Sahar Sharifi

My PhD research focuses on leveraging Earth Observation data for the assessment and monitoring of urban, peri-urban, and wetland environments. The project explores how innovative EO and AI capabilities -particularly Very High Resolution (VHR) satellite imagery- can be integrated with ground-based datasets to evaluate key habitat attributes such as quality, connectivity, and ecological networks. These analyses aim to improve our understanding of ecosystem structures and contribute to nature recovery and biodiversity enhancement across selected research sites.

In recent years, machine learning, particularly deep learning, has made substantial progress and has become a transformative component of EO-based environmental monitoring. The integration of these data-driven methods with high-resolution remote sensing imagery enables more accurate, efficient, and scalable analyses of complex ecological systems. This fusion between AI and EO advances scientific understanding and provides actionable insights for sustainable urban planning, ecosystem restoration, and adaptive environmental management.