November 22, 2019
Over the past few years, Blue Marble Geographics®’ advanced point cloud processing tool has developed into a professional photogrammetry and drone-mapping software. The latest version of Global Mapper comes with several enhancements, many of which are to the Pixels-to-Points tool for generating point clouds and 3D meshes from drone-captured images.
Here are the top 5 new features of Blue Marble’s Global Mapper:
1. Automatic point cloud classification of pole-like objects
Update: As of version 24.1 this feature has been superseded by a new(er) pole classification tool.
Manually classifying point cloud data can be time-consuming and tedious. This is why the Global Mapper Pro comes with automatic point cloud classification tools for points representing ground, buildings, vegetation, noise, powerlines, and most recently added poles.
The new pole classification tool identifies and classifies points of pole-like objects, such as signs, lamp-posts, utility poles, basketball hoops, and other cylindrical features.
With this tool, users can define the characteristics of the poles they would like to see classified. For example, they can define the minimum height and number of points per pole. They can also define a “pole-like” threshold, allowing for either rigid or relaxed definitions of a pole. For instance, a simple post would typically have a pole-like threshold of 90 – 100%, whereas some straight trees may have a pole-like threshold of 35 – 40%.
2. Photo masking in the photogrammetric tool Pixels to Points for eliminating unwanted backgrounds or data from images
Not all image-data is ideal or necessary in photogrammetrically generated point clouds. This is why an option for photo masking was introduced to the Pixels to Points tool in version 21 of the Global Mapper LiDAR Module. Masking allows users to cut out unwanted areas from images, such as swaths of data that tend to not reconstruct well in a point cloud, like sky or water. It also allows users to crop their data down to focus on specific interest areas, which also shortens the point cloud generation process.
3. Ground coverage polygons for showing the approximate ground coverage of drone-captured photos
Photogrammetrically generated point clouds can require hundreds of drone-captured images. To make it easier to manage and visualize the ground-coverage area of each photo, the latest version of the Global Mapper LiDAR Module’s Pixels to Points tool displays the ground extent of each input photo. Displaying these coverage-area polygons can also help users visualize the overlap of adjacent selected images.
4. Additional support for importing accurate GPS information from external text files
In the latest version of the LiDAR Module, users can update the image-capture location — EXIF information — from a text file. This allows users who have high-accuracy positioning in their orthoimages and point clouds — such as PPK — the ability to overwrite the initial geotag information that comes with their drone-captured images. This is a valuable feature for surveyors who need highly accurate photogrammetric point clouds or meshes.
5. Identification of images that contain selected ground control points based on their location
Another improvement to the Pixels to Points tool is the ability to see images that contain the same ground control points. When a single image is selected, the tool automatically suggests and highlights all image file names that may contain common ground control points. This makes selecting images based on location much easier and faster.
Accessible photogrammetry and point cloud processing software
Most of the improvements to the latest release of the Global Mapper LiDAR Module are to the photogrammetric point cloud generation tool Pixels to Points. This functionality allows GIS professionals easier access to point cloud data as drones and cameras become more affordable.
To try the Pixels to Points tool and the other powerful tools that come with the Global Mapper LiDAR Module, request a free two-week trial after downloading Global Mapper® here.
