Classify LAS Noise (3D Analyst)

Summary

Classifies LAS points with anomalous spatial characteristics as noise.

Usage

• Noise points in LAS returns typically have a detrimental impact on data visualization and analysis. For example, returns from high-flying birds and scattered pulses that encountered cloud cover, smog haze, water bodies, and highly reflective mirrors can distort the z-range of the points surrounding that location. Identifying such points as noise will allow them to be filtered out from the display and eliminated from the production of any derivative data, such as an elevation surface, slope or aspect profile.

• The Isolation method will process the LAS data in tiled 3 by 3 bins based on the region defined by the Neighborhood Width and Neighborhood Height parameters. If the number of LAS points in the analysis volume is less than the Neighborhood Point Limit parameter value, the LAS points will be treated as noise. The point limit should reflect a reasonable approximation based on the lidar point density and the number of LAS points that can be anticipated in the analysis volume.

• If some LAS point returns have abnormally high or low z-values for the region captured by the lidar collection, consider using the Absolute Height method to define the z-value threshold of the data to quickly identify the outlier points as noise.

• If LAS points have abnormally high or low z-values for specific regions, but those values fall within the range of valid measurements captured in the lidar collection, consider using the Relative Height method to define the z-value threshold of valid data based on an offset from the ground. To generate a ground surface, filter the LAS dataset for ground classified points, and use the LAS Dataset To Raster tool.

• Only LAS points with class code values of 0 or 1 will be reclassified. If unclassified points are represented by some other value, consider using the Change LAS Class Codes tool to assign the unclassified points a value of 1. When noise points are being classified and either the Isolation or Absolute Height method is used, all noise points will be assigned a class code value of 7. If the Relative Height method is used, noise points that are below the Minimum Height parameter threshold will be assigned a value of 7, which represents low noise; noise points that are above the Maximum Height parameter threshold will be assigned a value of 18, which represents high noise.

• If you are unsure about the settings to be used for determining noise points, consider exporting the LAS points detected as noise as a point feature while the option to edit the LAS classification code is disabled. If the output points reflect the expected results, you can reclassify the LAS points using those features through the Locate LAS Points By Proximity tool.

• The isolation method is a performance intensive operation that runs faster with larger bin sizes. Specify the largest possible bin size based on the nature and distribution of the data for best performance.

Parameters

Dialog

Label	Explanation	Data Type
Input LAS Dataset	The LAS dataset to process.	LAS Dataset Layer
Method	Specifies the noise detection method that will be used. Isolation—The spatial proximity of LAS points will be analyzed in tiled volumes to determine noise measurements along with height-based noise detection. This is the default. Relative Height from Ground—All points below the specified minimum height from the ground surface and above the maximum height from the ground surface will be identified as noise. Absolute Height—All points below the specified minimum height and above the maximum height in relation to mean sea level will be identified as noise.	String
Edit Classification	Specifies whether LAS points that are identified as noise will be reclassified. Checked—Noise points will be reclassified. This is the default. Unchecked—Noise points will not be classified.	Boolean
Assign Withheld Flag	Specifies whether the withheld classification flag will be assigned to noise points. This option is only enforced if the Edit Classification parameter is checked. Checked—The withheld classification flag will be assigned to noise points. Unchecked—The withheld classification flag will not be assigned to noise points. This is the default.	Boolean
Compute statistics (Optional)	Specifies whether statistics will be computed for the .las files referenced by the LAS dataset. Computing statistics provides a spatial index for each .las file, which improves analysis and display performance. Statistics also enhance the filtering and symbology experience by limiting the display of LAS attributes, such as classification codes and return information, to values that are present in the .las file. Checked—Statistics will be computed. This is the default. Unchecked—Statistics will not be computed.	Boolean
Ground	The ground surface that will be used to define relative height.	Raster Layer
Minimum Height	The height that will define the lowest z-value threshold for identifying noise points. Any point that is lower than the specified value will be classified as noise. If a ground surface is specified, this threshold will be based on an offset from the ground such that a value of -3 feet means any points that are 3 feet below the ground surface will be classified as noise.	Linear Unit
Maximum Height	The height that will define the highest z-value threshold for identifying noise points. Any point that is higher than the specified value will be classified as noise. If a ground surface is provided, this threshold will be based on an offset from the ground such that a value of 250 meters means any points that are higher than 250 meters above the ground surface will be classified as noise.	Linear Unit
Neighborhood Point Limit	The maximum number of points in the analysis volume that can be qualified as noise when using the Isolation method. If the analysis volume contains any number of LAS points that are equal to or less than this value, those points will be classified as noise.	Long
Neighborhood Width	The size of each dimension in the XY space of the analysis volume when using the Isolation method.	Linear Unit
Neighborhood Height	The height of the analysis volume when using the Isolation method.	Linear Unit
Processing Extent (Optional)	The extent of the data that will be evaluated. Default—The extent will be based on the maximum extent of all participating inputs. This is the default. Union of Inputs—The extent will be based on the maximum extent of all inputs. Intersection of Inputs—The extent will be based on the minimum area common to all inputs. Current Display Extent—The extent is equal to the visible display. The option is not available when there is no active map. As Specified Below—The extent will be based on the minimum and maximum extent values specified. Browse—The extent will be based on an existing dataset.	Extent
Process entire LAS files that intersect extent (Optional)	Specifies how the area of interest will be used in determining how .las files will be processed. The area of interest is defined by the Processing Extent parameter value, the Processing Boundary parameter value, or a combination of both. Unchecked—Only LAS points that intersect the area of interest will be processed. This is the default. Checked—If any portion of a .las file intersects the area of interest, all the points in that .las file, including those outside the area of interest, will be processed.	Boolean
Output Noise Points (Optional)	The output point features that represent the LAS points identified as noise.	Feature Class
Update pyramid (Optional)	Specifies whether the LAS dataset pyramid will be updated after the class codes are modified. Checked—The LAS dataset pyramid will be updated. This is the default. Unchecked—The LAS dataset pyramid will not be updated.	Boolean

