Model Key Points Filter Property Page

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

The Model Key Points Filter is a point cloud task that can output Model Key Points into a separate class or can set the Model Key Point flag. This enhancement is to reduce the source point density based on a surface error model. Typically, the goal is to reduce the number of LAS points in a ground model to a minimum number required to meet an accuracy requirement, especially if the data needs to be exported to an application that does not handle bulk LAS points well.

How to use the Model Key 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 Model Key Points Filter. Once you click OK, you should see the unique name that you gave your task selected in the list and the Model Key Points Filter property page displayed on the Point Cloud Task tab.

3. Specify the settings for the Model Key Points Filter operation in the Properties page that displays. Then, click Apply and run the filter by using the Point Cloud Tasks toolbar. See below for more information.

Overview of the Model Key Points Filter Properties Window

Source Points
The Source Points Button is the set of points that will be used in the point cloud task. If a classification is not turned on or is a part of the point cloud task, then those points will not be used in the point cloud task nor will they be classified or edited. For instance, if a user is trying to construct a ground model then he would uncheck every box in Source Points except the Ground class. There are a number of other tabs for setting filters, if the user desires, based on Return Combination, Point Source IDs, Elevation Range, Scan Angle, etc.

Destination Class
The Destination Class defines the class that the points will be set to. Typically this will be set to the Model Key Points class You can also set any flags necessary in the dialog that opens. This is where you would set a Model Key Point flag on the points that are determined as Model Key Points.

Units
Units are the units of the parameters for this point cloud task. If the units of the data differs from the units specified for the parameters, a conversion is performed on-the-fly. If no units are assigned to the project data, no conversion is performed. For example, if the project units are in Feet (see the Units combo box at the bottom-center of the LP360 window), the user can choose to use Meters in the filter and enter 10 for the Sample Distance. Since the project's units are in Feet (common in state plane projects) the Model Key Points filter will automatically convert the 10 Meters into the requisite number of Feet units, which would be 30.

Sample Distance
The Sample Distance is the maximum desired distance between seed-points in the reduced model. The seed sample distance for any particular area in a data set can be considered constant. As point density increases or decreases the seed sample distance stays the same. Note: Selecting a very big or very small sample distance can decrease the performance of the algorithm. For instance, if the ground model is particularly flat, then the sample distance can be set to a larger number as fewer model key points are needed in order to maintain the overall accuracy of the model. In a very uneven or hilly model, this amount may need to be smaller in order to maintain the required accuracy. Many datasets are not perfectly flat, so there is a balance to be found between a number that is not too high or too low.  

In the example below, the flat area may only need a Model Key Point every 100 or 200 feet to maintain accuracy.

Maximum Positive Deviation
This is the maximum vertical distance of a point above the TIN surface that can be classified as a Model Key Point. A higher number results in less Model Key Points and similarly a lower number results in more Model Key Points. Basically, this is an error tolerance in the positive direction.

Maximum Negative Deviation
This is the maximum vertical distance of a point below the TIN surface that can be classified as a Model Key Point. A higher number results in less Model Key Points and similarly a lower number results in more Model Key Points. Basically, this is an error tolerance in the positive direction.