data to support tasks like land cover change detection, flood detection, and environmental monitoring.

It highlights real-world applications, challenges such as data quality and model interpretability, and the future potential of AI-driven Earth observation.

A case study will illustrate how machine learning improves our ability to extract valuable insights from geospatial data for informed decision-making.