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&rsquo / 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.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12608054/index.pdf |
| Date | 01 December 2006 |
| Creators | Kurtar, Ahmet Kursat |
| Contributors | Duzgun, Sebnem |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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