Show simple item record Li, Longzhuang Guardiola, Jose Liu, Yonghuai 2011-11-08T16:15:37Z 2011-11-08T16:15:37Z 2011-11
dc.identifier.citation Li , L , Guardiola , J & Liu , Y 2011 , ' Qualitative spatial representation and reasoning for data integration of ocean observing systems ' Computers, Environment and Urban Systems , vol 35 , no. 6 , pp. 474-484 . DOI: 10.1016/j.compenvurbsys.2011.04.002 en
dc.identifier.issn 0198-9715
dc.identifier.other PURE: 173293
dc.identifier.other PURE UUID: cc6e2c2f-8e44-4bc0-ae32-b366960bf5e0
dc.identifier.other dspace: 2160/7691
dc.identifier.other DSpace_20121128.csv: row: 4546
dc.identifier.other RAD: 10854
dc.identifier.other RAD_Outputs_All_ID_Import_20121105.csv: row: 4018
dc.identifier.other Scopus: 80053386233
dc.description.abstract Spatial features are important properties with respect to data integration in many areas such as ocean observational information and environmental decision making. In order to address the needs of these applications, we have to represent and reason about the spatial relevance of various data sources to facilitate retrieval and integration of data. In this paper, using the in situ ocean observing stations in the Gulf of Mexico as an example we develop a statistical method, the semi-circular method, based on the semi-circular normal distribution to uniquely reason directional relations between indirectly connected points in addition to adopt the state-of-the-art qualitative spatial representation and reasoning techniques to represent partonomic, distance, and topological relations. In the experiment, the performance of the semi-circular method is compared with three existing methods, and the experimental results show that the statistic-based semi-circular method obtains the overall adjusted correct ratio of 88.1% by combining qualitative distance and directional relations, which achieves the comparable accuracy as and is slightly better than the probabilistic-based heuristic method. en
dc.format.extent 11 en
dc.language.iso eng
dc.relation.ispartof Computers, Environment and Urban Systems en
dc.rights en
dc.title Qualitative spatial representation and reasoning for data integration of ocean observing systems en
dc.type /dk/atira/pure/researchoutput/researchoutputtypes/contributiontojournal/article en
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Vision, Graphics and Visualisation Group en
dc.description.status Peer reviewed en

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