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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ICA-Abs</journal-id>
<journal-title-group>
<journal-title>Abstracts of the ICA</journal-title>
<abbrev-journal-title abbrev-type="publisher">ICA-Abs</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Abstr. Int. Cartogr. Assoc.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2570-2106</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/ica-abs-1-220-2019</article-id>
<title-group>
<article-title>Displacement and visualization of point symbols based on spatial distribution characteristics</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Liu</surname>
<given-names>Haipeng</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>Long</surname>
<given-names>Yi</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>Zheng</surname>
<given-names>Yi</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-group><aff id="aff1">
<label>1</label>
<addr-line>School of Geography Science, Nanjing Normal University, Nanjing, 210023, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing, 210023, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>15</day>
<month>07</month>
<year>2019</year>
</pub-date>
<volume>1</volume>
<elocation-id>220</elocation-id>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2019 Haipeng Liu 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://ica-abs.copernicus.org/articles/1/220/2019/ica-abs-1-220-2019.html">This article is available from https://ica-abs.copernicus.org/articles/1/220/2019/ica-abs-1-220-2019.html</self-uri>
<self-uri xlink:href="https://ica-abs.copernicus.org/articles/1/220/2019/ica-abs-1-220-2019.pdf">The full text article is available as a PDF file from https://ica-abs.copernicus.org/articles/1/220/2019/ica-abs-1-220-2019.pdf</self-uri>
<abstract>
<p>&lt;p&gt;In WEB2.0 environment, the number of map-based mashups which display user-led POI data keeps increasing. When the cartographic processing of these map mashups is lacking, the display of the POI data showed on the maps are quite unsatisfactory because of the overlapping of symbols.&lt;/p&gt;&lt;p&gt;At present, some widely used methods commonly use selection and simplification operations based on a quadtree data structure, which can get a good result in the small and medium scales in which users mainly focus on the distribution characteristics and the density difference of POI, but will lose a lot of information in the large scales in which users mainly focus on the specific location and detailed information of the data. For example, two hotels with the same size will retain only one symbol after using selection or simplification operation although in the large scale if they are adjacent to each other, which will bring trouble to users when using maps. Displacement is a suitable operation to deal with this situation, however, current displacement methods face the problems of symbol position drift and nevertheless the loss of information in high-density areas.&lt;/p&gt;&lt;p&gt;In order to address these problems, this paper proposes a real-time POI visualization algorithm combining the characteristics of traditional quadtree data structure and the advantages of an improved displacement operator.&lt;/p&gt;</p>
</abstract>
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</article-meta>
</front>
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