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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="3.0" xml:lang="en">
<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-XLVI-2-W1-2022-459-2022</article-id>
<title-group>
<article-title>A HYBRID POINT CLOUD REALITY CAPTURE FROM TERRESTRIAL LASER SCANNING AND UAV-PHOTOGRAMMETRY</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Razali</surname>
<given-names>A. F.</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>Ariff</surname>
<given-names>M. F. 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>Majid</surname>
<given-names>Z.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Geospatial Information and Imaging Research Group (GI2RG), Faculty of Built Environment &amp; Surveying, Universiti Teknologi Malaysia, Johor Bahru, Malaysia</addr-line>
</aff>
<pub-date pub-type="epub">
<day>25</day>
<month>02</month>
<year>2022</year>
</pub-date>
<volume>XLVI-2/W1-2022</volume>
<fpage>459</fpage>
<lpage>463</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2022 A. F. Razali et al.</copyright-statement>
<copyright-year>2022</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/XLVI-2-W1-2022/459/2022/isprs-archives-XLVI-2-W1-2022-459-2022.html">This article is available from https://isprs-archives.copernicus.org/articles/XLVI-2-W1-2022/459/2022/isprs-archives-XLVI-2-W1-2022-459-2022.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLVI-2-W1-2022/459/2022/isprs-archives-XLVI-2-W1-2022-459-2022.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLVI-2-W1-2022/459/2022/isprs-archives-XLVI-2-W1-2022-459-2022.pdf</self-uri>
<abstract>
<p>Point clouds are a digital representation of physical objects or buildings that exist in real world. There are many sources that a point cloud can come from such as a terrestrial laser scanner (TLS) or an unmanned aerial vehicle (UAV). This paper presents a simple method of integrating point clouds from two (2) data sources; TLS and UAV using simple alignment of rigid body transformation method known as Point Pair Picking (PPP). The point cloud data are the representation of details of a one-story building located in Johor Bahru, Malaysia. The process of aligning two (2) separate clouds into one (1) dataset requires initial processing such as noise removal before the alignment process was started. A laser (LAS) formatted data were formed so that it compatible with the PPP process. As the result, a high dense hybrid cloud-model was produced covering complete details of the building. This shows that integration of point clouds could improve 3D documentation assessment such as Building Information Modelling (BIM) by contributing richer semantic information.</p>
</abstract>
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</article-meta>
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