KrigingModelOrdinary (arcpy.sa)

摘要

定义普通克里金法模型。可用模型类型包括“球面”、“圆”、“指数”、“高斯”和“线性”。

讨论

KrigingModelOrdinary 对象用于克里金法工具。

普通克里金法假设模型为：

 Z(s) = µ + ε(s)

lagSize 的默认值为默认的输出像元大小。

如果未指定 majorRange、partialSill 和 nugget 的默认值，将在内部计算默认值。

语法

KrigingModelOrdinary ({semivariogramType}, {lagSize}, {majorRange}, {partialSill}, {nugget})

参数	说明	数据类型
semivariogramType	Semivariogram model to be used. SPHERICAL —Spherical semivariogram model. CIRCULAR — Circular semivariogram model. EXPONENTIAL — Exponential semivariogram model. GAUSSIAN — Gaussian (or normal distribution) semivariogram model. LINEAR —Linear semivariogram model with a sill. (默认值为 SPHERICAL)	String
lagSize	The lag size to be used in model creation. The default is the output raster cell size.	Double
majorRange	Represents a distance beyond which there is little or no correlation.	Double
partialSill	The difference between the nugget and the sill.	Double
nugget	Represents the error and variation at spatial scales too fine to detect. The nugget effect is seen as a discontinuity at the origin.	Double

属性

属性	说明	数据类型
semivariogramType (读写)	Semivariogram model to be used. SPHERICAL—Spherical semivariogram model. CIRCULAR—Circular semivariogram model. EXPONENTIAL—Exponential semivariogram model. GAUSSIAN—Gaussian (or normal distribution) semivariogram model. LINEAR—Linear semivariogram model with a sill.	String
lagSize (读写)	The lag size to be used in model creation. The default is the output raster cell size.	Double
majorRange (读写)	Represents a distance beyond which there is little or no correlation.	Double
partialSill (读写)	The difference between the nugget and the sill.	Double
nugget (读写)	Represents the error and variation at spatial scales too fine to detect. The nugget effect is seen as a discontinuity at the origin.	Double

代码实例

KrigingModelOrdinary 示例 1（Python 窗口）

演示如何创建 KrigingModelOrdinary 对象以及如何在 Python 窗口的 Kriging 工具中使用该对象。

import arcpy
from arcpy import env
from arcpy.sa import *
env.workspace = "C:/sapyexamples/data"
kModelOrdinary = KrigingModelOrdinary("CIRCULAR", 70000, 250000, 180000, 34000)
outKrigingOrd1 = Kriging("ca_ozone_pts.shp", "ELEVATION", kModelOrdinary, 2000, RadiusVariable(),"")
outKrigingOrd1.save("C:/sapyexamples/output/kordinary1")

KrigingModelOrdinary 示例 2（独立脚本）

使用 KrigingModelOrdinary 对象计算 Kriging 表面。

# Name: KrigingModelOrdinary_Ex_02.py
# Description: Uses the KrigingModelOrdinary object to execute the Kriging tool.
# Requirements: Spatial Analyst Extension

# Import system modules
import arcpy
from arcpy import env
from arcpy.sa import *

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

# Set local variables
inPointFeature = "ca_ozone_pts.shp"
outVarRaster = "C:/sapyexamples/output/ovariance2"

# Create KrigingModelOrdinary Object
lagSize = 70000
majorRange = 250000
partialSill = 180000
nugget = 34000
kModelOrdinary = KrigingModelOrdinary("CIRCULAR", lagSize, majorRange,
                                         partialSill, nugget)

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

# Execute Kriging
outKrigingOrd2 = Kriging(inPointFeature, "ELEVATION", kModelOrdinary, 2000,
                     RadiusFixed(200000, 10), outVarRaster)

# Save the output 
outKrigingOrd2.save("C:/sapyexamples/output/kordinary2")