Amanda Lind from Blue Marble Geographics discusses the functionality of the Compare Point Clouds feature within the global Mapper Pro software,facilitating straightforward elevation comparisons between two point clouds.
Analyzing the spatial differences between point clouds serves as an effective technique for evaluating modifications made to datasets, assessing photogrammetric precision, or monitoring landscape transformations over time, as well as verifying the performance of various lidar sensors. The Compare Point Clouds feature in Global Mapper simplifies the process of comparing elevation data across two point clouds. The latest version,24.1, introduces the capability to create Difference histograms and a new color-coding option for enhanced visualization of the measured discrepancies.
Utilizing the Path Profile tool, we can observe the subtle elevation variations between a P2P generated cloud (RGB) and the lidar data (color-coded by elevation). The Compare Point Clouds feature quantifies these differences.
Types of Point Clouds
Point clouds are widely used for measuring the earth’s surface and its features. In Geographic Information Systems (GIS), there are primarily two categories of point clouds: lidar and photogrammetric. While both types can be processed using the same tools in Global Mapper, understanding their respective limitations is crucial for users.
When contrasting lidar data with photogrammetrically generated point clouds, it is advisable to first filter for ground points by disabling all other classifications using the Filter lidar tool.
A notable limitation of photogrammetry is its inability to penetrate thick forest canopies. When comparing ground points from lidar with the lowest points captured through photogrammetry, discrepancies akin to tree heights frequently enough arise. This information can be especially useful when assessing vegetation heights (Thomas, 2020).
This Path Profile view illustrates how the darker points from the photogrammetrically derived cloud may not always accurately represent the ground compared to lidar data.
Utilizing the Compare Point Clouds Feature
The Compare Point Clouds feature conducts a 3D change detection analysis between two sets of point clouds, identifying points that exceed a specified minimum difference. Essentially, it locates points in one cloud that are further away than a defined distance from another reference/control point cloud.
Version 24.1 has enhanced this tool as part of the Pixels to Points (P2P) workflow,providing a refined method for evaluating the accuracy of dense photogrammetric point clouds in comparison to the generally more reliable lidar data. While all settings are detailed in the knowledge base, the two new optional features merit further discussion.
The difference report feature generates three windows, two of which are distance histograms that illustrate the count and distance of points in the Source (Compare Against) and the Reference (Find Changes In). Ideally, the distribution of points should resemble a normal distribution, represented by a bell curve.
Upon completion, points with a measured difference will be automatically highlighted (in red), allowing for easy copying and pasting into a new layer.
The Save Distance to Closest Point in Generic Field option enables users to visualize the measured distances through point cloud color. After processing,switch the Lidar Draw Mode to Generic to view these results. “Generic” refers to this additional attribute option integrated into .LAS/.LAZ file formats. Global Mapper leverages this flexible attribute to allow users to export these calculated distance values as part of the lidar data,if desired.
The ‘Color by Generic Value’ is determined by the active shader. To modify the color scheme, adjust the shader in the dropdown or configuration menu.
After evaluating the differences between clouds, the Fit Point clouds tool can be employed to align one cloud’s position to match the other.
A comparable process is raster differencing, where point clouds are transformed into solid raster grids or Digital Elevation Models (DEMs). When these are subtracted using the Combine/Compare Terrain Layers tool, a difference raster or digital elevation difference layer is produced to illustrate the measured variations.
To assess the distance between point clouds and Ground Control Points (GCP), the Lidar QC tool can be utilized. Following the distance measurement, Lidar QC offers the option to adjust the point cloud(s) closer to the GCPs.
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References:
- Amanda F. Thomas, Amy E. Frazier, Adam J. Mathews & Carlos E. Cordova (2020) Impacts of Abrupt Terrain Changes and Grass Cover on Vertical Accuracy of UAS-SfM derived Elevation Models, Papers in Applied Geography, 6:4, 336-351, DOI: 10.1080/23754931.2020.1782254
