GEM

Global Earth Monitor project (GEM) 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 (EO) DATA-EXPLOITATION MODEL which will dramatically enhance the exploitation of Copernicus data. For the first time a 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 (GAN, RNN, LSTM, Attention & Bayesian Deep Learning, Curriculum Learning, Incremental learning, Meta-learning, Hybrid modelling) will be combined to construct GLOBAL, SCALE-INDEPENDENT interpretation models with the special focus on CAUSALITY and CHANGE DETECTION. Technological and Methodological innovations will be combined into a unique CONTINUOUS MONITORING PROCESS. The process, based on seamless combination of data interpreted with sub-resolution, native resolution and super-resolution methods, will deliver 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 10-month demonstration - operational continuous monitoring of 10 MIO square km area.