The Global Mapper Lidar Module is an optional add-on to Global Mapper that provides numerous advanced lidar processing tools and is a must-have for anyone using or managing terrestrial or airborne lidar as well as other point cloud datasets.

The Module is embedded in the standard version of the software and is activated using an appropriate license file or order number. As with the full version of Global Mapper, the Lidar Module can be activated on a trial basis by requesting a temporary license. Click here for instructions on how to activate the module.

Low-Cost Lidar Processing

The enhanced lidar analysis and editing functionality in the Global Mapper Lidar Module is offered at a significantly lower price than similar applications. The cost of activating this module is on par with the cost of purchasing a copy of Global Mapper with flexible licensing options available for network, enterprise, and academic use. For more information, contact

Lidar Module Features

The Lidar Module® is embedded in the current release of Global Mapper® and is activated on the Module/License Extension Manager. Learn more about Lidar Module Features below. A free trial is available for evaluation.

Pixels to Points® Angle right

Using an array of overlapping images, such as those collected using a drone, the Pixels to Points tool generates a high-density point cloud based on user-selectable parameters. Employing the principles of photogrammetry in which measurements are derived from photographs, the Pixels to Points tool analyzes the relationship between recognizable objects in adjacent images to determine the three-dimensional coordinates of the corresponding surface. As a by-product of the point cloud generation capability, the Pixels to Points tool also offers the option of creating an orthorectified image by gridding the RGB values in each point, as well as a 3D Mesh, complete with photorealistic textures.

The processing of creating the point cloud begins with a simple loading of the images into the Pixels to Points dialog box. For optimal results, at least 60% overlap and evenly distributed photos taken from varying angles are recommended. Individual images can be previewed and those not needed for the final point cloud can be removed. Various settings can then be applied to determine the output quality, analysis method, etc. Finally, ground control points may optionally be added to adjust the horizontal and vertical positioning of the point cloud. After processing is complete, the point cloud will be automatically added to the current workspace. It can be further processed or edited before exporting to any of the supported point cloud formats including LAS and LAZ.

The Pixels to Points process is memory intensive and may take several hours to process depending on the input data and quality setting. It is recommended that this process is performed on a dedicated computer with at least 16GB of RAM. The Pixels to Points tool also requires a 64-bit operating system.

Mesh or 3D Model Creation Angle right

Using a selected group of lidar points, this process uses the inherent 3D geometry of the points along with the associated colors if present and creates a 3D mesh or model. When viewed in 3D, this model displays as a multifaceted photo-realistic 3D representation of the corresponding feature. This process produces a similar output to the model creation option in the Pixels to Points tool.

Automatic Point Classification Algorithms

Manual Classification Angle right

The Lidar Module includes a convenient toolbar to streamline the classification of selected points with a single button click. This toolbar includes buttons for the most common classification types including ground, vegetation, and buildings. Additionally, selected points can be manually edited and assigned to any of the ASPRS lidar classification types using the Digitizer’s edit function.

Automatic Classification Angle right

Based on the geometric properties and other characteristics of the lidar file or point cloud, the Lidar Module’s automatic reclassification tool is able to accurately identify and automatically reclassify points representing the important point feature types. First and foremost is the identification of ground points, which is used for the creation of a DTM or bare-earth model. Within the remaining above-ground points, specific algorithms can be applied to identify and reclassify high vegetation, buildings, and powerlines.

Global Mapper Lidar Module | Test Data Before Automatic Classification

Global Mapper Lidar Module | Test Data After Automatic Classification

Global Mapper Lidar Module | Classification of Power Lines

Lidar QC Angle right

The Lidar Module offers a tool for verifying the vertical accuracy of a point cloud. Using surveyed ground control points, the elevation values throughout the layer can be checked and adjusted if necessary.

Advanced Lidar Filtering Angle right

Points can be filtered using a variety of criteria and at various stages during the point cloud processing workflow. During import, points can be filtered based on classification, return count, sample count, or based on their geographic distribution. The same filtering options can be used to filter the display of points in the map view. When creating a gridded surface or a DEM, a further level of filtering is available which can be used to remove points based on elevation range, classification, intensity, color, or on many other point cloud characteristics.

Noise Removal Angle right

Addressing a major concern among lidar users, Global Mapper Lidar Module provides an efficient and effective way to remove noise from point cloud data. This powerful filtering tool can reclassify or automatically delete any points that are beyond a prescribed elevation or height above the ground threshold within a local area.

Lidar Querying Angle right

The Lidar Module includes numerous tools for querying points based on both the point cloud attributes and on their geographic distribution. The Search function can be used to create a multi-level query of point classification, elevation range, intensity, or any of the other variables. Spatial querying options include identifying points contained within a selected polygon or points that are within a defined distance of a certain type of point type or line feature. This function is ideally suited for encroachment detection.

Lidar Thinning Angle right

Using a set of customizable parameters, this tool reduces the number of points in a point cloud resulting in a more manageable file size while eliminating redundancy. This thinning process can be applied consistently across the 2D extent of the layer or it can vary to reflect the 3D distribution of points.

