Wildfire susceptibility maps flexible querying and answering

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Abstract

Forecasting natural disasters, as wildfires or floods, is a mandatory activity to reduce the level of risk and damage to people, properties and infrastructures. Since estimating real-time the susceptibility to a given phenomenon is computationally onerous, susceptibility maps are usually pre-computed. So, techniques are needed to efficiently query such maps, in order to retrieve the most plausible scenario for the current situation. We propose a flexible querying and answering framework by which the operator, in charge of managing an ongoing disaster, can retrieve the list of susceptibility maps in decreasing order of satisfaction with respect to the query conditions. The operator can also describe trends of the conditions that are related with environmental parameters, assessing what happens if a dynamic parameter is increasing or decreasing in value. © 2013 Springer-Verlag Berlin Heidelberg.

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APA

Arcaini, P., Bordogna, G., & Sterlacchini, S. (2013). Wildfire susceptibility maps flexible querying and answering. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8132 LNAI, pp. 352–363). https://doi.org/10.1007/978-3-642-40769-7_31

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