Dryland ecosystems face mounting pressures from climate extremes, desertification, and unsustainable land use, while remaining critical for biodiversity, carbon sequestration, and human livelihoods. TwinDryLands develops a high-resolution Digital Twin that integrates Earth observation, artificial intelligence, dynamic vegetation modelling, and causal inference. The project uses very high-resolution satellite imagery and AI-based mapping to improve the characterisation of vegetation structure and functioning and to support dryland restoration planning, policy, and sustainable land management.