Derived Output

Label	Explanation	Data Type
Output LAS Dataset	The LAS dataset to be modified.	LAS Dataset Layer

Python

arcpy.ddd.ClassifyLasNoise(in_las_dataset, method, edit_las, withheld, {compute_stats}, ground, low_z, high_z, max_neighbors, step_width, step_height, {extent}, {process_entire_files}, {out_feature_class}, {update_pyramid})

Name	Explanation	Data Type
in_las_dataset	The LAS dataset to process.	LAS Dataset Layer
method	Specifies the noise detection method that will be used. ISOLATION—The spatial proximity of LAS points will be analyzed in tiled volumes to determine noise measurements along with height-based noise detection. This is the default. RELATIVE_HEIGHT—All points below the specified minimum height from the ground surface and above the maximum height from the ground surface will be identified as noise. ABSOLUTE_HEIGHT—All points below the specified minimum height and above the maximum height in relation to mean sea level will be identified as noise.	String
edit_las	Specifies whether LAS points that are identified as noise will be reclassified. CLASSIFY—Noise points will be reclassified. This is the default. NO_CLASSIFY—Noise points will not be classified.	Boolean
withheld	Specifies whether the withheld classification flag will be assigned to noise points. This option is only enforced if the edit_las parameter is set to CLASSIFY. WITHHELD—The withheld classification flag will be assigned to noise points. NO_WITHHELD—The withheld classification flag will not be assigned to noise points. This is the default.	Boolean
compute_stats (Optional)	Specifies whether statistics will be computed for the .las files referenced by the LAS dataset. Computing statistics provides a spatial index for each .las file, which improves analysis and display performance. Statistics also enhance the filtering and symbology experience by limiting the display of LAS attributes, such as classification codes and return information, to values that are present in the .las file. COMPUTE_STATS—Statistics will be computed. This is the default. NO_COMPUTE_STATS—Statistics will not be computed.	Boolean
ground	The ground surface that will be used to define relative height.	Raster Layer
low_z	The height that will define the lowest z-value threshold for identifying noise points. Any point that is lower than the specified value will be classified as noise. If a ground surface is specified, this threshold will be based on an offset from the ground such that a value of -3 feet means any points that are 3 feet below the ground surface will be classified as noise.	Linear Unit
high_z	The height that will define the highest z-value threshold for identifying noise points. Any point that is higher than the specified value will be classified as noise. If a ground surface is provided, this threshold will be based on an offset from the ground such that a value of 250 meters means any points that are higher than 250 meters above the ground surface will be classified as noise.	Linear Unit
max_neighbors	The maximum number of points in the analysis volume that can be qualified as noise when using the Isolation method. If the analysis volume contains any number of LAS points that are equal to or less than this value, those points will be classified as noise.	Long
step_width	The size of each dimension in the XY space of the analysis volume when using the Isolation method.	Linear Unit
step_height	The height of the analysis volume when using the Isolation method.	Linear Unit
extent (Optional)	The extent of the data that will be evaluated. MAXOF—The maximum extent of all inputs will be used. MINOF—The minimum area common to all inputs will be used. DISPLAY—The extent is equal to the visible display. Layer name—The extent of the specified layer will be used. Extent object—The extent of the specified object will be used. Space delimited string of coordinates—The extent of the specified string will be used. Coordinates are expressed in the order of x-min, y-min, x-max, y-max.	Extent
process_entire_files (Optional)	Specifies how the processing extent will be applied. PROCESS_EXTENT—Only LAS points that intersect the area of interest will be processed. This is the default. PROCESS_ENTIRE_FILES—If any portion of a .las file intersects the area of interest, all the points in that .las file, including those outside the area of interest, will be processed.	Boolean
out_feature_class (Optional)	The output point features that represent the LAS points identified as noise.	Feature Class
update_pyramid (Optional)	Specifies whether the LAS dataset pyramid will be updated after the class codes are modified. UPDATE_PYRAMID—The LAS dataset pyramid will be updated. This is the default. NO_UPDATE_PYRAMID—The LAS dataset pyramid will not be updated.	Boolean

