Top 5 Tools and Functions of the Global Mapper LiDAR Module

In anticipation of the increasing availability and use of LiDAR and other point cloud datasets, the LiDAR Module, an add-on to Global Mapper, was first introduced in version 15 of the software. Over the last five years, this popular component has rapidly evolved and offers an array of powerful tools.

In this blog entry, we highlight the top five most important tools and functions in the LiDAR Module, including extracting vector features, processing UAV-collected images into point clouds, filtering LiDAR data, and generating 3D meshes or models.

Pixels-to-Points Tool in Global Mapper
3D Point cloud of a barn viewed created with the Pixels to Points tool

1. Pixels to Points

The newest addition to the LiDAR Module, Pixels to Points is a tool for creating a high-density point cloud, orthoimage, and 3D meshe from overlapping images, especially those captured using a drone

Based on the principles of photogrammetry, the Pixels to Points process identifies objects in multiple images and from multiple perspectives to generate a 3D point cloud. As a by-product of the point-generation process, the tool can also create an orthoimage by gridding the RGB values in each point, as well a 3D mesh, complete with photorealistic textures.

Pixels to Points offers photogrammetric point cloud creation that is both affordable and straightforward, and is increasingly used as an alternative to traditional LiDAR collection.

Auto Classification of LiDAr points
Buildings and trees identified and reclassified in a LiDAR layer

2) Auto Point Reclassification

The LiDAR Module’s automatic reclassification tools can accurately identify points representing ground, vegetation, buildings, and utility cables.

Algorithms in the LiDAR Module analyze the geometric properties and characteristics of point clouds to quickly classify these features. This process is commonly used to identify, classify, and filter ground points when creating a Digital Terrain Model (DTM), or as a first step in the process of isolating specific feature types when extracting vector features, such as buildings or trees, from a point cloud.

Feature Extraction using the Global Mapper LiDAR Module
Vector lines representing above-ground power cables extracted from LiDAR data

3) Feature Extraction

The Feature Extraction tool is used to create vector objects from appropriately classified points.

Based on a series of customizable settings, points representing buildings, trees, and utility cables are analyzed and automatically delineated as a series of 3D vector objects or, in the case of buildings, as a 3D mesh.

Feature extraction is particularly useful for creating building footprints, defining roof structures, powerlines, and other 3D features from classified LiDAR data.

Digitizing the edge of a curb using the Global Mapper LiDAR Module
Digitizing the edge of a curb using the perpendicular profile function

4) Custom Feature Extraction

Custom Feature Extraction is a function for delineating atypical 3D features from point cloud data.

This function allows for the creation of accurate 3D line or area features by defining control vertices in a sequential series of perpendicular path profile views. Examples of using Custom Feature Extraction might be for defining road curbs, pipelines, or drainage ditches,

3D Mesh created using the Global Mapper LiDAR Module
3D Mesh of a suburban neighborhood created from selected points in a point cloud

5) Mesh Creation from LiDAR Points

Mesh Creation is a function that uses a selected group of points to create a 3D vector object complete with photorealistic colors or textures.

The LiDAR Module offers the ability to create a mesh or model using the 3D geometry and colors of a selected group of points. When viewed in 3D, this model displays as a multifaceted photo-realistic 3D representation of the corresponding feature.

For information about all of the features that the LiDAR Module has to offer, visit our website here.

4 Replies to “Top 5 Tools and Functions of the Global Mapper LiDAR Module”

  1. I really appreciate what you are doing to upgrade the field of spatial data operation. please, keep it up to serve all over the world, specially, the ACP cpountries.

  2. I’ve been evaluating the LIDAR module to see if it is something I want to purchase as an alternative to Agisoft Metashape. I was interested because of the videos posted on the automatic classification of point clouds but it doesn’t do very well in macadamia nut orchards, and I would assume any semi-dense forested areas. It just classifies everything as buildings, even though there are no buildings in the area. Seems like it really needs large swaths of bare ground to do a good job, which I guess was expected since most photogrammetry software products I’ve looked at are rubbish for forestry/orchard/non-row crop ag work. It also doesn’t handle a lot of images. I have almost 6000 acres of orchards to map and I can’t create an orthomosaic for a 20 acre demonstration plot. Maybe its good for construction sites?

    1. Thanks Scott!
      If all of the points are showing as building, then the Bin Size and/or the Maximum Co-Planar and Minimum Vegetation Distance setting need to be increased. With photo-generated point-clouds, the bin size often needs to be increased to 1 or 2 meters instead of the auto-calculated value, which is generally better for traditional lidar point clouds.
      If you want to send a sample of your data to we would be happy to take a look and recommend some good settings for the automatic classification algorithms.

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