A DTC is a virtual representation (or replica) of a Physical System (PS) within its environment. The DTC is continuously updated with real-time data throughout its lifecycle and, at the same time, can interact with and influence the PS. The PS produces data related to the system. The DTC takes as input such data and uses a set of models to carry on different operations and actions on the PS. The proposed DTC is structured with a set of data and models associated with the Geo-Physical System (GeoPS), able to make available a set of services corresponding to the functions of the DTC. The identified requirements have addressed the selection of the data used as input to the DTC. The data contain the information and can be simply classified in:
● EO data, like SAR satellite measurements, multi- and hyper-spectral measurements of
atmospheric parameters, data obtained from integration;
● Ground data detected from seismic and geodetic networks;
● Ancillary data, like DEM, hazard maps, vulnerability data.
Multisource and multiparametric datasets (later Level 1) are integrated to obtain added value products (later Level 2). Then, three model components can be defined according to the roles: i) Descriptive models (later Level 3), that reflect the GeoPS and its environment, representing the actual and past state of the GeoPS, enhancing the understanding and enabling the analysis; ii) Predictive models that predict information not yet measured, allowing decision making and trade off analysis. They also include models for simulation and AI (machine learning and neural networks), used for the detection of critical situations. iii) Prescriptive models that may identify system reconfiguration and remedy actions based on the results of what-if exercises, in the case Predictive models identify critical situations, possibly prevented with specific countermeasures. The high-level conceptualisation of the
GET-it DTC is reported in figure.
High level conceptualisation of the geohazard DTC in GET-it.