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.
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.
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.
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.
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,
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.