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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Archives</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9034</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/isprs-archives-XLII-4-W16-161-2019</article-id>
<title-group>
<article-title>ADJUSTMENT OF CADASTRAL NETWORK USING LEAST-SQUARES VARIANCE COMPONENT ESTIMATION</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Bidi</surname>
<given-names>N. K.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Din</surname>
<given-names>A. H. M.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Som</surname>
<given-names>Z. A. M.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Omar</surname>
<given-names>A. H.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Geomatic Innovation Research Group (GIG), Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, Johor, Malaysia</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Geoscience and Digital Earth Centre (INSTEG), Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, Johor, Malaysia</addr-line>
</aff>
<pub-date pub-type="epub">
<day>01</day>
<month>10</month>
<year>2019</year>
</pub-date>
<volume>XLII-4/W16</volume>
<fpage>161</fpage>
<lpage>167</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2019 N. K. Bidi et al.</copyright-statement>
<copyright-year>2019</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLII-4-W16/161/2019/isprs-archives-XLII-4-W16-161-2019.html">This article is available from https://isprs-archives.copernicus.org/articles/XLII-4-W16/161/2019/isprs-archives-XLII-4-W16-161-2019.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLII-4-W16/161/2019/isprs-archives-XLII-4-W16-161-2019.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLII-4-W16/161/2019/isprs-archives-XLII-4-W16-161-2019.pdf</self-uri>
<abstract>
<p>The role of the stochastic model very important in data processing of geodetic network since it describes the accuracy of the measurements and their correlation with each other. Knowledge of weights of the observables is required to provide a better understanding of the sources of errors and to model the error, hence the weights need to be determined correctly. This study concentrates on the estimation of variance components from different types of instruments used in the cadastral survey. The ideas are to combine the conventional and advanced instruments in a traverse network to enhance the estimated variance component in the stochastic model. Thus, Least Squares Variance Component Estimation (LS-VCE) method was used in this study because the method is simple, flexible and attractive due to the precision of variance estimators that can be directly obtained. Observation data come with several types of instruments such as chain measurement, Electronic Distance Measurement and total station were utilized. The findings showed that LS-VCE method was very reliable in cadastral network application. Besides, the results revealed that the estimated variance components for distance scale error, &amp;sigma;&lt;sub&gt;p&lt;/sub&gt; seem to become unrealistic for each data tested. It was found that the traverse network which included chain survey, showed the insignificant result to the precision of station coordinates when the measurements were combined.</p>
</abstract>
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