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 a 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.
The Compare Point Clouds tool performs a 3D change detection between a set of point clouds to find points that have changed more than an allowed minimum difference. The output of this Compare Clouds tool is a layer containing the points that have changed between the input point clouds. Also provided is the ability to generate different histograms, and the ability to color the points based on distance for better visualization of the measured distances.
To use the Compare Point Clouds tool, start by loading the point clouds you would like to compare into Global Mapper. Select the Compare Cloud tool from the Lidar toolbar. 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 Point Cloud(s) Selected to Find Changes In box will be compared to the “Point Cloud(s) to Compare Against” when the tool is run.
The 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.
In the image above, you see areas in the 2023 point cloud that weren’t present in the 2020 point cloud, after running the Compare Cloud tool we see the selected (red) areas are the points detected to be changed. If the Save Distance to Closest Point in Generic Field option was checked, you can also change the Lidar Draw mode to color the points based on how far they changed. More information on that can be found in another blog, How to evaluate distances between point clouds using Global Mapper Pro.
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 tool speeds up the process of change detection on 3D data by directly comparing two point clouds to find points with significant change. Change detection functionality can be applied in a wide variety of industries including agriculture, forestry, and engineering.