This lesson provides an integrated introduction to multi-source remote sensing for agricultural monitoring and climate adaptation. Participants explore the principles, benefits, and challenges of combining optical and radar data (e.g., Sentinel-1, Sentinel-2, PlanetScope) to enhance crop monitoring and yield estimation. The lectures cover key topics including the use of RS time series to monitor crop phenology and extract Land Surface Phenology (LSP) metrics, as indicators of crop growth dynamics and productivity. The session also addresses the limitations of optical RS data due to cloud cover and demonstrates how data fusion with radar observations can bridge temporal gaps, enabling the generation of synthetic NDVI for more continuous and accurate crop monitoring. Together, these lectures provide a foundation for understanding how multi-sensor RS and AI-driven approaches can support sustainable agricultural management under changing climatic conditions.
Dr. Magdalena Main-Knorn (Contact: )
Dr. Gohar Ghazaryan
Prof. Patrick Hostert, EO Lab HU
Kazi Jahidur Rahaman
Dr. Anastasiia Safonova
Dr. Leonardo Inforsato
Anna Zoe Taege