Using an array of overlapping images, such as those collected using a drone, this 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.
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.
Quickly reclassify points with seven different classification types.
Automatically reclassify buildings, trees, ground points and above-ground utility cables with conveniently located button in the LiDAR tool bar. The Global Mapper LiDAR Module features improved classification to filter out likely buildings, trees and power lines along with additional parameters controls in the Ground Classify dialog. Machines with multiple cores will experience faster automatic classification of ground points. The user can also perform automatic classification on just selected points to speed up processing.
The LiDAR module offers an array of tools for improving the quality of a point cloud. Points can be manually or automatic reclassified, cropped to the extent of an area of interest and noise points can be automatically identified and removed. The vertical accuracy of the data can be validated against surveyed control points and adjusted if needed.
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.
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.
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.
Feature extraction allows the user to render buildings, trees and power lines for greater visualization of LiDAR data. This new and powerful feature in Global Mapper is something normally only seen in software that costs thousands of dollars for a single user license. The Global Mapper Lidar module enables users to easily and quickly conduct feature extraction rendering appropriately classified lidar points as 2D and 3D feature objects. This powerful data will assist users that wish to create better and more exact earth models with realistically representative objects.
Using the new 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.
The display of points can be adjusted to reflect many of the attributes within the point cloud, including:
When overlaid on a raster or gridded layer, the RGB or NIR value from each underlying pixel can be added to the associated point.
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.
The module also includes the ability to leverage the LiDAR toolbar directly in the Path Profile viewer for faster management, editing and reclassifying of points. The module includes two selection options for selecting points in the Path Profile viewer, to select by a click and drag method or selection by drawing a custom polygon to select points.