Space technology connected with Artificial Intelligence and machine learning techniques is one of the most rapidly developing field of science and also play a key role to control disaster by space like Covid-19 outbreak. While space technologies have been successfully applied to a small number of macroeconomy and heath care related matters over the last decade, there is neither a significant utilization of space elements nor a systematic analysis of needs for space assets in this sector yet. There are a significant number of indirect parameters observable from space that can be correlated to the impact on the economy of natural, health (including epidemic) and man-made disasters. Classical environment parameters (geographical, climatological and hydrogeological) and man induced impact on the environment (pollution, heat) can be combined with economic parameters of human activities impacted by the epidemic including transportation, industry, and commerce. Specific human activities can be directly correlated with the progression of the diseases i.e. increase of heat delivered by crematorium in the affected areas as well as in the dwelling areas due to lock-down restrictions. All these “observed parameters” need to be correlated to macro parameters related to the progress of the epidemic and its impact of the of the infection to the economy at different scales. At medium- and long-term time scale, this methodology enables the near real-time monitoring of macroeconomic parameters during the recovery phase following the end of the emergency outbreak. The project EYE intends to propose a prototype service based on Copernicus data, automatic image processing supported by artificial intelligence integrated with modelling and statistic and geospatial data into an IT platform able to provide econometric and epidemiologic nowcasting and forecasting data.

The seismic movements of the ground have a strong impact on the structural stability of the Cultural Heritage very often characterized by old construction methods and materials but still with a consistent density of population. To have an idea of the dimension of the phenomena, the damage on the CH asset declared by the Italian Ministry of CH, caused by the recent earthquakes in Centre Italy, has been assessed in 2 Billion Euro plus the death toll caused by the collapse of several buildings. Authorities responsible for the preservation of CH to the future generations are well aware of the huge costs required by rehabilitation intervention compared to preventive ones. Risk information becomes fundamental to reduce the vulnerability of heritage and to minimise the economic losses, helping disaster managers and cultural heritage professionals to design mitigation measures, set priorities and invest in resilient cultural heritage to mitigate the restoration costs and the death toll. The project ERA4CH addresses the development of a series of tool, combining Artificial Intelligence with structural stability models, advanced remote sensing techniques, image processing, geotechnics and cadastral data sets in a GIS application for damage assessment and long-term monitoring of historic centres. This innovative methodology and tools will enable effective monitoring and management of the historic centres to mitigate the effects of the catastrophic events by enabling preventive intervention in the areas where the majority of the damage is expected. Three representative test cases are proposed: the historic city of Narni (Italy), candidate to the UNESCO site list, the historical centre of Chania (Crete, Greece) and Strovolos (Nicosia, Cyprus).