Challenges and Opportunities on the synergism of multiple remote sensing data sources in deep learning applications

The recent increase of remote sensing systems and associated technologies opens a broad range of opportunities for improving earth observation applications. The collected data may supply a continuous stream of information that allow synergism and novel deep learning applications. Alternatively, the synergism has been validated using unmanned aerial vehicles that are cost-effective, compared to orbital and airborne sensors, and can also be equipped with several onboard sensors. However, to fully benefit from these technologies, several initiatives from both academia and industry have been carried out. However, the massive amount of data still poses new challenges ranging from storage, data integration to data fusion learning issues. This thematic session aims to provide new insights to this multidisciplinary field, by fostering discussion about existing cutting-edge solutions and opportunities in the area. Public datasets and research opportunities will also be promoted