<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "https://jats.nlm.nih.gov/nlm-dtd/publishing/3.0/journalpublishing3.dtd">
<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/isprsarchives-XL-1-W5-159-2015</article-id>
<title-group>
<article-title>DESIGN A FILTER TO DETECT AND REMOVE VEGETATION FROM ULTRA-CAM-X AERIAL IMAGES’ POINT CLOUD TO PRODUCE AUTOMATICALLY DIGITAL ELEVATION MODEL</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Enayati</surname>
<given-names>H.</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>Veissy</surname>
<given-names>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>Rahimpour</surname>
<given-names>F.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>MSc degree of photogrammetry, K.N. Toosi University of Technology, Tehran, Iran</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>MSc degree of RS&amp;GIS, Faculty of Environment, Islamic Azad University of Science and Research, Tehran, Iran</addr-line>
</aff>
<pub-date pub-type="epub">
<day>10</day>
<month>12</month>
<year>2015</year>
</pub-date>
<volume>XL-1/W5</volume>
<fpage>159</fpage>
<lpage>162</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2015 H. Enayati et al.</copyright-statement>
<copyright-year>2015</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>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XL-1-W5/159/2015/isprs-archives-XL-1-W5-159-2015.html">This article is available from https://isprs-archives.copernicus.org/articles/XL-1-W5/159/2015/isprs-archives-XL-1-W5-159-2015.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XL-1-W5/159/2015/isprs-archives-XL-1-W5-159-2015.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XL-1-W5/159/2015/isprs-archives-XL-1-W5-159-2015.pdf</self-uri>
<abstract>
<p>Digital elevation model is one of the most important spatial information for displaying bare earth. Because of existing objects on the ground, manual editing is unavoidable. Aerial images’ point clouds produced by advanced matching methods are good resources for generating DEM. In this paper, the purpose is design a filter for detect and eliminate vegetation from point clouds. For this purpose, point clouds’ texture is used for finding vegetation. Texture of point clouds is segmented by Otsu method. In the next step,
segmented image is added to raster of elevation and vegetation elevation is detected. Results is showing that point clouds’ texture is a good data for filtering vegetation and generating DEM automatically.</p>
</abstract>
<counts><page-count count="4"/></counts>
</article-meta>
</front>
<body/>
<back>
</back>
</article>