Disponible con licencia de Image Analyst.
Disponible con una licencia de Spatial Analyst.
Resumen
Performs subpixel classification and calculates the fractional abundance of land-cover types for individual pixels.
Debate
For more information about how this function works, see the Linear Spectral Unmixing raster function.
The referenced raster dataset for the raster object is temporary. To make it permanent, you can call the raster object's save method.
Sintaxis
LinearUnmixing (in_raster, in_spectral_profile_file, {value_option})| Parámetro | Explicación | Tipo de datos |
in_raster | The input raster. | Raster |
in_spectral_profile_file | The path to the spectral profile for the various land cover classes. This can be provided as a polygon feature class, a classifier definition file (.ecd) generated from the Train Maximum Likelihood Classifier tool, or a JSON file (.json) that contains the class spectral profiles. | String |
value_option | Specifies how the output pixel values will be defined.
Both options can be specified by delimiting with a semicolon: "SUM_TO_ONE;NON_NEGATIVE". | String |
| Tipo de datos | Explicación |
| Raster | The output raster. |
Muestra de código
This example resolves the fractional class values for each pixel in the multispectral raster.
from arcpy.ia import *
out_linearunmixing_raster = LinearUnmixing(
"Landsat8.tif","C:/arcpyExamples/data/training_feature.ecd")
out_linearunmixing_raster.save(
"C:/arcpyexamples/outputs/linearunmix_output.tif")This example resolves the fractional class values for each pixel in the multispectral raster.
# Import system modules
import arcpy
from arcpy.ia import *
# Check out the ArcGIS Image Analyst extension license
arcpy.CheckOutExtension("ImageAnalyst")
# Set the local variables
in_raster = "C:/data/Landsat_8.tif"
in_spectral_profile = "C:/data/training_features.ecd"
value_options = "SUM_TO_ONE;NON_NEGATIVE"
# Apply LinearSpectralUnmixing function
unmixing_outputs = LinearUnmixing(in_raster, in_spectral_profile, value_options)
# Save the output
unmixing_outputs.save("C:/arcpyExamples/outputs/unmixing_results.tif")