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		<title>Aerial Lidar on INBO Tutorials</title>
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				<title>Exploring the potential of aerial lidar: introduction to lidR</title>
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				<pubDate>Fri, 23 Oct 2026 00:00:00 +0000</pubDate>
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				<description>&lt;h1 id=&#34;1-introduction--acknowledgments&#34;&gt;1. Introduction &amp;amp; Acknowledgments&lt;/h1&gt;&#xA;&lt;p&gt;The workflow integrates: 1. &lt;strong&gt;Custom workflow script&lt;/strong&gt; based on regional&#xA;LiDAR data (e.g., Open Data Vlaanderen) pre-classified with deep&#xA;learning models (3D SegFormer). 2. &lt;strong&gt;Individual Tree Segmentation&#xA;(ITS)&lt;/strong&gt; techniques adapted from the &lt;a href=&#34;https://tgoodbody.github.io/lidRtutorial/06_its.html&#34;&gt;lidRtutorial by Tristan&#xA;Goodbody&lt;/a&gt; (&lt;a href=&#34;https://github.com/tgoodbody/lidRtutorial/blob/master/R/06_its.R&#34;&gt;GitHub&#xA;repository&lt;/a&gt;).&#xA;3. &lt;strong&gt;Advanced tree metrics and point cloud processing&lt;/strong&gt; concepts&#xA;inspired by Liam Irwin’s&#xA;&lt;a href=&#34;https://liamirwin.github.io/CompTreeR/&#34;&gt;CompTreeR&lt;/a&gt;. The code was compiled and documented with the support of Gemini.&lt;/p&gt;&#xA;&lt;hr&gt;&#xA;&lt;h1 id=&#34;2-setup--data-preparation&#34;&gt;2. Setup &amp;amp; Data Preparation&lt;/h1&gt;&#xA;&lt;h2 id=&#34;21-package-installation--environment&#34;&gt;2.1 Package Installation &amp;amp; Environment&lt;/h2&gt;&#xA;&lt;p&gt;First, ensure all required R packages are installed.&lt;/p&gt;</description>
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