Low/Isolated Points Filter

*This feature is available in the Advanced license level of LP360.

About the Low/Isolated Points Filter Point Cloud Task

The Low/Isolated Points Filter is an automated algorithm that is used to find low points and/or isolated points.

The low points option was designed for removing points lower than the ground surface prior to performing an automated ground classification. These points typically occur due to an anomaly in the data collection process such as a multi-path. For example, the purple point in the figure below is clearly an anomalous point that has occurred beneath the true ground surface. If low points are not removed prior to ground classification, these points will be included in the ground surface, creating an error.

Isolated points are points that are "far" from other points in the point cloud. Common causes for isolated points are hits from birds and water surfaces. It can be desirable to move these points to a separate class to prevent them from being introduced into an inappropriate class (e.g. you may not want bird hits showing up in the "high vegetation" class).

The Basic Algorithm for Low Points: The Low/Isolated algorithm considers each point from the Source Points selection. For each point, a radius (as specified by the radius parameter), in the X, Y plane is considered. All points within the limits of the radius are counted. If no more Cluster Size points are lower than all other points by Z Tolerance or more, the points are reclassified to the Low Class.

The Basic Algorithm for Isolated Points: If no points other than the candidate point occur within a cylinder with a radius defined by the specified radius and a height above and below the candidate point, centered on the candidate point, the candidate point is reclassified to the Isolated Points class. Note that the Cluster parameter is not used in the Isolated Points classifier.

How to create a Low/Isolated Points Filter

1. Use the Add Files command to open the LAS files that contain the data you want to use.  

2. Use the Add Task command to create a new point cloud task. When you are selecting a Task Type in the Add Point Cloud Task dialog, select the Low/Isolated Points Filter. Once you click OK, you should see the unique name that you gave your task selected in the list and the Low/Isolated Points Filter property page displayed on the Point Cloud Task tab.

3. Specify the settings for the Low/Isolated Points Filter operation in the Properties page that displays.

Overview of the Low/Isolated Points Filter Properties Window

Source Points
Click this to open the Source Filter dialog. Here you can set which points the task will draw from when performing its low and isolated point filter algorithms.

Filter Low Points
Checking this box enables the Low Points Classifier.

Low Class
This button opens the Low Destination Class dialog, where you can choose the class and/or flag that the identified Low Points will be moved into.

Cluster Size
Cluster size indicates the maximum number of points to be considered by the Low Points algorithm.

Filter Isolated Points
If checked, the isolated points algorithm is run.

Isolated Class
This button opens the Isolated Destination Class dialog, where you can choose the class and/or flag that the identified Isolated Points will be moved into.

Units
Converts the Map Units if this unit setting is different (e.g. if the Map Units are set to meters and the units of this dialog are set to feet, the input units of the dialog will be converted to meters).

Radius
The radial distance from the current candidate source point to be used in the algorithm. A smaller radius generally results in more points becoming classified (since the current candidate point will be compared to fewer neighborhood points).

Z Tolerance
The minimum vertical distance that a candidate point (or set of points up to the Cluster Size) must be below neighbor points to be considered a low point.