Pixels-to-Points™: Easy Point Cloud Generation from Drone Images

Point cloud generated from 192 drone images using the Pixels-to-Points tool
A point cloud generated by EngeSat’s Laurent Martin using the new Pixels-to-Points™ tool in version 19 of the LiDAR Module. The LiDAR Module tool analyzed 192 high resolution drone images to create this high-density point cloud.

When we have a new product release like the version 19 of the LiDAR Module that comes with the Pixels-to-Points™ tool, it’s always exciting to see that feature in action for the first time outside of the Blue Marble office. Our South and Central American reseller Laurent Martin from EngeSat was quick to try the new Pixels-to-Points tool for himself using drone data collected by his peer Fabricio Pondian.

The new Pixels-to-Points tool uses the principles of photogrammetry, generating high-density point clouds from overlapping images. It’s a functionality that makes the LiDAR Module a must-have addition to the already powerful Global Mapper, especially for UAV experts.

Below, screenshots captured by Laurent illustrate the simple step-by-step process of creating a point cloud using the Pixels-to-Points tool and some basic point cloud editing using other LiDAR Module tools.

1. Loading drone images into the LiDAR Module

The collection of images loaded into the LiDAR Module must contain information that can be overlapped. The Pixels-to-Points tool analyzes the relationship between recognizable objects in adjacent images to determine the three-dimensional coordinates of the corresponding surface. In this particular example of the Pixels-to-Points process, 192 images are used.
The flight path of the UAV and the locations of each photo can be viewed over a raster image of the project site.

2. Calculating the point cloud from loaded images

192 high-resolution images are selected in this particular example. The tool will give an estimated time of completion, which depends on the size of the images and number of images.
The Calculating Cloud/Mesh dialogue displays statistics of the images as they are analyzed and stitched together by the Pixels-to-Points tool.
An alert window pops up when the process is complete.

3. Viewing the generated point cloud

A new layer of the generated point cloud is now in the control center.
A close up of the final processing result with the orthoimage.
A close up of the final result with the new point cloud generated from the 192 images.
A 3D view of the resulting point cloud.
A view of the point cloud colorized by elevation
A cross-sectional view of the point cloud using the Path Profile tool

4. Classifying the point cloud

Points can be reclassified automatically or manually using LiDAR Module tools. Here, the point cloud is reclassified as mostly ground points.

5. Creating an elevation grid and contours from the point cloud

With the point cloud layer selected, a digital terrain model can be generated by clicking the Create Elevation Grid button.
A cross-sectional view of the digital terrain model using the Path Profile tool
Contours can be generated from the digital terrain model by simply clicking the Create Contours button.

A quick and easy process

In just a few steps, Laurent was able to create a high-density point cloud from 192 images, reclassify the points, and create a Digital Terrain Model. It’s a prime example of how easy version 19 of the LiDAR Module and the new Pixels-to-Points tool are to use. Check out EngeSat’s full article on the release of LiDAR Module.