Global Polynomial Interpolation

Fits a smooth surface that is defined by a mathematical function (a polynomial) to the input sample points.

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contributed at 2019-05-16

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Detailed Description

Code Sample

GlobalPolynomialInterpolation example 1 (Python window)

Interpolate point features onto a rectangular raster.

import arcpy

arcpy.env.workspace = "C:/gapysamples/data"

arcpy.GlobalPolynomialInterpolation_ga("ca_ozone_pts", "OZONE", "outGPI",

                                       "C:/gapyexamples/output/gpiout", "2000", "2", "")

GlobalPolynomialInterpolation example 2 (stand-alone script)

Interpolate point features onto a rectangular raster.

# Name: GlobalPolynomialInterpolation_Example_02.py

# Description: Global Polynomial interpolation fits a smooth surface that is

#              defined by a mathematical function (a polynomial) to the input

#              sample points. The Global Polynomial surface changes gradually

#              and captures coarse-scale pattern in the data.  Global Polynomial

#              interpolation is like taking a piece of paper and fitting it

#              between the raised points (raised to the height of value).

# Requirements: Geostatistical Analyst Extension

 

# Import system modules

import arcpy

 

# Set environment settings

arcpy.env.workspace = "C:/gapyexamples/data"

 

# Set local variables

inPointFeatures = "ca_ozone_pts.shp"

zField = "ozone"

outLayer = "outGPI"

outRaster = "C:/gapyexamples/output/gpiout"

cellSize = 2000.0

power = 2

 

# Check out the ArcGIS Geostatistical Analyst extension license

arcpy.CheckOutExtension("GeoStats")

 

# Execute GlobalPolynomialInterpolation

arcpy.GlobalPolynomialInterpolation_ga(inPointFeatures, zField, outLayer,

                                       outRaster, cellSize, power)

 

How to Cite

ESRI (2019). Global Polynomial Interpolation, Computable Model, OpenGMS, https://geomodeling.njnu.edu.cn/computableModel/692cf7e2-eef7-43f3-982e-1860b1ac15a8
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contributed at 2019-05-16

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