Top 5 Features of Global Mapper’s Lidar Module Version 22

Written by: Cíntia Miranda and David McKittrick

The Lidar Module®, an optional add-on to Global Mapper®, provides advanced point cloud processing tools, including Pixels to Points®, for photogrammetric point cloud creation using overlapping drone-captured images, automatic and manual point cloud classification, as well as feature extraction, hydro-flattening, and more.

The latest version of the Lidar Module includes several new tools, as well as improvements to many of the existing features and functions. This blog highlights the top five new features of version 22:

 

  • A new Terrain Paint tool 

 

Terrain Painting is a set of terrain editing tools that provide the ability to modify the elevation values of a gridded elevation dataset interactively. Using simple drawing tools, this innovative addition to the Lidar Module can be used to fill gaps in the terrain, raise or lower the existing elevation inside a defined area, or set a specific elevation height. Dynamically editing a terrain layer in this way is useful for site planning, modeling, and cleaning up or improving sensor derived elevation data. This tool works with all types of gridded elevation datasets, including DSMs and DTMs, bathymetric datasets, lidar derived terrain data, and more.

The ‘Fill Gaps’ operation is used to fill in missing areas of terrain.

The ‘Smooth Terrain – Average’ operation is used to create a cleaner terrain surface.

In this example, the ‘Set Terrain Height’ tool is used to create the simulated path of a road. The feathering effect creates a sloped transition into the surrounding terrain.

 

  • A new algorithm that improves building classification 

 

The Lidar Module includes a variety of automatic feature identification and point reclassification tools. The underlying algorithms analyze the point cloud’s geometric structure in a local context to look for patterns that match a prescribed format. The specific options include reclassification of points representing high vegetation or trees, powerlines, power poles, and buildings. For the version 22 release, the algorithm for identifying buildings in a point cloud has been updated to provide a more accurate reflection of human-made structures when working with point cloud data from any source.

The orange points have been automatically classified as building points.

 

  • Improved building extraction with better 3D shape simplification 

After a point cloud has been appropriately classified, individual vector features can be created, reflecting the object’s three-dimensional characteristics. For example, 3D line features can be automatically generated by connecting the dots for those points that were identified as powerline points. Perhaps one of the more useful applications for this feature extraction tool is for creating 3D polygons representing buildings. In version 22, several new settings and options have been added, and the vectorization algorithm has been significantly improved to provide more accurate building outlines. Individual surface planes are now created, allowing the building’s specific structure to be more precisely represented, and the simplification process has been updated, resulting in cleaner roof planes and sidewalls.

Complex building features extracted from a point cloud as 3D polygons.

 

  • A new option to generate a process summary report when using the Pixels to Points process 

 

The Pixels to Points tool is arguably one of the most powerful components of the Lidar Module. Using simple drone-collected images, this tool photogrammetrically analyzes and identifies recurring patterns of pixels in multiple images to create a 3D reconstruction of the environment. Version 22 of the Lidar Module includes several improvements to this function, most notably a new ‘Post Processing Report’ that concisely summarizes the pertinent information from the data generation process. This report includes a summary of input data, processing time, output data, quality assessment, as well as a visual representation of the individual output layers. The report is in HTML format and will automatically open in your default web browser from where it can be saved as a PDF file.

A section of the report generated after the Pixels to Points process has been completed.

 

  • Two new lidar draw modes

 

3D lidar or other point cloud data can be rendered to reflect various point attributes, such as elevation, return intensity, and point classification. This latest release introduces two new lidar draw modes:

Color by Source Layer — With this option, a unique color is applied to each loaded point cloud layer as a simple way to distinguish separate point cloud layers in the workspace clearly. A specific color can be selected for a layer in the Lidar Display for that layer.

Color by Scan Angle – In this mode, lidar points are colorized using the scan angle attribute, with values potentially ranging from -90 to 90 degrees. The actual color of the points is determined by the Shader Option chosen in the workspace.

If you’re not familiar with Global Mapper and the Lidar Module, request a two-week free trial today. If you would like to speak with a representative about how the software can address your unique geospatial challenges, request a demo!

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