Tham khảo tài liệu 'risk management in environment production and economy part 4', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Generation of Added Values Products Supporting Risk Analysis 49 Fig. 1. Synthetic risk cycle diagram The ASI-SRV project has developed data processing modules dedicated to the generation of specific products meeting the user needs and to the dissemination of the information by means of dedicated Web-GIS. ASI-SRV system provides the capability to manage the import many different EO data into the system it maintains a repository where the acquired data are stored and generates selected products which are functional to the phases described above. All technical choices and development of ASI-SRV are based on flexible and scalable modules which will take into account also the new coming space sensors new processing algorithms considering the national and international scenario in the space technologies. An important step of the project development regards the technical and scientific feasibility of the provided products. In fact the technical feasibility depends on the data availability accuracy algorithms and models used in the processing and of course the possibility to validate the results by means of comparison with other independent measurements EO and non-EO . Archived series and near real time NRT acquisition of EO optical and radar data are used to derive information on surface and plume characteristics building the knowledge for the two volcanic systems composing the test sites respectively Etna and Vesuvio Campi Flegrei. Considering the different type of volcanic activities characterizing the investigated volcanic complexes different stacks of products type are necessary to the User considering also the product feasibility. Each product is generated by a specific modules based on algorithm developed by the researcher during last decade. All these modules can process in parallel EO optical data generating huge volume of products to be stored in the ASI-SRV main database building a very long catalogue of geophysical parameters suitable for back analysis but also
