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A point-set-based approximation for areal objects: A case study of representing localities

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dc.contributor.author Liua, Y
dc.contributor.author Yuan, Y
dc.contributor.author Xiao, D
dc.contributor.author Zhang, Y
dc.contributor.author Hu, J
dc.date.accessioned 2013-10-21T02:37:32Z
dc.date.available 2013-10-21T02:37:32Z
dc.identifier.uri http://dl.lib.mrt.ac.lk/handle/123/8701
dc.description.abstract Since partonomy knowledge is an important component of human cognition, we propose a point-set-based region (PSBR) model to approximate areal objects, especially vague areal objects. Two major properties of this model are that it is cognition-accordant and that it can represent vague regions easily. Given a point-set-based model, we can estimate the corresponding region using various methods, including convex hull, minimum bounding box, one-class support vector machine, and point density. We can examine the spatial relationships between two PSBRs using the derived areal objects. Additionally, we present a number of methods to compute relationships directly, based on two PSBRs. In the case study, we use a number of localities in China to demonstrate applications of the PSBR model. The proposed model can be implemented easily in an object-relational database management system. Hence, it provides a reasonable representation for vague objects that takes both manageability and approximation into account, especially now that Web 2.0 is making point data more convenient to collect.
dc.language en
dc.subject Point-set-based approximation
dc.subject Vague areal object
dc.subject Locality
dc.title A point-set-based approximation for areal objects: A case study of representing localities
dc.type Article-Full-text
dc.identifier.year 2009
dc.identifier.journal Computers, Environment and Urban Systems
dc.identifier.issue 2
dc.identifier.volume 34
dc.identifier.database Science Direct
dc.identifier.pgnos 28-39


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