March 24, 2020

How to Compare Point Clouds Using Global Mapper

Written by: Mackenzie Mills, Application Specialist


In many areas of GIS,  change detection can be a powerful analysis tool. Comparing datasets through time can add another dimension to your work as you can visualize and measure how a study area changes. This type of analysis is becoming particularly important as drone mapping and collection of first-hand data are more common. Change detection analysis can also be very useful when looking for natural change in an area, like the impact of a natural disaster or new vegetation growth year to year; or a man-made change, like the progress of construction in an area or deforestation; or change made to the data by previous edits.

In the release of Global Mapper version 21.1, the Compare Clouds tool was introduced to detect change points between overlapping lidar or point cloud layers. Previously in Global Mapper, change detection was only available using the Combine/Compare Terrain Grid tool, which creates a new elevation layer based on the difference in the per-pixel Z-values of the overlapping layers using the subtraction setting.  The output of the new Compare Clouds tool is a layer containing the points that have changed between the input point clouds.

To use the Compare Cloud tool, start by loading the point clouds you would like to compare into Global Mapper. Select the Compare Could tool from the Lidar Tools toolbar.

Compare Lidar Point Clouds

In the Point Cloud(s) to Compare Against box, select the starting or original point cloud. This is typically the first or earlier pass over an area. The cloud(s) selected in the Point Cloud(s) to Find Changes In box will be compared to the “Point Cloud(s) to Compare Against when the tool is run.

This new tool works to compare point clouds by having the user input a distance to use for comparison. This Minimum Distance Between Point Clouds value allows for a looser or tighter comparison of the clouds. This setting is important when comparing point clouds because they are made up of individual points and not interpolated like a terrain grid. It is unlikely that the point clouds you are looking to compare will contain points in the exact locations, so a threshold (specified in point spacings, meters, or feet) is required for comparison. Any points from the Find Changes In point cloud that do not have a corresponding point in the Compare Against cloud will be considered changes in the area.

When the process runs, those points in the second layer that have been found to have shifted beyond the designated threshold when compared to the original layer will be marked as having changed. After running this process, you will find a new layer added to the workspace containing only the points that have changed.

Points detected to be changed using the Compare Cloud tool in Global Mapper

In the image above, you see an area of rocks where some have been removed between point cloud one and point cloud two, after running the Compare Cloud tool we see the selected (red) areas are the points detected to be changed.

After identifying change in an area using the Compare Clouds tool, you may wish to classify the points detected as changed or delete them to reconcile multiple datasets. Alternatively, you may want to generate gridded layers to show the changed areas and layer these changed grids over the original or use the Compare Against layer.

This powerful new tool speeds up the process of change detection on 3D data by directly comparing two point clouds to find points with significant change. This change detection functionality can be applied in a wide variety of industries including agriculture, forestry, and engineering. Take a look at the latest release of Global Mapper and the Lidar Module to bring this streamlined workflow into your own data analysis.

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