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• W33393301 abstract "The advent of remote sensing, satellite, and information system technologies havenseen a rapid increase in the amounts of geographic spatial data being generatednand stored. In parallel there is an ever-growing commercial and private marketnfor the use of such data. Several examples where spatial data can he used tonimprove business practice, or facilitate new applications include agriculture, navigation,ntraffic monitoring, weather monitoring, construction planning, and townnplanning. In addition, many applications may utilise the same spatial dataset forndifferent purposes. Mobile users may wish to view a very large scale map whennusing a portable device with limited display real-estate. Conversely climatologistsnwill need to view a large region in order to properly plot weather patterns.n Multiresolution databases are suitable for the growing needs of spatial applicationsnas they facilitate access to spatial data over different resolutions, whilenmaintaining only a single stored instance at a fixed resolution. However, these systems have only been explored with respect to map visualisation where the number of supported resolutions is very small. Given the scope of applications,nand varying capabilities of hardware display devices, it is desirable to support asnmany resolutions as possible.n Another concern with multiresolution systems is that they have been designednonly for map visualisation. Hence only issues regarding the spatial window querynhave been investigated. A spatial data repository could potentially be used fornmany other applications such as analytical data mining. Therefore the databasenshould be able to support hath small-scale and large-scale processing simultaneouslynand efficiently.n In this thesis a point-based multiresolution data structure is proposed to handlenboth small-scale and large-scale spatial operations. The structure is firstnapplied to the cartographic processes simplification and tokenisation to evaluatenefficiency when handling small data loads. Next it is applied to the amalgamationnoperation under high data loads to simulate use for data mining applications.n The data structure uses z-values to encode spatial geometries. The advantagenof this approach is twofold. First a large number of resolutions of data can benextracted from a single instance of the data stored at one resolution. Second,ncertain topological anomalies that commonly occur in cartographic processes, asnwell as other operations that manipulate spatial data, can be avoided. These advantagesnovercome two drawbacks of existing multiresolution systems. Moreover, the z-value coding scheme can be used to control the precision of query results,nwhich is very useful considering that lowering the resolution of spatial data alsoncompromises its accuracy. Providing a correlation between resolution and accuracyncan make the expression of spatial queries more practical. Thus users maynspecify the maximum allowable error in results instead of specifying a map scale.n Using z-values allows B-trees to be used instead of the default R-tree structurenfor multidimensional indexing. Reducing dimensionality in most cases facilitatesnspeedier query processing. Spatial queries are developed for the testednoperations under the proposed data structure. Experimental evaluations revealnthat the data structure performs superiorly to current single-resolution spatialndatabase schemes for all operations using real-world datasets. Under simplificationnand tokenisation the structure exhibits efficiency for data loads suitable fornhigh resolution CRT displays. When used for amalgamation the structure performsnefficiently for resolutions where results are produced to within a respectablen50-900 metres accuracy. Finally the structure is shown to also be more resilientnto frequent data updates when compared with a single-resolution alternative.n" @default.
• W33393301 created "2016-06-24" @default.
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• W33393301 date "2005-01-01" @default.
• W33393301 modified "2023-09-27" @default.
• W33393301 title "Query processing in multiresolution spatial databases" @default.
• W33393301 hasPublicationYear "2005" @default.
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