This work deals with a useful joined application of Kalman filter and Kriging technique for a continuous and accurate environmental monitoring in a disaster scenario or generally in a critical event, necessary to assure an efficient and timely risk management. A suitable Decision Support Systems (DSS) is proposed to provide assistance for the “early warning" of a critical situation, so to improve the "first response" to the happened event. Using the proposed modelling techniques in data environmental analysis permits both the characterization and validation of all measured big data coming from a suitable Space- Aided Distributed Sensor System (SADSS). In particular, the proposed technique is able also to predict the values of the monitored environmental parameters, so it results a very useful analysis tool, especially when there are many missing ,erroneous or invalid data.
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