Interpolate From Point Cloud (Data Management)

Summary

Interpolates a digital terrain model (DTM) or a digital surface model (DSM) from a point cloud.

Usage

• The form of the point cloud can be either LAS files or a solution point table.

Parameters

Dialog

Label	Explanation	Data Type
Input LAS Folder or Point Table	The path and name of the file, folder, or feature layer. The input can be a folder of LAS files or a solution point table from orthomapping tools. The LAS files can be the output from the Generate Point Cloud tool, in which LAS points are categorized as ground and above ground. The solution point table is output from either the Compute Block Adjustments tool or the Compute Camera Model tool.	Folder; File; Feature Layer
Output Raster	The output raster dataset location, name, and file extension. The output can be created in most writable raster formats, such as TIFF, CRF, or IMG.	Raster Dataset
Cellsize	The cell size of the output raster dataset.	Double
Interpolation Method (Optional)	Specifies the method that will be used to interpolate the output raster dataset from the point cloud. TIN linear interpolation— The triangulation method will be used. It is also known as triangulated irregular network (TIN) linear interpolation and is designed for irregularly distributed sparse points, such as solution points from block adjustment computation. TIN natural neighbor interpolation—The natural neighbor method will be used. It is similar to triangulation but generates a smoother surface and is more computationally intensive. Inverse distance weighted average interpolation—The inverse distance weighted (IDW) average method will be used. It is used for regularly distributed dense points, such as point cloud LAS files from the Generate Point Cloud tool. The IDW search radius is automatically computed based on average point density.	String
Smoothing Method (Optional)	Specifies the filter that will be used to smooth the output raster dataset. Gaussian 3 by 3—A Gaussian filter with a 3 by 3 window will be used. Gaussian 5 by 5—A Gaussian filter with a 5 by 5 window will be used. Gaussian 7 by 7—A Gaussian filter with a 7 by 7 window will be used. Gaussian 9 by 9—A Gaussian filter with a 9 by 9 window will be used. No smoothing—No smoothing filter will be used.	String
Surface Type (Optional)	Specifies whether a digital terrain model or a digital surface model will be created. Digital terrain model—A digital terrain model will be created by interpolating only the ground points. Digital surface model—A digital surface model will be created by interpolating all the points.	String
Input Fill DEM (Optional)	A DEM raster input that is used to fill NoData areas. Areas of NoData may exist where pixels do not have enough information from the input to generate values.	Raster Dataset; Raster Layer; Mosaic Dataset; Mosaic Layer

Python

arcpy.management.InterpolateFromPointCloud(in_container, out_raster, cell_size, {interpolation_method}, {smooth_method}, {surface_type}, {fill_dem})

Name	Explanation	Data Type
in_container	The path and name of the file, folder, or feature layer. The input can be a folder of LAS files or a solution point table from orthomapping tools. The LAS files can be the output from the Generate Point Cloud tool, in which LAS points are categorized as ground and above ground. The solution point table is output from either the Compute Block Adjustments tool or the Compute Camera Model tool.	Folder; File; Feature Layer
out_raster	The output raster dataset location, name, and file extension. The output can be created in most writable raster formats, such as TIFF, CRF, or IMG.	Raster Dataset
cell_size	The cell size of the output raster dataset.	Double
interpolation_method (Optional)	Specifies the method that will be used to interpolate the output raster dataset from the point cloud. TRIANGULATION— The triangulation method will be used. It is also known as triangulated irregular network (TIN) linear interpolation and is designed for irregularly distributed sparse points, such as solution points from block adjustment computation. NATURAL_NEIGHBOR—The natural neighbor method will be used. It is similar to triangulation but generates a smoother surface and is more computationally intensive. IDW—The inverse distance weighted (IDW) average method will be used. It is used for regularly distributed dense points, such as point cloud LAS files from the Generate Point Cloud tool. The IDW search radius is automatically computed based on average point density.	String
smooth_method (Optional)	Specifies the filter that will be used to smooth the output raster dataset. GAUSS3x3—A Gaussian filter with a 3 by 3 window will be used. GAUSS5x5—A Gaussian filter with a 5 by 5 window will be used. GAUSS7x7—A Gaussian filter with a 7 by 7 window will be used. GAUSS9x9—A Gaussian filter with a 9 by 9 window will be used. NONE—No smoothing filter will be used.	String
surface_type (Optional)	Specifies whether a digital terrain model or a digital surface model will be created. DTM—A digital terrain model will be created by interpolating only the ground points. DSM—A digital surface model will be created by interpolating all the points.	String
fill_dem (Optional)	A DEM raster input that is used to fill NoData areas. Areas of NoData may exist where pixels do not have enough information from the input to generate values.	Raster Dataset; Raster Layer; Mosaic Dataset; Mosaic Layer

Code sample

InterpolateFromPointCloud example 1 (stand-alone script)

This is a Python sample for the InterpolateFromPointCloud function.

import arcpy
arcpy.InterpolateFromPointCloud_management('c:/data/LASFolder',
                                           'c:/data/dsm.crf', '10',
                                           'IDW', 'GAUSS5x5', 'DTM')

Environments

Cell Alignment, Current Workspace, Extent, Geographic Transformations, Mask, Output Coordinate System, Parallel Processing Factor, Pyramid, Scratch Workspace

Licensing information

• Basic: No
• Standard: Requires ArcGIS Reality
• Advanced: Yes