GA Layer 3D To NetCDF (Geostatistical Analyst)

Disponible con una licencia de Geostatistical Analyst.

Resumen

Exports one or more 3D geostatistical layers created using the Empirical Bayesian Kriging 3D tool to netCDF format (*.nc file). The primary purpose of this tool is to prepare the 3D geostatistical layers for visualization as a voxel layer in a local scene.

Learn more about voxel layers

Ilustración

3D geostatistical layer exported to a voxel layer
The voxel layer displays the results of a 3D interpolation.

Uso

  • The Output netCDF file parameter will not automatically add layers to the map or scene. To render the output as a voxel layer, it must be added to a local scene with the same horizontal and vertical coordinate system as the netCDF file. It can also be added to a map or scene as a feature or raster layer using the Make NetCDF Feature Layer tool or Make NetCDF Raster Layer tool, respectively.

  • To render the Output netCDF file as a voxel layer, set the Export locations parameter to 3D gridded points. The voxel layer requires gridded locations in order to render.

  • All Input 3D geostatistical layers must be 3D geostatistical layers created using Empirical Bayesian Kriging 3D.

  • You can choose locations to predict and export in either of the following ways:

    • Predict to 3D gridded points—Predictions will be exported to gridded points in 3D. To use this option, specify 3D gridded points for the Export locations parameter. The X spacing, Y spacing, and Elevation spacing parameters specify the distance between each gridded point in the x, y, and z (elevation) dimensions.
    • Predict to custom 3D locations—Predictions will be exported to custom 3D locations defined by 3D point features. To use this option, specify Custom 3D points for the Export locations parameter, and add 3D point features to the 3D point locations parameter to specify the locations to export. The 3D point locations must have their elevations stored in the Shape.Z geometry attribute. If the elevations are stored as an attribute field rather than Shape.Z, you can convert them to 3D points using the Feature To 3D By Attribute tool.

  • The default output extent of the Output netCDF file parameter is the union of the extents of all Input 3D geostatistical layers.

  • If 3D gridded points is specified for the Export locations parameter, the first point is created at the minimum x-, minimum y-, and minimum z-coordinate of the Output extent environment. The remaining points are created by iterating the X spacing, Y spacing, and Elevation spacing parameter distances through the dimensions of the output extent. If any of the spacing distances do not evenly divide the corresponding dimension of the output extent, one row or column of points will be created beyond the output extent. For example, if the output extent for x is specified as 0 through 10 and the X spacing parameter is specified as 3, the output will have 4 rows in the x-extent: 0, 3, 6, 9, and 12. Similarly, an additional row or column of points will be created if the spacing distances do not evenly divide the y- or z-extents.

Sintaxis

GALayer3DToNetCDF(in_3d_geostat_layers, out_netcdf_file, {export_locations}, {x_spacing}, {y_spacing}, {elevation_spacing}, {in_points_3d}, {output_variables})
ParámetroExplicaciónTipo de datos
in_3d_geostat_layers
[in_3d_geostat_layers,...]

The 3D geostatistical layers that will be exported to the Output netCDF file. If more than one layer is provided, the output will be a multivariate netCDF file.

Geostatistical Layer
out_netcdf_file

The output netCDF file containing the exported values from the Input 3D geostatistical layers.

File
export_locations
(Opcional)

Specifies the locations to export from the Input 3D geostatistical layers. You can export to 3D gridded points or provide custom 3D point features to represent the export locations. If you choose 3D gridded points, you must provide values for the X spacing, Y spacing, and Elevation spacing parameters that represent the distance between each gridded point in all dimensions. If you choose Custom 3D points, you must provide 3D point features in the 3D point locations parameter representing the locations to export.

  • 3D_GRIDDED_POINTSPrediction locations are 3D gridded points. This is the default.
  • CUSTOM_3D_POINTSPrediction locations are defined by custom 3D point features.
String
x_spacing
(Opcional)

The spacing between each gridded point in the x-dimension. The default value creates 40 points along the output x-extent.

Linear Unit
y_spacing
(Opcional)

The spacing between each gridded point in the y-dimension. The default value creates 40 points along the output y-extent.

Linear Unit
elevation_spacing
(Opcional)

The spacing between each gridded point in the elevation (z) dimension. The default value creates 40 points along the output z-extent.

Linear Unit
in_points_3d
(Opcional)

The 3D point features representing locations to export. The point features must have their elevations stored in the Shape.Z geometry attribute.

