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<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-3-W10-831-2020</article-id>
<title-group>
<article-title>EXTRACTION OF HOUSES FROM POINT CLOUD LIDAR: PROBLEMS AND CHALLENGE</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Zhou</surname>
<given-names>G. Q.</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>Di</surname>
<given-names>W. Q.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, 12 Jian’gan Road, Guilin, Guangxi 541004, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>College of Earth Sciences, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>08</day>
<month>02</month>
<year>2020</year>
</pub-date>
<volume>XLII-3/W10</volume>
<fpage>831</fpage>
<lpage>837</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2020 G. Q. Zhou</copyright-statement>
<copyright-year>2020</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-3-W10/831/2020/isprs-archives-XLII-3-W10-831-2020.html">This article is available from https://isprs-archives.copernicus.org/articles/XLII-3-W10/831/2020/isprs-archives-XLII-3-W10-831-2020.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLII-3-W10/831/2020/isprs-archives-XLII-3-W10-831-2020.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLII-3-W10/831/2020/isprs-archives-XLII-3-W10-831-2020.pdf</self-uri>
<abstract>
<p>Although many efforts have been made on the extraction of houses from LiDAR (Light Detection and Ranging) and/or aerial imagery and/or their fusion, little investigation using co-registration between the orthoimage map and LiDAR on the basis of geodetic coordinates as element for house extraction. For this reason, this paper first overviews the advances of LiDAR and investigates the advantages and disadvantages of LiDAR system vs. traditional photogrammetry, and then indicates that LiDAR technology has not yet resolved all existing problems that traditional photogrammetry remained so far, such as texture information, LiDAR point cloud density. A comprehensive comparison in extraction of houses (feature information) from LiDAR data set and from aerial imagery are also presented. It has been widely accepted and admitted that full automation for extraction of houses (feature information in city area) from LiDAR point cloud has still been difficult. Therefore, this paper proposes a human-computer interaction operation for houses extraction through combination of LiDAR point cloud and the orthorectified high-resolution aerial imagery. The real data is utilized for validation of the proposed method.</p>
</abstract>
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