KNOWLEDGE BASE
Multi-User Work together easily with shared projects
With the Multi-User functionalities in Pointly, you can work together with multiple users and simultaneously on projects and contained point clouds. By working in parallel within a Multi-User project, you can manage the classification process and introduce quality assurance workflows.
Tags for point clouds – Categorize your point clouds
Custom tags for point clouds are free text fields, to tag the point cloud and/or comment on the point clouds to categorize them. For example you could tag all point clous that have the same characteristic with the same tag, like “LiDAR”.
Locking Classes – Lock and Unlock Classes while Classifying
The Locking classes feature can make the classification process more efficient. If point clouds were uploaded pre-classified these existing classification can be locked to not overwrite them. In this tutorial we show how to apply the Looking Class Feature to individual and all classes.
How to get started with Pointly plus 5 useful hacks
Want to use our intelligent, cloud-based software, but don’t know how to get started? Then you’re in the right place. In this article, we will provide you with information on different account types and sum up the most important tools and features of Pointly.
How to convert your point cloud data into .Las / .Laz
First of all – Don’t worry it’s pretty easy! Pointly will work with the data format LAS or LAZ. The preferred upload format is LAZ because of its compression, followed by LAS.
Manual classification on point clouds – This is why you should do it
Currently there is a lot of inefficient work with point clouds in order to extract information. Pointly offers a way to change that into efficient work.