The Global Earth Monitor project is addressing the challenge of continuous monitoring of large areas in a sustainable cost-effective way. The goal of the project is to establish a new disruptive Earth Observation Data - Exploitation model which will dramatically enhance the exploitation of Copernicus data.
For the first time, continuous monitoring of the planet on the global/regional scale will be enabled for a sustainable price. Disruptive innovations are planned in the technology and in the methodology domain, where a proprietary concept of Adjustable Data Cubes (a combination of static and dynamic data cubes) will be developed and integrated with EO-oriented open-source Machine Learning (ML) framework eo-learn.
During the project, eo-learn will be upgraded to consume ML technologies from widely accepted ML frameworks and to adapt/evolve them to specifics of EO-data interpretation. Modern ML technologies and approaches will be combined to construct global, scale-independent interpretation models with a special focus on causality and change detection.
Technological and methodological innovations will be combined into a unique continuous monitoring process. The process, based on a seamless combination of data interpreted with sub-resolution, native resolution, and super-resolution methods, will deliver an optimal combination of processing/storage costs – enabling continuous monitoring of large areas for just a fraction of current costs.
The concept of continuous monitoring will be validated through the development of five specific use-cases and through their employment in a 6-month demonstration - operational continuous monitoring of 10 MIO km2 area.