Diffusion Interpolation With Barriers (Geostatisical Analyst)

Zusammenfassung

Uses a kernel that is based upon the heat equation and allows one to use a combination of raster and feature datasets to act as a barrier.

Learn how Diffusion Interpolation With Barriers works

Verwendung

Syntax

DiffusionInterpolationWithBarriers_ga (in_features, z_field, out_ga_layer, {out_raster}, {cell_size}, {in_barrier_features}, {bandwidth}, {number_iterations}, {weight_field}, {in_additive_barrier_raster}, {in_cumulative_barrier_raster}, {in_flow_barrier_raster})
ParameterErläuterungDatentyp
in_features

The input point features containing the z-values to be interpolated.

Feature Layer
z_field

Field that holds a height or magnitude value for each point. This can be a numeric field or the Shape field if the input features contain z-values or m-values.

Field
out_ga_layer

The geostatistical layer produced. This layer is required output only if no output raster is requested.

Geostatistical Layer
out_raster
(optional)

The output raster. This raster is required output only if no output geostatistical layer is requested.

Raster Dataset
cell_size
(optional)

The cell size at which the output raster will be created.

This value can be explicitly set under Raster Analysis from the Environment Settings. If not set, it is the shorter of the width or the height of the extent of the input point features, in the input spatial reference, divided by 250.

Analysis Cell Size
in_barrier_features
(optional)

Absolute barrier features using non-Euclidean distances rather than line-of-sight distances.

Feature Layer
bandwidth
(optional)

Used to specify the maximum distance at which data points are used for prediction. With increasing bandwidth, prediction bias increases and prediction variance decreases.

Double
number_iterations
(optional)

The iteration count controls the accuracy of the numerical solution because the model solves the diffusion equation numerically. The larger this number, the more accurate the predictions, yet the longer the processing time. The more complex the barrier's geometry and the larger the bandwidth, the more iterations are required for accurate predictions.

Long
weight_field
(optional)

Used to emphasize an observation. The larger the weight, the more impact it has on the prediction. For coincident observations, assign the largest weight to the most reliable measurement.

Field
in_additive_barrier_raster
(optional)

The travel distance from one raster cell to the next based on this formula:

(average cost value in the neighboring cells) x (distance between cell centers).

Raster Layer
in_cumulative_barrier_raster
(optional)

The travel distance from one raster cell to the next based on this formula: (difference between cost values in the neighboring cells) + (distance between cell centers).

Raster Layer
in_flow_barrier_raster
(optional)

A flow barrier is used when interpolating data with preferential direction of data variation, based on this formula:

Indicator (cost values in the to neighboring cell > cost values in the from neighboring cell) * (cost values in the to neighboring cell - cost values in the from neighboring cell) + (distance between cell centers),

where indicator(true) = 1 and indicator(false) = 0.

Raster Layer

Codebeispiel

DiffusionInterpolationWithBarriers example 1 (Python window)

Interpolate point features that are constrained by a barrier onto a rectangular raster.

import arcpy
arcpy.env.workspace = "C:/gapyexamples/data"
arcpy.DiffusionInterpolationWithBarriers_ga("ca_ozone_pts", "OZONE", "outDIWB",
                                            "C:/gapyexamples/output/diwbout", "2000",
                                            "ca_outline", "", "10", "", "", "", "")
  
DiffusionInterpolationWithBarriers example 2 (stand-alone script)

Interpolate point features that are constrained by a barrier onto a rectangular raster.

# Name: DiffusionInterpolationWithBarriers_Example_02.py
# Description: Diffusion Interpolation with Barriers uses a kernel which is based
#   upon the heat equation and describes the variation in temperature with time
#   in a homogeneous medium.
# 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 = "outDIWB"
outRaster = "C:/gapyexamples/output/diwbout"
cellSize = 2000.0
power = 2
inBarrier = "ca_outline.shp"
bandwidth = ""
iterations = 10
weightField = ""
addBarrier = ""
cumuBarrier = ""
flowBarrier = ""

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

# Execute DiffusionInterpolationWithBarriers
arcpy.DiffusionInterpolationWithBarriers_ga(inPointFeatures, zField, outLayer,
                                            outRaster, cellSize, inBarrier,
                                            bandwidth, iterations, weightField,
                                            addBarrier, cumuBarrier, flowBarrier)


Umgebungen

Verwandte Themen

Lizenzinformationen

ArcView: Erfordert Geostatistical Analyst
ArcEditor: Erfordert Geostatistical Analyst
ArcInfo: Erfordert Geostatistical Analyst

7/10/2012