A comprehensive system for semantic spatiotemporal assessment of risk in urban areas

Abstract

Abstract Risk assessment of urban areas aims at limiting the impact of harmful events by increasing awareness of their possible consequences. Qualitative risk assessment allows to figure out possible risk situations and to prioritize them, whereas quantitative risk assessment is devoted to measuring risks from data, in order to improve preparedness in case of crisis situations. We propose an automatic approach to comprehensive risk assessment. This leverages on a semantic and spatiotemporal representation of knowledge of the urban area and relies on a software system including: a knowledge base; two components for quantitative and qualitative risk assessments, respectively; and a WebGIS interface. The knowledge base consists of the TERMINUS domain ontology, to represent urban knowledge, and of a geo‐referenced database, including geographical, environmental and urban data as well as temporal data related to the levels of operation of city services. CIPcast DSS is the component devoted to quantitative risk assessment, and WS‐CREAM is the component supporting qualitative risk assessment based on computational creativity techniques. Two case studies concerning the city of Rome (Italy) show how this approach can be used in a real scenario for crisis preparedness. Finally, we discuss issues related to plausibility of risks and objectivity of their assessment.