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EN
One of the most important applications of spatial data regards the ability to inform decision makers on spatially distributed and disaggregated hazards and risks, thus enhancing strategic decision making on how to manage and limit risks for a given area or region and prioritize investments. However, a full risk based adaptation assessment inside a Geographical Information System (GIS) can be cumbersome, since some complex tasks cannot be carried out directly. One example of these tasks involves Bayesian probabilistic analysis and decision making, which is a fundamental component of risk analysis, yet requires dedicated tools/software which usually do not belong to a standard GIS portfolio. For this reason, exploring the various capabilities of a GIS platform in connection with a Bayesian Network (BN) software is essential. The objective is to have an effective tool for knowledge representation and reasoning under the influence of uncertainty that can be displayed in a spatial manner. A case study using this tool was performed to assess the risk levels faced by the electrical distribution system of Long Island because of storm events as the Sandy Storm.
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