Feature Layer
output_variables
[[layer_name, output_type, quantile_probability_value],...]
(Opcional)

Specifies the output types for the Input 3D geostatistical layers. You can specify one or more output types for each of the layers or you can apply an output type to all input geostatistical layers. By default, the predictions for all layers will be exported.

To export other output types, specify the layer to export (or choose All to specify all layers) in the first entry of the value table. Specify the output type in the second entry of the value table. If you choose Probability or Quantile as the output type, specify the threshold value (for probability) or the quantile value (for quantile) in the third entry of the value table. If you choose Prediction or Prediction standard error as the output type, you can leave the third entry in the value table empty.

Learn more about geostatistical output types

Value Table

Muestra de código

GALayer3DToNetCDF example 1 (Python window)

Interpolate 3D points twice and convert the outputs to a multivariate netCDF file.

import arcpy
arcpy.ga.EmpiricalBayesianKriging3D("my3DPoints1", "Shape.Z",
                                    "myValueField1", "my3DGALayer1")
arcpy.ga.EmpiricalBayesianKriging3D("my3DPoints2", "Shape.Z",
                                    "myValueField2", "my3DGALayer2")
arcpy.ga.GALayer3DToNetCDF("my3DGALayer1;my3DGALayer2", "outputNCDF.nc",
                           "3D_GRIDDED_POINTS", "50 Meters", "50 Meters", "5 Meters",
                           "", "<ALL> PREDICTION #")
GALayer3DToNetCDF example 2 (stand-alone script)

Interpolate 3D points twice and convert the outputs to a multivariate netCDF file. Export to gridded and custom 3D points.

# Name: GALayer3DToNetCDF_Example_02.py
# Description: Interpolates 3D points and exports to a netCDF file.
# Requirements: Geostatistical Analyst Extension
# Author: Esri

# Import system modules
import arcpy

# Allow overwriting output
arcpy.env.overwriteOutput = True

# Set up variables
in3DPoints1 = "C:/gapydata/inputs.gdb/my3DPoints1"
in3DPoints2 = "C:/gapydata/inputs.gdb/my3DPoints2"
elevationField1 = "Shape.Z"
elevationField2 = "Shape.Z"
valueField1 = "myValueField1"
valueField2 = "myValueField2"
outGALayer1 = "myGALayer1"
outGALayer2 = "myGALayer2"


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

# Execute Empirical Bayesian Kriging 3D twice
arcpy.ga.EmpiricalBayesianKriging3D(in3DPoints1, elevationField1, valueField1, outGALayer1)
arcpy.ga.EmpiricalBayesianKriging3D(in3DPoints2, elevationField2, valueField2, outGALayer2)


# Export predictions for first model and probability that second model exceeds 10
# Export to gridded 3D points

# Set up variables
in_3d_ga_layers = outGALayer1+";"+outGALayer2
out_ncdf = "C:/gapydata/outputs/outputNetCDF1.nc"
export_locations = "3D_GRIDDED_POINTS"
x_spacing = "50 Meters"
y_spacing = "50 Meters"
elev_spacing = "5 Meters"
custom_points = ""
out_vars = "myGALayer1 PREDICTION #;myGALayer2 PROBABILITY 10"

# Run tool.
arcpy.ga.GALayer3DToNetCDF(in_3d_ga_layers, out_ncdf, export_locations,
                           x_spacing, y_spacing, elev_spacing, custom_points, out_vars)


# Export standard errors for first model and 75th quantile for second model
# Export to custom 3D points

# Set up variables
in_3d_ga_layers = outGALayer1+";"+outGALayer2
out_ncdf = "C:/gapydata/outputs/outputNetCDF2.nc"
export_locations = "CUSTOM_3D_POINTS"
x_spacing = ""
y_spacing = ""
elev_spacing = ""
custom_points = "C:/gapydata/inputs.gdb/myCustom3DPoints"
out_vars = "myGALayer1 PREDICTION_STANDARD_ERROR #;myGALayer2 QUANTILE 0.75"

# Run tool.
arcpy.ga.GALayer3DToNetCDF(in_3d_ga_layers, out_ncdf, export_locations,
                           x_spacing, y_spacing, elev_spacing, custom_points, out_vars)

Información de licenciamiento

  • Basic: Requiere Geostatistical Analyst
  • Standard: Requiere Geostatistical Analyst
  • Advanced: Requiere Geostatistical Analyst

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