Skip To Content

Locate LAS Points By Proximity


Identifies lidar points within the three-dimensional proximity of z-enabled features while also providing the option to reclassify the points and export them to an output feature class.


  • This tool updates the input feature with a field that contains the count of LAS points that fall within the specified search radius.

  • When a LAS dataset is specified as input, all the data points in the LAS files it references will be processed. A subset of lidar data can also be selected by its classification codes, classification flags, and return values by applying the desired LAS point filters through a LAS dataset layer. Filters can be defined through the layer properties dialog or the Make LAS Dataset Layer tool.

  • Consider using this tool to identify the presence of potential obstructions within a specified proximity to features of interest, such as vegetation encroachment near utility lines.


LocateLasPointsByProximity_3d (in_las_dataset, in_features, search_radius, count_field, {out_features}, {geometry}, {class_code}, {compute_stats})
ParameterExplanationData Type

The LAS dataset to process.

LAS Dataset Layer

The 3D point, line, or polygon features whose proximity will be used for identifying LAS points.

Feature Layer

The distance of the space around the input features that will be evaluated for the presence of LAS points, which can be provided as either a linear distance or a numeric field in the input feature's attribute table.

If the search radius is derived from a field or a linear distance whose units are specified as Unknown, the linear unit of the input features' XY spatial reference is used.

The following units are supported:

  • UNKNOWNUnknown
  • INCHESInches
  • FEETFeet
  • YARDSYards
  • MILESMiles
  • CENTIMETERSCentimeters
  • DECIMETERSDecimeters
  • METERSMeters
  • KILOMETERSKilometers
Linear Unit; Field

The name of the count field that will be added to the input feature's attribute table. The field's values will reflect the sum of LAS points that are in the proximity of an input feature.


Output point features that represent the LAS points found within the specified proximity of the input features.

Feature Class

The geometry of the output point features that represent the LAS points found within the specified proximity of the input features.

  • MULTIPOINTMultipoint features that will have multiple points in each row.
  • POINTSingle-point features that will have a unique row for each identified LAS point.

The class code value that will be used to reclassify the points found within the search radius of the input features.


Specifies whether statistics should be computed for the LAS files referenced by the LAS dataset. The presence of statistics allows the LAS dataset layer's filtering and symbology options to only show LAS attribute values that exist in the LAS files.

  • COMPUTE_STATSStatistics will be computed.
  • NO_COMPUTE_STATSStatistics will not be computed. This is the default.

Code sample

LocateLasPointsByProximity example 1 (Python window)

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

import arcpy
from arcpy import env

env.workspace = 'C:/data'
arcpy.LocateLasPointsByProximity_3d('lidar.lasd', 'powerlines.shp', 
                                    search_radius="10 Feet", 
LocateLasPointsByProximity example 2 (stand-alone script)

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

Name: Classify Noise Points
Description: Updates classification of version 1.0 LAS files to conform to
             the standardized class codes introduced in the 1.1 specifications.
             The code is designed for use as a script tool.
# Import system modules
import arcpy
import exceptions, sys, traceback

# Set Local Variables
inLas = arcpy.GetParameterAsText(0)
recursion = arcpy.GetParameterAsText(1)
lasd = arcpy.GetParameterAsText(2)
reclassList = arcpy.GetParameterAsText(3) #List of values '<oldCode> <newCode>'
calcStats = arcpy.GetParameter(4)

    # Execute CreateLasDataset, lasd, folder_recursion=recursion)
    # Execute Locate Outliers
    outlier_pts = 'in_memory/outliers'
    arcpy.ddd.LocateOutliers(lasd, out_feature_class=outlier_pts, 
                            absolute_z_min=-15, absolute_z_max=680, 
                            z_tolerance=0, slope_tolerance=150, 
                            exceed_tolerance_ratio=0.5, outlier_cap=3000)
    # Execute ChangeLasClassCodes
    arcpy.ddd.LocateLasPointsByProximity(lasd, in_features=outlier_pts, 
                                         search_radius='0.5 Centimeters', 
    # Report messages

except arcpy.ExecuteError:

Licensing information

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

Related topics