Earth observation (EO) is integral to numerous industries, including surveillance, defense, climatology, ecosystem monitoring and restoration, water quality assessment, maritime tracking, pollution monitoring, and precision agriculture. The increasing number of EO satellites in orbit utilize varied hardware for Earth surface monitoring, ranging from line scanners to zone and mosaic cameras.
This hardware must address multiple factors such as Earth’s atmosphere, water vapor, cloud cover, and the specifics of orbital speed and altitude, with some corrections requiring onboard processing. Consequently, EO operations in space present demanding engineering and scientific tasks. Imaging devices are advancing, providing effective sensor capabilities beyond the visual spectrum, while revisit times are decreasing and ground resolutions are improving.
These developments mean that efficient management of data, particularly high-resolution multispectral time-series imagery, is essential due to constraints in hardware availability, power consumption, and computational resources. The data cube methodology shows potential for addressing these issues by effectively storing and organizing long time-series imagery and metadata in a machine-readable format.
To explore these technologies in practice, this hands-on workshop provides participants with a guided introduction to EO systems, data management techniques, and real-world applications.
Coffee Break – 10:20 – 10:40
13:15 – 14:00 Networking & Lunch
