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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/isprsarchives-XL-2-W1-87-2013</article-id>
<title-group>
<article-title>COMPARISON OF POINT MATCHING TECHNIQUES FOR ROAD NETWORK MATCHING</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Hackeloeer</surname>
<given-names>A.</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>Klasing</surname>
<given-names>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>Krisp</surname>
<given-names>J. M.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Meng</surname>
<given-names>L.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>BMW Forschung und Technik GmbH, Hanauer Straße 46, 80992 Munich, Germany</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Department of Cartography, Technische Universität München, Arcisstraße 21, 80333 Munich, Germany</addr-line>
</aff>
<pub-date pub-type="epub">
<day>13</day>
<month>05</month>
<year>2013</year>
</pub-date>
<volume>XL-2/W1</volume>
<fpage>87</fpage>
<lpage>92</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2013 A. Hackeloeer et al.</copyright-statement>
<copyright-year>2013</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/3.0/">https://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions>
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<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XL-2-W1/87/2013/isprs-archives-XL-2-W1-87-2013.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XL-2-W1/87/2013/isprs-archives-XL-2-W1-87-2013.pdf</self-uri>
<abstract>
<p>Map conflation investigates the unique identification of geographical entities across different maps depicting the same geographic
region. It involves a matching process which aims to find commonalities between geographic features. A specific subdomain of
conflation called Road Network Matching establishes correspondences between road networks of different maps on multiple layers
of abstraction, ranging from elementary point locations to high-level structures such as road segments or even subgraphs derived
from the induced graph of a road network.
&lt;br&gt;&lt;br&gt;
The process of identifying points located on different maps by means of geometrical, topological and semantical information is
called point matching. This paper provides an overview of various techniques for point matching, which is a fundamental
requirement for subsequent matching steps focusing on complex high-level entities in geospatial networks. Common point matching
approaches as well as certain combinations of these are described, classified and evaluated. Furthermore, a novel similarity metric
called the Exact Angular Index is introduced, which considers both topological and geometrical aspects. The results offer a basis for
further research on a bottom-up matching process for complex map features, which must rely upon findings derived from suitable
point matching algorithms. In the context of Road Network Matching, reliable point matches provide an immediate starting point for
finding matches between line segments describing the geometry and topology of road networks, which may in turn be used for
performing a structural high-level matching on the network level.</p>
</abstract>
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