OBJECTIVE 1
Stimulate the development of new spatiotemporal modelling applications with the release of the most comprehensive spatiotemporal datasets ever created
Stimulate the development of new spatiotemporal modelling applications with the release of the most comprehensive spatiotemporal datasets ever created
Implement and benchmark novel DL architectures for Change Detection that can realize the full potential of the new combined data sources
Demonstrate large scale thematic Change Detection with high temporal cadence using daily harmonized multisensor, multiscale imagery.
Demonstrate improved LULC classification using daily harmonized multisensor, multiscale imagery.
The emergence of powerful new artificial intelligence methodologies must be matched by tools that enable the remote sensing community to exploit their full potential when applied to the anticipated increasing volumes, cadence and diversity of sensor data. As it has been proved in other fields where artificial intelligence is revolutionizing entire industries (e.g. the self-driving car, video processing, voice recognition, face recognition), the availability of large volumes of training data representative of the phenomenologies to be modeled is key to overcoming a fundamental obstacle. A related challenge is the issue of sensor interoperability.
Revolutionary machine learning core technology and overall framework to enable a new spatiotemporal level of data exploitation and drive the next generation of Copernicus Land Monitoring solutions.
Higher accuracy for the monitoring of compliance with environmental policies, Improved measurements of land degradation, Improved management of forest resources
Improved robustness for food security, Improved monitoring of carbon
stocks, Increased level of transparency, More agile interventions
In September 2015 the United Nations adopted the 2030 Agenda to achieve a better and sustainable future for all. We have only a decade to meet its Sustainable Development Goals (SDGs), the most ambitious agenda for global change in UN history. The measurement of sustainability has been a topic of debate among researchers, policy makers and other stakeholders. The 17 SDGs and related targets have been designed to be monitored through a set of global indicators, 93 of which are designed to measure the environmental dimensions of “sustainable development.” Alarmingly, nearly five years into the agenda the UN Environmental Programme has found that we have little to no data on 68 percent of them.
Learn MoreThe RapidAI4EO projects brings together Planet Labs, the operator of the world’s largest fleet of Earth-imaging satellites, Vito, the main production center of the Copernicus Global Land Service, Vision Impulse, a recent spin-off of German Research Center for Artificial Intelligence, the International Institute for Applied Systems Analysis (IIASA), and Serco Italia, a worldwide service provider to governments, international agencies and industries, and operator of the ONDA DIAS platform.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101004356.