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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-XLVIII-1-W2-2023-1-2023</article-id>
<title-group>
<article-title>GENERATION OF 3-D LARGE-SCALE MAPS USING LIDAR POINT CLOUD DATA</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Dhruwa</surname>
<given-names>L.</given-names>
<ext-link>https://orcid.org/0009-0009-4923-6018</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Garg</surname>
<given-names>P. K.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Department of Civil Engineering, IIT Roorkee, Uttarakhand, India</addr-line>
</aff>
<pub-date pub-type="epub">
<day>13</day>
<month>12</month>
<year>2023</year>
</pub-date>
<volume>XLVIII-1/W2-2023</volume>
<fpage>1</fpage>
<lpage>5</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2023 L. Dhruwa</copyright-statement>
<copyright-year>2023</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/XLVIII-1-W2-2023/1/2023/isprs-archives-XLVIII-1-W2-2023-1-2023.html">This article is available from https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/1/2023/isprs-archives-XLVIII-1-W2-2023-1-2023.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/1/2023/isprs-archives-XLVIII-1-W2-2023-1-2023.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/1/2023/isprs-archives-XLVIII-1-W2-2023-1-2023.pdf</self-uri>
<abstract>
<p>3-Dimensional geospatial data is essential for creating and utilizing real-world visualizations for analyzing infrastructure design improvements. However, techniques exist such as Total Station, Global Positioning System (GPS), and Google Earth data. Traditionally 3D maps were constructed using simple measurements of angles and distances, providing a planimetric representation of the area with a limited number of cross-sections to reflect the built-up area.&lt;/p&gt;
&lt;p&gt;However, Terrestrial laser scanning (TLS) is an efficient technique for capturing dense point clouds to construct detailed information models for large-scale built-up areas. In recent years, advancements in the measurement of speed, reduction of size and cost, and portability of these technologies have revolutionized 3-D data collection. This article discusses the methodological framework and 3-D mapping accuracy by adopting terrestrial laser scanning to map a built-up area having different features. Point cloud data collected in the form of scans were processed and registered using Faro Scene software with an overall registration error of 14 mm (RMSE). Finally, it creates a 3-D map of the built-up area having planimetric and elevation accuracy analyses. It will be used for spatial analyses or simulating the interaction of surface and subsurface processes contributing to urban and rural planning development in a 3-D GIS environment and for smart cities.&lt;/p&gt;
&lt;p&gt;The method presented here provides a different way for achieving large-scale maps with greater accuracy, which will be applicable in identifying and monitoring the deformations in the built-up areas and in various disaster mitigation.</p>
</abstract>
<counts><page-count count="5"/></counts>
</article-meta>
</front>
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