TAILIEUCHUNG - Risk Management in Environment Production and Economy Part 5

Tham khảo tài liệu 'risk management in environment production and economy part 5', 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 69 influence the distribution of future eruptive products namely lava flows and need to be carefully mapped and measured for the assessment of the hazard from future eruptions. The new distribution of ash and lava flow have been evaluated by means of spectral classification using supervised and unsupervised technique. Beside this surface classification an evaluation of the thickness of eruptive products will be carried out in the field using hand-held GPS to create a model of the new post-eruptive surface morphology in areas affected by the eruptive activity. GPS is the instrument most suitable for obtaining a high quantity of data at a resolution comparable to that of the satellite images used for the project This new morphology will be superimposed on the pre-eruptive morphology to reveal the approximate 5 m thickness of the new products in any site and obtain volume estimates Fig. 7 . Fig. 7. Example of post eruptive lava distribution map product generated and delivered by means of dedicated gateway Multiparametric analysis All the above mentioned early-warning products have been used to verify the capability of dedicated statistical model to support the monitoring activities. ASI-SRV project has implemented a well-known model called Bayesian Event Tree - Eruption Forecast BET-EF Marzocchi et al. 2009 which is an already developed algorithm for the eruption model and has been adapt as it is to the ASI-SRV needs. The BET-EF model represents a flexible tool to provide probabilities of any specific event at which we are interested in by merging any kind of available and relevant information such as theoretical models a priori beliefs monitoring measures and real time and past data. It is mainly based on a Bayesian 70 Risk Management in Environment Production and Economy procedure and it relies on the fuzzy approach to manage monitoring data. The method deals with short- and long-term forecasting .

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