Interpolate Irregular Data function

Overview

Point clouds, LiDAR and other datasets store their geolocation as irregularly spaced arrays of point data. The Interpolate Irregular Data function converts irregularly gridded point feature class data into a raster dataset with square pixels.

Notes

You can change the interpolation method and output cell size used in the Interpolate Irregular Data raster function.

Parameters

Parameter name	Description
Input Samples	The input point feature class or shapefile.
Value Field	The name of the field that contains the value of the points to be interpolated.
Cellsize	The cell size for the output raster dataset. This can be different from the input raster, though the extent of the raster dataset will remain the same.
Interpolation Method	The resampling method to use for interpolation: Nearest Neighbor—Calculates pixel value using the nearest pixel. If no source pixel exists, no new pixel can be created in the output. This is the default. Linear Tinning—Uses a triangular irregular network from the center points of each cell in the irregular raster to interpolate a surface that is then converted to a regular raster. Natural Neighbor—Finds the closest subset of input samples to a query point and applies weights to them based on proportionate areas to interpolate a value. Inverse Distance Weighted—Determines cell values using a linearly weighted combination of a set of sample points or cells. The weight is a function of the inverse of the distance from the known points or cells.
Search Radius	The number of pixels to be included for resampling. The default value is 3 pixels.