Derived Output

Name	Explanation	Data Type
out_las_dataset	The LAS dataset to be modified.	LAS Dataset Layer

Code sample

ClassifyLasNoise example 1 (Python window)

The following sample demonstrates the use of this tool in the Python window.

arcpy.env.workspace = 'C:/data'

arcpy.ddd.ClassifyLasNoise('Denver_2.lasd', "ABSOLUTE_HEIGHT", 
                           edit_las='CLASSIFY', withheld='WITHHELD', 
                           high_z='450 Feet')

ClassifyLasNoise example 2 (stand-alone script)

The following sample demonstrates the use of this tool in a stand-alone Python script.

'''****************************************************************************
       Name: Classify Lidar & Extract Building Footprints
Description: Extract footprint from lidar points classified as buildings, 
             regularize its geometry, and calculate the building height.

****************************************************************************'''
import arcpy

lasd = arcpy.GetParameterAsText(0)
dem = arcpy.GetParameterAsText(1)
footprint = arcpy.GetParameterAsText(2)

try:
    desc = arcpy.Describe(lasd)
    if desc.spatialReference.linearUnitName in ['Foot_US', 'Foot']:
        unit = 'Feet'
    else:
        unit = 'Meters'
    ptSpacing = desc.pointSpacing * 2.25
    sampling = '{0} {1}'.format(ptSpacing, unit)
    # Classify overlap points
    arcpy.ddd.ClassifyLASOverlap(lasd, sampling)
    # Classify ground points
    arcpy.ddd.ClassifyLasGround(lasd)
    # Filter for ground points
    arcpy.management.MakeLasDatasetLayer(lasd, 'ground', class_code=[2])
    # Generate DEM
    arcpy.conversion.LasDatasetToRaster('ground', dem, 'ELEVATION', 
                                        'BINNING NEAREST NATURAL_NEIGHBOR', 
                                        sampling_type='CELLSIZE', 
                                        sampling_value=desc.pointSpacing)
    # Classify noise points
    arcpy.ddd.ClassifyLasNoise(lasd, method='ISOLATION', edit_las='CLASSIFY', 
                               withheld='WITHHELD', ground=dem, 
                               low_z='-2 feet', high_z='300 feet', 
                               max_neighbors=ptSpacing, step_width=ptSpacing, 
                               step_height='10 feet')
    # Classify buildings
    arcpy.ddd.ClassifyLasBuilding(lasd, '7.5 feet', '80 Square Feet')
    #Classify vegetation
    arcpy.ddd.ClassifyLasByHeight(lasd, 'GROUND', [8, 20, 55], 
                                  compute_stats='COMPUTE_STATS')
    # Filter LAS dataset for building points
    lasd_layer = 'building points'
    arcpy.management.MakeLasDatasetLayer(lasd, lasd_layer, class_code=[6])
    # Export raster from lidar using only building points
    temp_raster = 'in_memory/bldg_raster'
    arcpy.management.LasPointStatsAsRaster(lasd_layer, temp_raster,
                                           'PREDOMINANT_CLASS', 'CELLSIZE', 2.5)
    # Convert building raster to polygon
    temp_footprint = 'in_memory/footprint'
    arcpy.conversion.RasterToPolygon(temp_raster, temp_footprint)
    # Regularize building footprints
    arcpy.ddd.RegularizeBuildingFootprint(temp_footprint, footprint, 
                                          method='RIGHT_ANGLES')

except arcpy.ExecuteError:
    print(arcpy.GetMessages())

Environments

Current Workspace, Output Coordinate System, Geographic Transformations

Licensing information

• Basic: Requires 3D Analyst
• Standard: Requires 3D Analyst
• Advanced: Requires 3D Analyst