<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Potree on ION Solutions</title><link>https://ion-solutions.at/en/tags/potree/</link><description>Recent content in Potree on ION Solutions</description><generator>Hugo</generator><language>en</language><lastBuildDate>Tue, 20 Jan 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://ion-solutions.at/en/tags/potree/index.xml" rel="self" type="application/rss+xml"/><item><title>3D Point Clouds with Potree: Billions of Points in the Browser</title><link>https://ion-solutions.at/en/blog/3d-point-clouds-potree/</link><pubDate>Tue, 20 Jan 2026 00:00:00 +0000</pubDate><guid>https://ion-solutions.at/en/blog/3d-point-clouds-potree/</guid><description>&lt;h2 id="what-are-point-clouds"&gt;What Are Point Clouds?&lt;/h2&gt;
&lt;p&gt;A point cloud is a collection of millions or billions of individual 3D points that together describe the surface of an object or environment. Each point has at least three coordinates (X, Y, Z) and can carry additional attributes: color (RGB), intensity, classification, or timestamps.&lt;/p&gt;
&lt;p&gt;Point clouds are generated through various capture methods:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;&lt;strong&gt;LiDAR&lt;/strong&gt; (Light Detection and Ranging): Laser scanners measure distances and produce high-precision 3D data. Terrestrial scanners capture buildings, while airborne LiDAR maps entire landscapes.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Photogrammetry&lt;/strong&gt;: Structure-from-Motion algorithms compute 3D points from overlapping photographs. More affordable than LiDAR but less precise.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Structured light&lt;/strong&gt;: Projected patterns are captured by cameras and converted into 3D data. Common for interior scans.&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;The problem: these datasets grow enormous quickly. A single scan of a building can contain 500 million points. A city survey easily reaches several billion. How do you bring that much data into a web browser?&lt;/p&gt;</description></item></channel></rss>