Classify by Statistics Point Cloud Task
*This feature is available in the Standard license level and above for LP360.
The Classify by Statistics Point Cloud Task (PCT) allows for the classification of points based on the statistical analysis of a grid which you specify. A shapefile of your grid during the process of this point cloud task may also be produced.
Statistics supported by this point cloud task at this time include:
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Low Point
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High Point
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Median Point
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n Random Points
This task is primarily useful for thinning points based on these statistics. If your primarily interest is in the statistics themselves, the Point Cloud Statistics Extractor Point Cloud Task would be more suited to your needs.
Overview of the Classify by Statistics Point Cloud Task
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Input Datasets
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Feature Geometry - This is the input geometry for the point cloud task. It can be set within the I/O Manager by clicking the (...) button. The input geometry can be a Tool Geometry, File, or SHP Layer.
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Units - The Units setting allows you to optimize parameters in units of Feet or Meters, regardless of the units of the data. You will want to make sure that the Map View units are set to the units of the point cloud data.
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Input LAS Layer - The input LAS Layer can be the "Active Layer" or any other LAS Layer. Clicking the "Source Points..." button displays the Points Filter dialog to set different filtering options.
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Cell Size - Sets the size of the cells for the grid which will be created. Example: Specifying a cell size of 10 will create cells of 10 square units (feet or meters).
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Samples - Determines the type of samples taken from the cells during the point cloud task operation. Options are Min, Max, Median, and Random.
NoteIf you make the cell size too small, you may have many cells with no points. |
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Destination Class - Opens the Destination Class dialog which allows you to set the class and flags for the marked points.
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Generate Cell Output Shape file - Check this option if you want to output a gridded shapefile.
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Shapefile Clipping
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Full Grid (No Clipping) - The full grid option results in a grid that spans the input area, regardless of the presence of points that pass the Source Filter test.
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Clip to Source Points - The Clip to Source Points option will create a grid cell polygon only where a Source Point is present in the grid cell.
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Output Datasets
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Grid Output Shape File - The output file determines the location of the grid file. It can be set within the I/O Manager by clicking the (...) button. A good practice is to use the Project Path as the root location of the output file. This allows you to use the same task output file setting, regardless of project location.
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Classify by Elevation Quartiles
Use the standard output class/flag dialog to set the output of the outliers and quartile classification.
TipFor more information about quartiles go to Byjus Link |
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The area to be processed (as determined by however you use the PCT) is divided into a grid of square cells with size equal to the “Cell Size” setting of the dialog.
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A cell is processed by computing an elevation histogram of points (that pass the overall Source Filter for the PCT).
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The points are tagged as to which of the four quartiles they belong.
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If Outlier Classification has been selected for either High or Low Outliers, the Inter-Quartile Range (IQR) is computed. If Outlier classification has not been selected, the points are classified according to the Quartile Classification settings of Figure 2: and the task is complete.
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The High Points threshold is computed as the dividing elevation between Q3 and Q4 plus the user specified multiplier (unit selected by user at the top of the dialog) times the IQR. All points above this level will be set to the user selected High Points Classification/Flags.
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The Low Points threshold is computed as the dividing elevation between Q1 and Q2 minus the user specified multiplier times the IQR. All points below this level will be set to the user selected Low Points Classification/Flags.
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If you choose to create a shapefile of the grid, the metadata of the above algorithm are stored as attributes on the shapefile (below).
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The quartile classification section of the Classify by Statistics Point Cloud Task is a useful tool when using canopy height models (CHM).
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