Discovering spatio-temporal relationships a case study of risk modelling of domestic fires

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Spatenková, Olga
dc.date.accessioned 2012-08-24T07:36:53Z
dc.date.available 2012-08-24T07:36:53Z
dc.date.issued 2009
dc.identifier.isbn 978-952-248-233-4 (electronic)
dc.identifier.isbn 978-952-248-191-7 (printed) #8195;
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/4727
dc.description.abstract A systematic risk analysis for mitigation purposes plays a crucial role in the context of emergency management in modern societies. It supports the planning of the general preparedness of the rescue forces and thus enhances public safety. This study applies the principles of knowledge discovery and data mining to support the development of a risk model for fire and rescue services. Domestic fires, which are a serious threat in an urban environment, are selected to demonstrate the methods. The aim of the research is to identify important factors that contribute to the probability of the occurrence of domestic fires. Various physical and socio-economic conditions in the background environment are analysed to provide an insight into the distribution of domestic fires in relation to underlying factors. Following the cross-disciplinary nature of data mining, this study offers a set of distinct methods that share the same goal - to identify patterns and relationships in data. The methods originate in different scientific fields, such as information visualisation, statistics, or artificial intelligence. Each of them reveals different aspects of the existing relations, which supports an understanding of the phenomenon and thus expands the expert knowledge. The application of data mining techniques is not straightforward because of the specific nature of geospatial data. This study documents the analysis process in order to provide guidelines for potential future users. It considers the suitability of the methods to handle spatial and spatio-temporal data with special attention to the GIS-motivated conceptualisation of the problem being analysed. Furthermore, the requirements for the user to be able to apply the methods successfully are discussed, as is the available software support. en
dc.format.extent Verkkokirja (7574 KB, 130 s.)
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Teknillinen korkeakoulu en
dc.subject.other Geoinformatics en
dc.title Discovering spatio-temporal relationships a case study of risk modelling of domestic fires en
dc.type G4 Monografiaväitöskirja fi
dc.contributor.department Maanmittaustieteiden laitos fi
dc.subject.keyword domestic fires en
dc.subject.keyword Helsinki en
dc.subject.keyword risk analysis en
dc.subject.keyword emergency management en
dc.subject.keyword spatio-temporal data en
dc.subject.keyword geographical data en
dc.subject.keyword geospatial data en
dc.subject.keyword visual data mining en
dc.identifier.urn URN:ISBN:978-952-248-233-4
dc.type.dcmitype text en
dc.type.ontasot Väitöskirja (monografia) fi
dc.type.ontasot Doctoral dissertation (monograph) en


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