Uncertainty models for vector based functional curves and assessing the reliability of G-Band

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2006
Kurtar, Ahmet Kürşat
This study is about uncertainty medelling for vector features in geographic information systems (GIS). It has mainly two objectives which are about the band models used for uncertainty modelling . The first one is the assessment of accuracy of GBand model, which is the latest and the most complex uncertainty handling model for vector features. Some simulations and tests are applied to test the reliability of accuracy of G-Band with comparing Chrisman’s epsilon band model, which is the most frequently used band model among the others. The tests are realized with two cases, testing with digitized lines by people and testing with randomly created lines with gaussian random number generator algorithm. So, the results can be examined in two different ways. The second aim of this thesis is development of band models for functional special curves. These functional curves are based on some mathematical models. Specifications of these curves are defined in the structure of Geographic Markup Language (GML) of Open GIS Consortium (OGC). They are arc, arc string, clothoid and cubic spline. Uncertainty for arc by three coordinates, arc string and cubic spline are modelled by G-Band. Arc by center point and clothoid are modelled by epsilon band. In this thesis, a commercial GIS API, GeoKIT is used to create the band geometries of functional curves, to perform some simulations and tests to make the comparison and to present the developed functionality as a desktop application. Band geomeiv tries are developed in the structure of API model which enable the functionality. Secondly, Matlab 2006a is used for technical computing to calculate multivariate normal cumulative density function (mvncdf) to be used in analyses and simulations.

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Citation Formats
A. K. Kurtar, “Uncertainty models for vector based functional curves and assessing the reliability of G-Band,” M.S. - Master of Science, Middle East Technical University, 2006.