Just in time for INTERGEO 2015, the Potree software was released in its latest 1.3 version. Potree is a WebGL based point cloud viewer for very large datasets.
The Potree software allows to publish large LiDAR point clouds on the Web such that anyone can explore the data with nothing more but a modern browser. The interactive 3D viewer not only visualizes the LiDAR in many useful and intuitive ways but also comes with tools to perform various measurements. As its only Gold Sponsor, rapidlasso GmbH is the main supporter of this powerful open source package by Markus Schütz.
In the near future the Potree software will be distributed together with the LAStools package to offer a one-click solution for generating Webportals that host and distribute large LiDAR data sets and offer interactive online visualization and exploration. Potree is open source software that is free for anyone to acquire and to deploy. Please remember that using open source software is not the same as supporting open source software. Given the positive experience that rapidlasso GmbH has had with Potree we can only encourage other geospatial companies to support with time or money those open source projects that help your business.
About rapidlasso GmbH:
Technology powerhouse rapidlasso GmbH specializes in efficient LiDAR processing tools that are widely known for their high productivity. They combine robust algorithms with efficient I/O and clever memory management to achieve high throughput for data sets containing billions of points. The company’s flagship product – the LAStools software suite – has deep market penetration and is heavily used in industry, government agencies, research labs, and educational institutions. Visit http://rapidlasso.com for more information.
Potree is a WebGL based viewer for large point clouds. The project evolved as a Web based viewer from the Scanopy desktop point cloud renderer by TU Wien, Institute of Computer Graphics and Algorithms. It will continue to be free and open source with a FreeBSD license to enable anyone to view, analyze and publicly share their large datasets. Visit http://potree.org for more information.