Automatic Extraction of Buildings, Trees, Power Poles and Powerlines Angle right

One of the Lidar Module’s most powerful capabilities, the feature extraction tool is used to create a vector (point, line, or polygon) features derived from appropriately classified points. Based on a series of customizable settings, patterns of points representing buildings, trees, poles, and utility cables are analyzed and their extent is automatically delineated as a series of 3D vector objects or, in the case of buildings, as a 3D mesh.

Custom 3D Digitizing and Feature Extraction Angle right

Using the Perpendicular Path Profile function, a series of custom spaced cross-sectional views are created perpendicular to a defined path through a point cloud. 3D vertices can be quickly and accurately placed at regular intervals within each successive profile view. When the sequence is complete, either a 3D linear or area feature is created using Global Mapper’s standard Digitizing tool. This is an ideal tool for delineating curbs, utility cables, pipelines, drainage ditches, or building rooflines from high-resolution point cloud data.

Point Cloud Visualization Angle right

The display of points can be adjusted to reflect many of the attributes within the point cloud, including:

  • Elevation
  • Intensity
  • Classification
  • Return Number
  • Height Above Ground
  • Point Source ID
  • NDVI/NDWI (when NIR attribute is present)
  • Point Density

When overlaid on a raster or gridded layer, the RGB or NIR value from each underlying pixel can be added to the associated point.

Advanced DEM Creation Angle right

The Lidar Module provides numerous options for creating a surface model. Supplementing the simple triangulation (TIN) process, binning offers a more efficient and customizable way to create DTM or DSM of a specific resolution. Hydro-flattening allows the inherent elevation values associated with 3D vector lines or polygons to override the point-based elevations when modeling water bodies or streams.

Path Profile Rendering and Editing Angle right

The module enables the display of a section of a point cloud in the Path Profile view. This lateral perspective is initially created by establishing a swath width to ensure that sufficient points are displayed for the area of interest. The lateral perspective is ideally suited for manual point selection and editing as it clearly distinguishes points that are vertically offset from those in the surrounding area.

Global Mapper Lidar Module | Path Profile

Additional File Format Support Angle right
  • E57 lidar format support
  • Leica PTS point cloud file support

Do I Need the Lidar Module?

Coinciding with the rapidly expanding availability of Lidar data, the Lidar Module supplements the standard version of Global Mapper with an array of powerful point cloud processing tools and superior terrain creation capability. This affordable add-on component exponentially increases the value of the software by providing the means to fully utilize significantly more points in any point cloud dataset.

Software Comparison

Feature Global Mapper Lidar Module
Pixels-to-Points® tool for creating 3D point clouds from overlapping images Tick
Read/Write support for LAS/LAZ files Tick Tick
Support for Leica PTS format Tick
Support for working with over one billion points [64-bit only] Tick Tick
Option to render point cloud by elevation shader Tick Tick
Option to render point cloud by RGB values embedded in point cloud Tick Tick
Option to render point cloud by intensity Tick Tick
Option to render point cloud by classification Tick Tick
Option to render point cloud by return number Tick Tick
Option to render point cloud by point index Tick Tick
Option to render point cloud by point source ID Tick Tick
Option to render point cloud by the difference in height between the first and last return Tick Tick
Option to render point cloud by calculated NDVI or NDWI value (requires NIR attribute) Tick Tick
Option to render point cloud by height above ground Tick
Option to render point cloud by point density Tick
Ability to interactively change rendering method from Toolbar Tick
One-button point cloud colorization from raster imagery Tick
Ability to calculate statistics for point cloud data using a script Tick
Ability to reproject Lidar point clouds Tick Tick
Ability to transform point cloud coordinates (including rectification) Tick
Ability to crop point clouds Tick Tick
Ability to manually edit or delete points Tick Tick
Ability to select points based on proximity (encroachment detection) Tick
Easy filtering for separating point classes Tick
Ability to filter selected Lidar points by elevation/color range Tick
Ability to manually adjust elevations in entire point cloud Tick
Lidar QC to vertically correct Lidar elevations from ground control points Tick
Ability to display and edit Lidar points in Path Profile (cross-sectional view) Tick
One-button point reclassification tools Tick
Automatic ground point classification Tick
Automatic identification of noise points Tick
Automatic reclassification of building, tree, and power line points Tick
Ability to create custom keyboard shortcuts for reclassification Tick
Building, tree, and powerline extraction from classified Lidar points Tick
Custom 3D digitizing and feature extraction using perpendicular path profile views Tick
Elevation grid creation using Triangulated Irregular Network (TIN) method Tick Tick
Elevation grid creation using local minimum elevation (DTM) Tick
Elevation grid creation using local maximum elevation (DSM) Tick
Elevation grid creation using local average elevation Tick
Option to filter points applied in gridding process Tick
Ability to create grid from heights above ground rather than elevation Tick
Ability to create grid based on intensity rather than elevation Tick
Ability to create grid from color values to create an image layer Tick
Option to export Lidar points within elevation range Tick
Option to export LAS files using height above ground instead of elevation Tick

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