ArcMap

Areal Interpolation Layer To Polygons

Disponible avec une licence Geostatistical Analyst.

Résumé

Reaggregates the predictions of an Areal Interpolation layer to a new set of polygons.

Learn more about Areal Interpolation

Utilisation

  • This tool is used to reaggregate polygonal data. After an Areal Interpolation layer is created in the Geostatistical Wizard, this tool aggregates the predictions to a new set of polygons.

  • This tool can be used in the workflow to downscale or upscale polygonal data, such as predicting population in census blocks from population counts in postal codes.

  • The input geostatistical layer must be the result of performing Areal Interpolation on a dataset. Geostatistical layers resulting from other interpolation techniques cannot be used with this tool.

  • The fields in the output feature class can include the following (where applicable):

    • Predicted—The predicted value of the polygon. The interpretation of the predicted value depends on the type of data used to create the areal interpolation geostatistical layer:
      • Average (Gaussian)—Predicts the average value of the Gaussian variable in the polygon.
      • Rate (Binomial)—Predicts the proportion of the population of a polygon that has a particular characteristic.
      • Event (Overdispersed Poisson)—Predicts the count in the polygon. If a time field is specified, the tool predicts the count per unit time.
    • StdError—The standard error of predicted values in the polygons.
    • Included—Indicates whether a stable prediction can be made for the polygon. If a prediction cannot be made, a description will indicate why it cannot be made.

Syntaxe

ArealInterpolationLayerToPolygons(in_areal_interpolation_layer, in_polygon_features, out_feature_class, {append_all_fields})
ParamètreExplicationType de données
in_areal_interpolation_layer

Input geostatistical layer resulting from an Areal Interpolation model.

Geostatistical Layer
in_polygon_features

The polygons where predictions and standard errors will be aggregated.

Feature Layer
out_feature_class

The output feature class containing the aggregated predictions and standard errors for the new polygons.

Feature Class
append_all_fields
(Facultatif)

Determines whether all fields will be copied from the input features to the output feature class.

  • ALL — All fields from the input features will be copied to the output feature class. This is the default.
  • FID_ONLY — Only the feature ID will be copied, and it will be named Source_ID on the output feature class.
Boolean

Exemple de code

ArealInterpolationLayerToPolygons example 1 (Python window)

Aggregate areal interpolation predictions to a new set of polygons.

import arcpy
arcpy.env.workspace = "C:/gapyexamples/data"
arcpy.ArealInterpolationLayerToPolygons_ga("AI_layer","new_polys","pred_new_polys","ALL")
ArealInterpolationLayerToPolygons example 2 (stand-alone script)

Aggregate areal interpolation predictions to a new set of polygons.

# Name: ArealInterpolationLayerToPolygons_Example_02.py
# Description: Averages (in the case of Gaussian data) or aggregates (in the cases of Binomial or Poisson)
#    the predictions of an Areal Interpolation layer to a new set of polygons.
# Requirements: Geostatistical Analyst Extension
# Author: Esri

# Import system modules
import arcpy

# Set environment settings
arcpy.env.workspace = "C:/gapyexamples/data"

# Set local variables
inArealInterpolationLayer = "C:/gapyexamples/data/AI_layer.lyr"
inPolygonFeatures = "C:/gapyexamples/data/new_polys.shp"
outFeatureClass = "C:/gapyexamples/output/aiout.shp"
appendAllFields = "FID_ONLY"

# Check out the ArcGIS Geostatistical Analyst extension license
arcpy.CheckOutExtension("GeoStats")

# Execute ArealInterpolationLayerToPolygons
arcpy.ArealInterpolationLayerToPolygons_ga(inArealInterpolationLayer, inPolygonFeatures, outFeatureClass, appendAllFields)

Environnements

Informations de licence

  • Basic: Requiert Geostatistical Analyst
  • Standard: Requiert Geostatistical Analyst
  • Advanced: Requiert Geostatistical Analyst

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